Course Dates and Deadlines
Horizon Labs features flexible start dates. Students should apply 4-6 weeks prior to their preferred start date. Horizon Seminar has fixed term dates and a formal application deadline.
Applications for Horizon Seminar are now closed for summer 2023 and open for fall of 2023. Applications for Horizon Labs are open for students interested in beginning research 4 weeks after their date of application.
Fall 2023
Horizon Seminar: October 21, 2023 - February 10, 2024
Application Deadline: September 21, 2023
Financial Aid Deadline: September 14, 2023
Horizon Labs: Start dates are flexible and there is no deadline, but students must apply at least 4 weeks prior to a contemplated start date.
Spring 2024
Horizon Seminar: March 1, 2024 - June 30, 2024
Application Deadline: February 1, 2024
Financial Aid Deadline: January 4, 2024
Horizon Labs: Start dates are flexible and there is no deadline, but students must apply at least 4 weeks prior to a contemplated start date.
Horizon Seminar Courses
Horizon Academic offers two distinct kinds of research experiences: Horizon Labs, which is a one-on-one research mentorship program, and Horizon Seminar. Horizon Seminar allows high school students to complete a college-level research project under the guidance of a professor or lecturer with decades of teaching experience in their field. Students develop individualized research topics and attend small group classes, with an average class size of 4 and a maximum of 6 students. Our Senior Instructors lead 14 classes throughout the trimester, and our Teaching Assistants (who tend to be masters or PhD students in these fields) offer an additional 6 sessions for review, discussion, and feedback. Although Horizon Seminar classes meet in small groups of 4-6 students, all students complete their own individual research project and are not expected to agree upon a research topic with other students.
(Unavailable Fall 2023)
How do ecosystems collapse? How can we engineer solutions to environmental catastrophe? Dr. Truncer’s course explores how human society can react to environmental systems collapse. Students may examine and research a variety of sustainability issues with regard to agricultural production, urbanization, infrastructure, resource use, and modern day engineering innovations. Dr. Truncer has previously taught this course at Harvard University and Stanford University.
How does our psychology influence the decisions we make every day and, ultimately, economic outcomes? We explore the rules-of-thumb that our brains constantly employ to makes choices, and how they can backfire, leading to biases in our decisions. You will be a participant in live experiments and learn how social scientists use them to study behavior. Professor Gallo has previously taught at Harvard and Oxford, and he currently teaches behavioral economics at Cambridge.
(Only Available Spring and Summer Terms)
The course will explain and illustrate research methods in psychology using current research on human emotions, emotion regulation, and emotional disorders. Students will become familiar with research methods and experimental designs in these areas. Students will also design a study on a current topic of their choice in one of these areas.
(The Seminar track of this course is only available in the spring and summer terms, turn to the Labs track for a year-round option)
What are the causes of war and peace? How does the international system affect the behavior of states, and how does this affect people on the ground? We explore the theories, patterns, and frameworks of international relations. We critically examine controversies surrounding current phenomena such as world governance, state failure, international injustice, and great power competition. Professor Rezvani had previously taught this course at Dartmouth, Harvard, and Oxford.
(Only Available Summer Terms)
Knot Theory is the mathematical branch of topology with many applications, including analyzing DNA structures. In this theoretical math course, we study knot theory with an eye for one of the most foundational uses of all: understanding causality and the relationship between events. We will analyze models of knots and links in 2+1-dimensional spacetimes and apply computable link invariants to study what invariants can plausibly enable us to detect causality between two points or events.
(Only Available in Summer Terms)
Internet attacks are increasingly sophisticated and complex, and they can have huge impact on our everyday lives. Do you really know how the Internet works? Are you sure that your personal data is well protected? In this class, we will first build our background knowledge on how computers communicate with one another through the internet. Then, we'll use machine learning approaches to detect compromised machines through network traffic, denial of service attacks, and hijacking attacks.
(Only available in Summer terms)
Public social media platforms have become very popular avenues for many people to get news to share their thoughts, feelings, and worldviews. In turn, social media data feeds can provide invaluable insights and strong signals of emerging problems. For example, leveraging powerful machine learning tools and social media feeds, we can detect when a social media account is involved with spreading misinformation, fake news, and hate speech, or in engaging in cyberbullying or malicious “trolling.” Additionally, we can predict when a user might have indications of mental health decline such as depression.
(Only Available in Summer Terms)
Computational neuroscience is divided into three subspecialties: neural coding, biophysics of neurons, and neural networks. This course explores how the brain processes information from the cellular level and the network level with the aim of explaining what nervous systems do and how they function. Students will be familiarized with the basic techniques of modeling biophysics, excitable membranes, small and large-scale network systems, neuroengineering methods and technologies for studying therapeutic solutions to brain diseases or damage to the CNS.
(Only Available in Summer Terms)
This course aims to convey theoretical and practical knowledge on the pathophysiology, clinical features, epidemiological aspects, treatment regimens, and neurobiological substrates of neurodegenerative diseases and explore the molecular, cellular and network pathways that are connected to the neurology and neuroscience of such diseases. While “neurodegenerative disease” is an umbrella term for a wide range of conditions that influence neurons in the central and peripheral nervous system, the focus will be on Alzheimer’s Disease, Parkinson’s Disease, Huntington’s Disease, Amyotrophic Lateral Sclerosis and Traumatic Brain Injury.
The availability of computer power and massive data has propelled the growth of data science as a discipline and its application to numerous fields. In this course, we study machine learning techniques, the mathematics behind those techniques, and the computer language Python, to implement those techniques on real data. As a course project, the student will have the option of analyzing a real data set or exploring mathematical aspects of machine learning. The topics of the possible course projects are listed below.
(Only Available in Summer Terms)
This course explores algorithms, data structures, and the Python programming language. In the course, students will better understand the mechanics of how real-world computer programs work and how to develop their own programs in Python. We focus on efficient algorithm design, something which allows smaller and less complex devices like wearables to do tasks that once required powerful processors and which has brought down the cost of life-saving research like genomic sequencing from billions to only hundreds of dollars.
Horizon Labs Courses
Horizon Labs offers high school students the opportunity to work one-on-one with leading researchers and lecturers from some of the world's best known universities to develop highly specialized and unique research projects in interdisciplinary topics in the sciences and humanities. Horizon Labs allows students to get individualized mentorship from instructors who are on the front lines of PhD-level research, often who are in the process of completing their own PhD or postdoctoral research. These instructors are intimately acquainted with the latest studies, the most relevant data sets, and the most interesting perspectives being introduced in their respective fields. Through 20 hours of one-on-one mentorship with their instructors, Horizon Labs students can get access to useful and unique data sets, develop customized reading lists to enrich their writing, get individualized feedback about their paper drafts, and hear advice on publication opportunities from experts in their fields.
Machine learning and predictive analytics can be used in a stunning number of ways. From predicting the price of a stock you buy, to estimating the chances that your flight will be delayed, to estimating how well your favorite sports team might do next game, to even guessing the outcomes of a Supreme Court case, machine learning can help us predict the world around us. This course examines interesting and unlikely applications of machine learning that advance social goals, improve economic efficiency, or better understand the world around us.
What is a ‘mind’? How do our minds hook onto the world? Are artificial intelligences genuine minds? Could trees be conscious? How can we scientifically study the mind, which is something we seem to know only through introspection? How do minds come to know the physical world? This course uses philosophy and cognitive science to investigate the nature of mind, consciousness and cognition. Students can focus on interpreting scientific experiments or on more philosophical issues. This is an adapted version of a course that Dr. Craig taught at Oxford University.
The decisions we make are always affected by the decisions of others. This course will study the different circumstances in which humans interact on a pair, community, and national scale. We will cover a wide range of topics, starting with popular models in game theory such as the Prisoners Dilemma and different versions of auctions. We will then progress to understanding how information and preferences can spread through different networks, focusing on how these networks are formed and taking examples from social influence and epidemic spreading. Finally, we explore decision making in the context of politics.
How did life begin? What is the basis for human life and how are scientists learning to manipulate our genetic code? How can CRISPR allow use to control genetic expressions and human development? How is CRISPR being used in cutting edge diagnostic approaches and treatments? How can we theorize and understand the medical and social risks of CRISPR? This course allows students to interpret, understand, and perhaps build on leading scientific research on CRISPR and Gene Editing.
Horizon Academic is thrilled to offer a full range of 72 subtopics in psychology, spanning key questions in clinical, social, developmental, and cognitive psychology. Our psychology program started out with a narrower focus on data science and pathology, but our psychology offerings have continued to grow as more instructors of diverse psychology backgrounds have joined our team. We invite you to have a closer look at the many diverse psychology sub-topics we offer.
Never before has there been so much available data about various diseases and possible genetic associations with them. At the same time, new machine learning tools and data science techniques are enabling researchers to identify patterns and linkages between genes and disease. In this course, we first begin by reviewing key concepts in data analysis and machine learning. From there, students may explore connections between genetics and cardiovascular disease, autism, heart disease, allergies or autoimmune diseases.
Fluid dynamics governs the water you drink, the air you breathe, and the blood running through you — even the plasma that makes up the stars. The intricacies of fluid motion are easily seen by watching phenomena such as the flame or smoke of a candle, the clouds moving overhead, or the ocean waves breaking against the shoreline — all fluids without a repeated pattern. The motion is constantly changing, sensitive to perturbations, and therefore difficult to predict. Fluid dynamics provides us the tools to better understand these complicated motions — through analytic, experimental, and computational study.
What are proteins? How do enzymes speed up chemistry? What do the proteins in photosynthesis and the electron transport chain actually do to capture energy? What role do they play in the emerging antibiotic resistant bacteria which are increasing mortality in hospitals and how do they influence viral infection? Is there anything proteins can teach us about physics? In this course we will discuss these questions and more based on our own research and multiple biophysics courses we have taken from world leaders in these topics at Stanford.
How do organizations make good decisions, and why do they sometimes make bad ones? In what ways can team dynamics be improved? How can businesses foster creativity and innovation, and why are they important? This course examines the intersection of business and management studies, behavioral sciences, and psychology. Organizations, such as schools, startups, non-profits, corporations, and governments, are complex social systems that influence, and are influenced by, individual and group behavior.
How was slavery classified in the Greco-Roman world? What alternative forms of bondage existed alongside it? What were the conditions of the slave systems during this time? How might we imagine the lives of those under bondage? To what extent were slaves able to express their autonomy? How was love expressed among people in the Greco-Roman world? Are there any compelling cases in other eras that merit further comparisons? In this course, we work to gather an accurate picture of ancient Greek and Roman civilizations, not only from the perspective of political leaders and social elites, but from the perspective of the laborers, artisans, soldiers, and slaves who made up the majority of these societies.
How is it that you can smell a shampoo fragrance hours after cleaning your hair? What is the purpose of the long list of ingredients in your favorite snack? How can you control the release of new therapeutic drugs in human bodies? This class begins with key concepts on formulation chemistry (emulsion preparation, system stability, encapsulation techniques, characterization methods) before studying concrete applications in filtration, food, paints & coatings, cosmetics or pharmaceutical industries. Projects may consist of applications of machine learning to predict chemical reactions or material properties, or extensive literature reviews on a specific scientific challenge at the intersection of formulation chemistry and Material Science.
In recent decades, views on what constitutes a “mental illness” and what constitutes humane treatments have evolved with social norms. Psychopathology has also become increasingly amenable to the discussion of “public issues” that fall outside of an individual’s private life. This course takes a sociological lens to the study of psychotherapy, grounding itself in the emergence of a modern “therapeutic society.” We focus on the practice of psychotherapy itself and the topics that individuals bring to psychotherapy, as well as how those topics are discussed in society. In so doing, we consider both the role of “the medical expert”—the therapist—and the role of “the patient”—the individual attending therapy.
We investigate the concepts central to the writing and understanding of history. These include, on the one hand, theoretical concepts like objectivity, historical fact, causality, agency, determinism, and morality; on the other, more empirical concepts like nation, empire, revolution, global, race, culture, and identity. Reading selected writings by distinguished historians, we will analyze how these concepts shape the way historical events and processes are interpreted.
What justifies the authority of the state? What are the basic liberties that a just society should secure? How should societies reckon with implicit bias, historical injustices, and structures of racism, classism, and sexism? Can meritocracy exist alongside entrenched privilege? We examine these questions and more in Mr. Cabezas's course, based on his section of the Contemporary Civilization (CC) course at Columbia University.
Horizon Academic offers a wide range of 57 sub-topics in neuroscience, ranging from social neuroscience, neurobiology, and more than a dozen topics about neurodegeneration disorders. Originally created in collaboration with two of our instructors working at the Department of Physiology Anatomy & Genetics at Oxford, our neuroscience offerings have continued to grow in recognition of our students' diverse interests in this exciting field.
What are the causes of war and peace? How does the international system affect the behavior of states, and how does this affect people on the ground? We explore the theories, patterns, and frameworks of international relations. We critically examine controversies surrounding current phenomena such as world governance, state failure, international injustice, and great power competition.
Horizon Seminar
Small Group Classes. Individualized Research Projects. Taught by Professors and Lecturers.
Environmental Problems in Human Society:
Lessons from the Past, Engineering Future Solutions
【 James Truncer 】
How do ecosystems collapse? How can we engineer solutions to environmental catastrophe? Dr. Truncer’s course explores how human society can react to environmental systems collapse. Students may examine and research a variety of sustainability issues with regard to agricultural production, urbanization, infrastructure, resource use, and modern day engineering innovations. Dr. Truncer has previously taught his course at Harvard and Stanford University.
Pre-approved Topic List
1. What advantages does organic farming have over conventional farming? Can organic farms compete with conventional farms in feeding the world?
2. How can cities and their infrastructure be designed for the predicted changes in climate? Provide specific examples in your response.
3. The recent tremendous growth of urban areas has created a multitude of environmental problems and challenges. Choose one area of urban design that can improve the urban environment – what costs and benefits are involved?
4. What are the latest advances in hydroponic and vertical farming? Are these the food production methods of the future? What are the costs?
5. Are the economic benefits of dam building worth the environmental costs?
6. Sea level rise is expected to impact many coastal cities and islands (e.g. Andaman Islands) in the coming years. What are the advantages or disadvantages of relocating an island settlement or city versus building dikes and protective barriers such as in the case of the Netherlands?
7. Are genetically modified organisms (GMOs) significantly different from the variation produced through more traditional methods of cross-breeding and the creation of hybrids?
8. Oceans are absorbing increasing amounts of carbon dioxide and are becoming more acidic. How will this affect marine ecosystems and thus human society? What policies might be implemented to make the public more aware of this looming environmental crisis and what incentives would encourage governments to take action?
9. Money and research are now being poured into the technology of self-driving cars. Is maintaining the concept of “car” an efficient means of transportation, or are there better, more sustainable systems for the movement of people?
10. Soil erosion is severe in many areas of the world. What farming methods and other activities are creating this erosion? What farming methods can not only reduce soil erosion but build nutrient-rich soil that enhances crop yields and lowers carbon emissions substantially? What policies might encourage soil conservation on farmland?
11. Renewable energy sources are gaining more and more attention, and represent an increasingly larger percentage of energy production. What is the most promising type of renewable energy and why? Can modern society completely convert to renewable energy sources from a largely carbon-based system? What further advances or changes in lifestyle might be required?
12. Most large farms rely on mechanization and need to add massive amounts of artificial fertilizer to produce high crop yields. How did this situation come about, and is this a sustainable practice? What are the carbon costs of such agriculture and are there feasible alternatives?
13. Can sustainable practices be successfully incorporated into current business models? If not, what might need to change in order to create a better fit?
14. Are United Nations treaties and resolutions an effective means to pass worldwide sustainability measures or is a different system necessary?
15. Some architects are now designing “walkable” cities. What does this mean and what are the advantages and disadvantages of such an urban design? Illustrate your response with examples.
16. Aquaculture, or fish farming, is increasingly providing a major source of food for a growing world population. What forms of aquaculture are most sustainable, and which forms are the least sustainable? Why? Provide specific examples of aquaculture in your analysis.
Behavioral Economics
【 Edoardo Gallo 】
How does our psychology influence the decisions we make every day and, ultimately, economic outcomes? Professor Gallo's course explores the heuristics, or rules-of-thumb, our brain constantly employs to makes choices, and how in some instances they systematically backfire leading to biases in our decisions. You will be a participant in live experiments and learn how social scientists use them to study how people behave. Professor Gallo has previously taught at Harvard and Oxford, and he is currently teaching behavioral economics as well as other courses at Cambridge.
Pre-approved Topic List
1. What behavioral principles should be used to design a pension scheme?
2. What type of policies mitigate the bad consequences of unemployment?
3. Design an insurance policy that is going to attract consumers by exploiting psychological biases.
4. Humans are prone to errors when making decisions under uncertainty. How can modern technology reduce these errors?
5. Pollution is a problem affecting most large metropolitan areas. How may insights from psychology inform urban policy to decrease pollution?
6. Top students from disadvantaged backgrounds often do not apply to the best universities. What are the potential reasons and what kind of actions can be taken to change this?
7. Doctors routinely make recommendations that may have life/death implications for their patients. How can biases in decision-making affect their advice?
8. How can we increase the rate at which individuals recycle?
9. Describe how psychological biases may affect judicial decisions and propose policy changes to minimize their negative impact.
10. Delays in paying income tax lead to significant financial losses from governments. What design changes could be made to tax collection policy to minimize these delays?
11. Buying a house is an infrequent transaction with large financial consequences. In what ways can a prospective house buyer or seller avoid mistakes due to psychological biases?
12. A new type of fertilizer has been invented that increases crop yields by 300%. Nevertheless, farmers are not adopting it. What could be the reasons and what policies can be implemented to increase takeup?
13. A major supermarket chain has hired you as a consultant to apply behavioral principles to improve their sales. Write a report with your recommendations.
14. You are a financial advisor for a wealthy individual. Come up with an investment strategy that avoids pitfalls from biases in decision making.
15. Develop an idea for a phone app that uses insights from behavioral economics to improve an individual’s health.
Controversies in International Relations
【 David Rezvani 】
What are the causes of war and peace? Professor Rezvani’s course explores the theories, patterns, and frameworks of international relations. It critically examines controversies surrounding current phenomena such as world governance, state failure, international injustice, and great power competition. Professor Rezvani had previously taught at Harvard, MIT, and Oxford University.
Pre-approved Topic List
1. Should countries (like the US or others) allow companies and individuals to hack back against foreign cyber attackers?
2. Which country has the best model for fighting global pandemics?
3. What strategy should the US adopt for managing its relations with China?
4. What is the greatest challenge to China’s “Belt and Road” initiative and how can it be overcome?
5. Should other countries be happy or worried about the Asian Infrastructure Investment Bank (AIIB)?
6. What is the best type of free trade agreement for Asia?
7. What explains China’s remarkable economic growth?
8. Is China a revisionist or status quo power?
9. Was Brexit the right decision for the United Kingdom?
10. What political outcome has the best chance at resolving the Israeli-Palestinian conflict?
11. In light of the massive flow of refugees from places like Ukraine and the Middle East to Europe, is international migration bad for host countries?
12. What is the best solution to address the plight of the Rohingya?
13. Should the international community prohibit Iran from obtaining nuclear weapons?
14. Is global poverty better reduced through free trade or international aid?
15. Does humanitarian disaster justify military intervention?
16. Was it a right choice for America and its allies to have invaded Libya?
17. What role should countries play in their policy toward Syria?
18. What strategy should the US adopt for managing its relations with Russia?
19. Do you believe that Russia’s aggression toward Ukraine is the West’s fault?
20. What carbon tax or carbon emission trading scheme do you favor to address the threat of global warming?
21. In light of the similarities and differences between credit monitoring systems in different countries, what changes, if any, would you make to China’s social credit system?
Theoretical Mathematics: Studying Knots, Links, Invariants to Prove Causality
【 Vladimir Chernov 】
Only available Summer Terms
Prerequisites: Students will need to have completed Calculus 1 before beginning this course. This requirement would be satisfied by the completion of AP Calculus A/B, IB Math HL, or the equivalent offered in your school. Please note that Statistics and Pre-Calculus are not sufficient to satisfy this prerequisite.
Knot Theory is the mathematical branch of topology with many applications, such as analyzing DNA structures. In this theoretical math course, we study knot theory with an eye for one of the most foundational uses of all: understanding causality and the relationship between events. Identifying cause and effect is foundational: to understanding the physics that govern our universe to functioning in daily life. Two points or events in a spacetime are causally related if one can get from one of them to the other without exceeding the speed of light. Mathematicians and physicists have related causality in spacetimes to the study of knots and links, and knot theorists often study simplified, flatted models of knots we encounter in everyday life, such as shoelaces tied together, to develop models for how we might understand causality and complex objects. We will analyze models of knots and links in 2+1-dimensional spacetimes and apply computable link invariants to study what invariants can plausibly enable us to detect causality between two points or events, drawing on the work in particular of Samantha Allen and Jacob Swenberg. Students will be free to select their own research topic relevant to knot theory, but Prof. Chernov is able to recommend particular racks or quandles that students can analyze. Student projects will examine which (of the many available) quandle invariants can be combined to the Alexander-Conway polynomial in order to plausibly detect causality in the toy models of the 2+1 dimensional spacetimes.
Detailed Course Description
Student projects will build on major developments in knot theory, culminating in their independent research topics. In order to reach this, students will examine the following theoretical developments:
1. Robert Low (a student of a recent Nobel Prize Winner Sir Roger Penrose) posed a conjecture relating causality in toy models, of (2+1)-dimensional spacetimes to the study of knots and links, essentially circular shoelaces tied together in different configurations. The Low conjecture was expanded on by Jose Natario and Paul Tod in the Legendrian Low conjecture to examine real world (3+1)-dimensional spacetimes and led to the question communicated by Penrose on the Vladimir Arnold Problem List. These conjectures and the questions were solved in the works of Stefan Nemirovski and Vladimir Chernov.
2. In order to be able to apply these results to the real life problems, one needs to have computable invariants of links that completely determine causality. The work of Gage Martin, Ina Petkova and Vladimir Chernov show that the very powerful but computable Heegaard-Floer and Khovanov Homology Theories do solve this problem for the toy models of the (2+1)-dimensional spacetimes.
3. The very recent work of Samantha Allen and Jacob Swenberg studied the question of whether the Alexander-Conway polynomial and the Jones polynomial are enough for this purpose. These polynomial invariants are obtained from the above homology theories by omitting much information, and the results of Allen and Swenberg suggest that the Jones polynomial is enough to detect causality, but the Alexander-Conway polynomial is likely not enough.
4. Quandles and Racks are the classical and somewhat technical, but computable, link invariants that generalize the tri-coloring invariant. In this course, we will discuss all the theories mentioned above, and students will develop projects exploring which of the many Quandle invariants should be added to the Alexander-Conway polynomial so that it becomes plausible that they together completely detect causality in toy models of (2+1)-dimensional spacetimes. Examples of quandles that one can try to use are the Takasaki and more generally Alexander quandles and symplectic quandles. Invariants that are related to the quandle coloring invariants are the ones coming from quandle cocycles. We will discuss what these are and how to work with them and build some of the projects on this approach.
Clinical Psychology and Emotion Regulation
【 Bridget Callaghan 】
Only available Spring and Summer Terms
The course will explain and illustrate research methods in psychology using current research on human emotions, emotion regulation, and emotional disorders. Students will become familiar with research methods and experimental designs in these areas. Students will also design a study on a current topic of their choice in one of these areas.
Pre-approved Topic List
1. Does it make sense to think of mental disorders as discrete categories or dimensions that we all vary on?
2. How do we regulate our emotions? How does emotion regulation go awry in psychopathology?
3. How can moods and emotions be measured and manipulated?
4. Are cognitions important for emotions?
5. What are the implications of cognitive approaches towards emotions for our understanding and treatment of emotional disorders.
6. Why are we not better at treating mental disorders?
7. Are today's youth really more anxious and depressed than youth in the past? If so, what is contributing to this increase?
8. How do scientists study treatments for mental health problems? What are empirically supported treatments, why are they useful, and what are their limitations?
9. How can mental health treatments be delivered? What are the advantages and disadvantages of certain delivery formats?
10. How can we increase access to mental health treatments?
11. What is depression, exactly? Is it one syndrome, or is it a collection of different syndromes that we grouped under the same name?
Leveraging Machine Learning and Social Media to Detect Fake News, Understand Mental Health, and Combat Cybercrime
(Only Available Spring and Summer Terms)
Public social media platforms have become very popular avenues for many people to get news to share their thoughts, feelings, and worldviews. In turn, social media data feeds can provide invaluable insights and strong signals of emerging problems. For example, leveraging powerful machine learning tools and social media feeds, we can detect when a social media account is involved with spreading misinformation, fake news, and hate speech, or in engaging in cyberbullying or malicious “trolling.” Additionally, we can predict when a user might have indications of mental health decline such as depression. Finally, we can detect when accounts on social media are being misused or abused for malicious purposes such as spamming, participating in cyberattacks, or proliferating malicious software. In this class, we will work with real world social media datasets (Twitter, Reddit, etc.) and applied machine learning techniques to develop models that indicate when a problem is under the way.
Pre-approved Topic List
1. Digital Epidemiology: Mental health and social media
2. Predicting Depression using social media data
3. Detecting fake news and misinformation
4. Modeling the spread of information over social media
5. Detecting hate speech
6. Identifying cyberbullying on social media
7. Applying graph analysis techniques on social media
8. The formation of communities on social media
9. Non-Coding Track: public policy and regulation of social media
Data Science Approaches to Internet Security
(Only Available Summer Terms)
Internet attacks are increasingly sophisticated and complex, and they can have huge impact on our everyday lives by disconnecting entire networks, disrupting food and gas supply chains, and leaking sensitive financial and personal information. As a result, the need for experts in all aspects in the Cybersecurity field is continuously increasing. In this class, we will first build our background knowledge on how computers communicate with one another, and how they work as parts of the Internet. Then we will learn about the indications that a device (computers, servers, handheld devices, and IoT / household devices connected to the Internet) is compromised or has atypical behavior. We use machine learning approaches to detect compromised machines through network traffic, denial of service attacks, and hijacking attacks. The course also features a non-coding track for students who are interested in the public policy and regulatory aspects of Cybersecurity. Skills we will focus on include Data science, Machine Learning, Network Traffic analysis, Internet Policies.
We will work with real datasets on cross disciplinary projects.
Pre-approved Topic List
1. How does the Internet work?
2. How to detect compromised devices?
3. Hands-on Internet Security: Network Traffic Analysis
4. What could bring the Internet down? Introduction to Security and overview of Internet Attacks.
5. Hands-on Internet Security: Denial of Service Attacks (DoS)
6. Hands-on Internet Security: Hijacking attacks
7. How global physical and political events impact the Internet?
8. Non-Coding Track: Public Policies and the Internet
Neurodegenerative Diseases: Pathogenesis and Pathophysiology
This course aims to convey theoretical and practical knowledge on the pathophysiology, clinical features, epidemiological aspects, and neurobiological substrates of neurodegenerative diseases and explore the molecular, cellular and network pathways that are connected to the neurology and neuroscience of such diseases. While “neurodegenerative disease” is an umbrella term for a wide range of conditions that influence neurons in the central and peripheral nervous system, the focus will be on Alzheimer’s Disease, Parkinson’s Disease, Huntington’s Disease, Amyotrophic Lateral Sclerosis and Traumatic Brain Injury. The course will unravel the complex relationships between the genetics of neurodegeneration, pathomechanisms of disease development, epidemiology, molecular biology, pharmaceutical chemistry, neurobiology, imaging, assessments, and treatment regimens. Upon completion of this course, students will obtain an overall understanding of neurodegeneration and gain detailed insight into these most common neurodegenerative disorders. The course will first cover foundational topics and then goes relatively in depth in covering the classical and cutting-edge research on the mechanisms that have been discovered to play a role in each of the neurodegenerative diseases to be tackled. Students will also be able to critically evaluate papers from the primary scientific literature.
Pre-approved Topic List
1. Why is it important to study neurodegenerative diseases and what are the most common neurodegenerative diseases?
2. What are the basic cellular and circuit processes that are affected by each of the neurodegenerative diseases that the course will tackle?
3. What are the molecular mechanisms that underlie the different neurodegenerative diseases and what are the molecular pathologies in each?
4. How are biomarkers used in neurodegenerative disease diagnosis, and why are new biomarkers needed for such diseases?
5. What are the common mechanisms and strategies for the treatment of neurodegenerative diseases?
6. What are the current diagnostic methods and criteria as placed within the recent developments in neuropathology?
7. How do the etiopathogenetic factors vary across the different neurodegenerative diseases?
8. Why are we not better at treating neurodegenerative diseases?
9. How are the neuropathological and multisystem neurodegeneration processes different across the different neurodegenerative diseases?
10. How can we increase access to neurodegenerative diseases treatments?
11. Can we use gene editing to study neurodegeneration? Can CRISPR be used as genetic therapy?
12. Why are current treatments considered ineffective? How can we develop new therapies for these disorders?
13. Can we reverse neurodegeneration? What would be some of the strategies for this?
14. How does our lifestyle impact our risk for developing neurodegenerative disease? Exercise, diet, education, social connection - how do all of these factors impact our disease risk? Are lifestyle modifications effective for disease prevention?
Algorithms, Data Structures, and Python
(Available Beginning Summer 2024)
Algorithms are sets of instructions to execute tasks. The task may seem as simple as sorting alphabetically a set of words, or complex such as the reconstruction of genomes from biochemical experiments or the encryption of sensitive data for safety purposes.
There are several algorithms to accomplish the same task, but some algorithms are more efficient than others. The efficiency of an algorithm depends to the number of operations and the memory space required for its execution. If an algorithm is not efficient, it may require so much time or memory to execute that it becomes useless. The reading of genomes is an example of this fact. Reading genomes involves biochemical experiments to collect data, and algorithms to process this data on computers. The development of efficient algorithms to read genomes helped decrease its cost from billions to just hundreds of dollars.
Data structures refers on how the data is represented. Data structures go hand with algorithms. Different algorithms may require different data structures
This course is in algorithms, data structures and the programming language Python. It is recommended only for students should enjoy computer science and mathematics. After completing this course, students will understand how many real-world programs work, and will also be able to write their own programs in Python.
Pre-approved Topic List
1. Given an unsorted integer array, find a pair with the given sum in it.
2. Finding the longest subsequence present in given two sequences in the same order, i.e., find the longest sequence which can be obtained from the first original sequence by deleting some items and from the second original sequence by deleting other items.
3. Given an integer array, find a contiguous subarray within it that has the largest sum.
4. Given an unlimited supply of coins of given denominations, find the total number of distinct ways to get the desired change.
5. We are given a set of items, each with a weight and a value, and we need to determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible.
6. Given a set of positive integers and an integer k, check if there is any non-empty subset that sums to k.
7. The Longest Palindromic Subsequence (LPS) problem is finding the longest subsequences of a string that is also a palindrome.
8. Matrix chain multiplication problem: Determine the optimal parenthesization of a product of n matrices.
9. The longest common substring problem is the problem of finding the longest string (or strings) that is a substring (or are substrings) of two strings.
10. Given a rod of length n and a list of rod prices of length i, where 1 <= i <= n, find the optimal way to cut the rod into smaller rods to maximize profit.
11. Word Break Problem: Given a string and a dictionary of words, determine if the string can be segmented into a space-separated sequence of one or more dictionary words.
12. The Levenshtein distance between two words is the minimum number of single-character edits (i.e., insertions, deletions, or substitutions) required to change one word into the other. Each of these operations has a unit cost. Develop an algorithm to compute the Levenshtein distance between two words.
13. Given a chessboard, find the shortest distance (minimum number of steps) taken by a knight to reach a given destination from a given source.
14. Given a set of positive integers, check if it can be divided into two subsets with equal sum.
15. 3-partition problem: Given a set S of positive integers, determine if it can be partitioned into three disjoint subsets that all have the same sum, and they cover S.
16. Find the minimum number of throws required to win a given Snakes and Ladders board game.
17. Given an integer array, find the largest subarray formed by consecutive integers. The subarray should contain all distinct values.
18. Given an array containing only 0’s, 1’s, and 2’s, sort it in linear time and using constant space.
19. Given a chessboard, print all sequences of moves of a knight on a chessboard such that the knight visits every square only once.
20. Given an N × N matrix of integers, find the maximum sum submatrix present in it.
21. Given a string, find the maximum length contiguous substring of it that is also a palindrome. For example, the longest palindromic substring of “bananas” is “anana”, and the longest palindromic substring of “abdcbcdbdcbbc” is “bdcbcdb”.
22. Given a list of tasks with deadlines and total profit earned on completing a task, find the maximum profit earned by executing the tasks within the specified deadlines. Assume that each task takes one unit of time to complete, and a task can’t execute beyond its deadline. Also, only a single task will be executed at a time.
23. The N–queens puzzle is the problem of placing N chess queens on an N × N chessboard so that no two queens threaten each other. Thus, the solution requires that no two queens share the same row, column, or diagonal.
24. Given an integer array, find the subarray that has the maximum product of its elements. The solution should return the maximum product of elements among all possible subarrays.
25. The Longest Repeating Subsequence (LRS) problem is finding the longest subsequences of a string that occurs at least twice.
26. Given an unsorted integer array, find a triplet with a given sum in it.
27. The Shortest Common Supersequence (SCS) is finding the shortest supersequence Z of given sequences X and Y such that both X and Y are subsequences of Z.
28. Given an array containing positive and negative elements, find a subarray with alternating positive and negative elements, and in which the subarray is as long as possible.
29. 4-sum problem: Given an unsorted integer array, check if it contains four elements tuple (quadruplets) having a given sum.
30. In the k–partition problem, we need to partition an array of positive integers into k disjoint subsets that all have an equal sum, and they completely cover the set.
31. Given a set of positive integers S, partition set S into two subsets, S1 and S2, such that the difference between the sum of elements in S1 and S2 is minimized. The solution should return the minimum absolute difference between the sum of elements of two partitions.
32. Wildcard Pattern Matching: Given a string and a pattern containing wildcard characters, i.e., * and ?, where ? can match to any single character in the string and * can match to any number of characters including zero characters, design an efficient algorithm to check if the pattern matches with the complete string or not.
33. Consider an event where a log register is maintained containing the guest’s arrival and departure times. Given an array of arrival and departure times from entries in the log register, find the point when there were maximum guests present in the event.
34. Graph coloring (also called vertex coloring) is a way of coloring a graph’s vertices such that no two adjacent vertices share the same color. This post will discuss a greedy algorithm for graph coloring and minimize the total number of colors used.
35. The Longest Increasing Subsequence (LIS) problem is to find a subsequence of a given sequence in which the subsequence’s elements are in sorted order, lowest to highest, and in which the subsequence is as long as possible. This subsequence is not necessarily contiguous or unique.
36. There are two players, A and B, in Pots of gold game, and pots of gold arranged in a line, each containing some gold coins. The players can see how many coins are there in each gold pot, and each player gets alternating turns in which the player can pick a pot from either end of the line. The winner is the player who has a higher number of coins at the end. The objective is to “maximize” the number of coins collected by A, assuming B also plays “optimally”, and A starts the game.
37. Activity Selection Problem: Given a set of activities, along with the starting and finishing time of each activity, find the maximum number of activities performed by a single person assuming that a person can only work on a single activity at a time.
38. The longest alternating subsequence is a problem of finding a subsequence of a given sequence in which the elements are in alternating order and in which the sequence is as long as possible. In order words, we need to find the length of the longest subsequence with alternate low and high elements.
39. Given an integer array, find the length of the longest subsequence formed by the consecutive integers. The subsequence should contain all distinct values, and the character set should be consecutive, irrespective of its order.
40. Trapping rainwater problem: Find the maximum amount of water that can be trapped within a given set of bars where each bar’s width is 1 unit.
41. Given a list of jobs where each job has a start and finish time, and has profit associated with it, find a maximum profit subset of non-overlapping jobs.
42. The Longest Bitonic Subarray (LBS) problem is to find a subarray of a given sequence in which the subarray’s elements are first sorted in increasing order, then in decreasing order, and the subarray is as long as possible. Strictly ascending or descending subarrays are also accepted.
43. Suppose we are given n red and n blue water jugs, all of different shapes and sizes. All red jugs hold different amounts of water, as do the blue ones. Moreover, there is a blue jug for every red jug that holds the same amount of water and vice versa. The task is to efficiently group the jugs into pairs of red and blue jugs that hold the same amount of water. (Problem Source: CLRS)
44. Given a positive number n, find the total number of ways in which n hats can be returned to n people such that no hat makes it back to its owner.
45. Given a set of intervals, print all non-overlapping intervals after merging the overlapping intervals.
46. Write an efficient algorithm to find the longest common prefix (LCP) between a given set of strings.
47. Given a rod of length n, find the optimal way to cut the rod into smaller rods to maximize the product of each of the smaller rod’s price. Assume that each rod of length i has price i.
48. Given a set of rectangular 3D boxes (cuboids), create a stack of boxes as tall as possible and return the maximum height of the stacked boxes.
49. Given an integer array, find the maximum product of its elements among all its subsets.
50. Given a binary tree, find the size of the Maximum Independent Set (MIS) in it.
Additional Topics Available for Students Interested in Projects with a Higher Level of Difficulty
1. Applications of number theory and cryptography: Learn and implement in Python the RSA algorithm.
2. Applications in bioinformatics: Learn and implement in Python the algorithm used to reconstruct genomes.
Computational Neuroscience
The human brain, perhaps the most complex, sophisticated, and complicated learning system, controls virtually every aspect of our behavior. Neuroscience is the study of the brain, and computational neuroscience divides this study into three subspecialties: neural coding, biophysics of neurons, and neural networks. The course is primarily aimed at high school students that are interested in learning how the brain processes information. The course will start with a basic introduction to the structure and function of the central nervous system, and then include a study of the neurophysiology of the neuron, electrophysiological approaches to record from neurons, as well as mathematical and/or computer-based models that help explain existing biological data. The course will provide a simple introduction to basic computational methods of the brain from the cellular level and the network level with the aim of explaining what nervous systems do and how they function. Basic techniques of modeling biophysics, excitable membranes, small network and large-scale network systems will be introduced. The range of topics include simulations of electrical properties of membrane channels, single cells, neuronal networks, learning and memory models, and models of synaptic transmission, thereby providing a theoretical framework that encapsulates our emerging understanding of the sensory, motor, and cognitive functions of the brain. A main goal of this course also is to provide students with a broad overview of the many practical applications in the field of computational neuroscience and review neuroengineering methods and technologies that enable the study of and therapeutic solutions for diseases of the brain or damage to the CNS, particularly for research or clinical application in the neurosciences.
Pre-approved Topic List
1. How can the basic cellular and network-level organization of neurons in selected systems be defined?
2. How do the properties of cells that make up the nervous system, including the propagation of electrical signals used for cellular communication, relate to their function in organized neural circuits and systems?
3. How are biophysical models of neural systems that emulate electrical behavior of neurons constructed?
4. How can mathematical analyses of data recorded during neurophysiology experiments be performed to describe the principles of neural information coding in sensory and motor systems?
5. What hypotheses can be formulated by captured mathematical models, as possible explanations for observed relationships between experimental outcomes and manipulations?
6. What are the principles of electrophysiological techniques and imaging technologies?
7. What are the applications of neural engineering in sensory, motor, neurological and mental disorders?
8. What are the principles, methodologies and applications of the main engineering techniques used to study and interact with neural systems?
9. How can intracellular recordings be carried into the lab efficiently with all its components — from handing the animal to preparing solutions, slicing the brain and patching onto cells?
Machine Learning and Data Science
【 Guillermo Goldsztein 】
The availability of computer power and massive data has led to the incredible growth of data science as a discipline. Data science is now being applied to numerous fields. As a consequence, the demand for data scientists is very high. Leading universities have created new Data Science degrees at both the undergraduate and graduate level, and becoming a data scientist is considered the best career (or the career of the future) by many. In this course, students will learn machine learning techniques (the core of data science), the mathematics behind those techniques, and the computer language Python, to implement those techniques on real data. As a course project, the student will have the option of analyze a real data set or exploring mathematical aspects of machine learning. The topics of the possible course projects are listed below.
Pre-approved Topic List
Applications:
1. Email Spam: Design an automatic spam detector that filters out spam to avoid clogging a user's inbox, without diverting desirable emails.
2. Prostate Cancer: Predict the chances a patient has or will contract prostate cancer by utilizing clinical data.
3. Handwritten Digit Recognition: Develop a computer program that automatically reads handwritten ZIP codes.
4. DNA Expression Microarrays: Detect reads in DNA that are prevalent in certain cancers to enable a better understanding of cancer risks based on a patient's DNA.
5. South African Heart Disease: Understand risk factors that lead to heart disease.
6. Speech recognition: Develop a computer program that automatically detects different sounds and/or speech.
7. Image recognition: Develop a computer program that recognizes subjects in an image.
8. Dynamics of a galaxy: Use data from the motion of stars within the galaxy to understand its dynamics.
9. Applications in sports: Analyze sports data that is of interest to the student.
10. Income from demographics: Understand how different demographic factors are related to the income of an individual.
Mathematics and methods:
For the project, the student will have the option to learn and explore topics we did not have time to learn during the lectures. Some of these topics are likely to be:
1. Some advanced aspects of Neural Networks. (We will cover Neural Networks in the course, but this is an expansive topic, so students will do a significant amount of independent work if they select this topic)
2. Unsupervised learning
3. Reinforcement Learning
4. Advanced optimization techniques
5. Advanced linear algebra
6. Advanced Statistics
Horizon Labs
One on One Mentorship. Specialized Research Topics. Flexible Timing.
Applications of Machine Learning
【 Parsa A. 】| 【 Patrick Emedom-Nnamdi 】|【 Perman J.】|【 Rida Assaf 】|【 Derek S.】【 Alex T.】|【 Emma R. 】|【 Angelina W. 】|【 Daniel K. 】|【 Jordan A.】|【 Xiaoqi C.】|【 Matthew G.】|【 Lasya Sreepada 】|【 Gerry Chen 】|【 Jan C.Z. 】|【 Jack Kolb 】|【 Joe Xiao 】
Machine learning and predictive analytics can be used in a stunning number of ways. From predicting the price of a stock you buy, to estimating the chances that your flight will be delayed, to estimating how well your favorite sports team might do next game, to even guessing the outcomes of a Supreme Court case, machine learning can help us predict the world around us. This course examines interesting and unlikely applications of machine learning that advance social goals, improve economic efficiency, or better understand the world around us.
Pre-approved Topic List
Topics in Image Recognition
Topics in Medical Applications of Machine Learning
The Philosophy of the Mind
【 Alasdair Craig 】
What is a mind and what is consciousness? Are artificial intelligences genuine minds? Could trees be conscious? What are the implications of artificial intelligence for creativity and morality? How can we scientifically study the mind? These are some of the questions you can explore in this course, which uses philosophy and cognitive science to investigate the nature of the mind, consciousness and cognition. Course materials include classical and contemporary writing by philosophers and cognitive scientists, as well as videos and podcasts of philosophers and cognitive scientists debating the issues. Students will also cultivate study skills and learn how to write and debate with clarity and rigor. Depending on their interests, students can focus on interpreting scientific experiments or focus more on philosophical issues to do with the mind and consciousness. The course is adapted from courses that Dr. Craig has taught undergraduates at the University of Oxford.
Pre-approved Topic List
1. Are conscious minds physical, material things, or are they non-physical? For example, is the human brain a mind, or must minds be something else, over and above the brain?
2. Could artificial intelligences be conscious? Could they have emotions?
3. What is pain? Is it a state of the brain? Could a robot feel pain?
4. What do perceptual illusions and hallucinations reveal about the nature of consciousness and perception? Do we ever ‘directly’ see the world as it really is?
5. Can science explain consciousness, or will consciousness always be mysterious to science?
6. Can the conscious experiences that we have when we see, hear and smell be influenced by our prior beliefs, expectations and desires?
7. In the future, will we read novels and listen to music written by artificial intelligences?
8. Could artificial intelligence bring about the end of the human species?
9. What are delusions? To understand what is going on when people suffer from delusions, must we postulate abnormalities in how beliefs are formed and maintained, or does it suffice to appeal to abnormalities in perception or experience?
10. What is the structure of the mind? How does it process information?
11. Is the human mind best understood as a kind of computer?
12. What exactly is consciousness?
13. Could panpsychism – the view that all matter is conscious – actually be true?
14. Do we have free will?
Political Theory and Philosophy
【 César Cabezas Gamarra 】|【 Sonny K. 】|【 Johan T. 】
What justifies the authority of the state? What are the basic liberties that a just society should secure? How should societies reckon with implicit bias, historical injustices, and structures of racism, classism, and sexism? Can meritocracy exist alongside entrenched privilege? We examine these questions and more in Mr. Cabezas's course, based on his section of the Contemporary Civilization (CC) course at Columbia University.
Pre-approved Topic List
1. What justifies the authority of the state? What are the problems associated with social life in the absence of government (i.e. a state of nature)? How does the "social contract" proposed by the likes of Hobbes, Locke, and Rousseau work as a solution to these problems?
2. What are the supreme principles (if any) that should guide our moral conduct? Do they admit of exceptions?
3. What is implicit bias? Should we blame agents for having implicit biases even if they are outside their control?
4. Can we explain the various aspects of social reality purely in terms of individual beliefs, actions and intentions? Or does an adequate explanation of social reality require reference to social phenomena such as organizations, social structures and social laws?
5. Is morality merely a matter of personal (or group) opinion? Or are there objective moral facts that transcend cultures and historical eras?
6. What are the basic liberties that a just society should secure? Is being free not having others interfere with one's personal affairs? Or is it to have the capacity to make one's own laws by participating in the collective process of government? Or is freedom a matter of not being subject to the arbitrary power of the state and/or other subjects?
7. What is the role of privileges or unearned advantages in sustaining systems of oppression?
8. What are our moral duties regarding injustices in which we participate indirectly (e.g. buying clothes produced in sweatshops)?
9. Are we morally responsible for the moral failures of our ancestors (e.g. colonization, slavery, the Holocaust)? What about the present-day consequences of their moral failures?
10. What are some convincing argument for the right to reparations for African-Americans?
11. Why are epistemic virtues such as humility, open-mindedness, and curiosity important for our life in community?
12. What is the importance of public deliberation and disagreement for a democratic society?
13. Can people be willfully ignorant? If so, how does willful ignorance contribute to the maintenance of social injustice?
14. Given that science has ruled out the existence of biological races, should we give up the concept of race? Or is there a plausible non-biological concept of race that can contribute to a better understanding of racial relations?
15. What is the difference between race, ethnicity and nationality?
16. Is racism a matter of individual beliefs, intentions and actions, or can racism also take place at the level of institutions and social structures?
17. What is intersectionality? How does it contribute to a better understanding of gender, race and class?
18. What is work? What is meaningful work? How might we make work more meaningful?
19. Is work an oppressive institution? Can we make work (more) free? How?
20. What is a Universal Basic Income? What are the best arguments in favor of UBI and what are the strongest objections?
21. What is care-work? How does the distribution of responsibility for care
22. Is work becoming more "precarious”? How do we weigh the benefits of flexible work up against the perils of precarity?
23. What is civil disobedience? When, if ever, is civil disobedience justified?
24. How should the climate justice movement think about the use of civil disobedience? Might there be arguments for going even further? What about uncivil disobedience?
25. On revolution, with a focus on Hannah Arendt: Why did Arendt favor the American over the French revolution? What does it tell us about her conception of modern politics?
26. What is an oligarchy? Is the US an oligarchy? What can be done to make an oligarchy more democratic?
Gene Editing and CRISPR Technology
【 Erika DeBenedictis 】|【 Zeynep Ozturk 】|【 Erin Berlew 】|【 Nadia Nasreddin】|【 Merrick S. 】|【 Soufiane Aboulhouda 】|【 Ana Queiroz】|【 Everardo Hegewisch Solloa 】|【 Niki G. 】|【 Grace H. 】|【 Christa C. 】|【 William 】|【 Eoghan 】|【Paul Gehret】|【 Corrado Mazzaglia 】
How did life begin? What is the basis for human life and how are scientists learning to manipulate our genetic code? How can CRISPR allow users to control genetic expressions and human development? What is CRISPR, how was it discovered, and how can it rapidly change our ability to understand and manipulate biology? how are CRISPR systems being applied to both detect and treat human disease? How do we find new CRISPR systems with ever expanding functionality? We examine these questions and more in this course, based on the sections of the Biological Engineering course at the Massachusetts Institute of Technology that our instructors teach.
Pre-approved Topic List
Please note that topics offered by Ms. Erika DeBenedictis are marked as "E". Those offered by Ms. Zeynep Ozturk are marked as "Z". Those offered by Ms. Erin Berlew are marked as "B". Those offered by Ms. Nadia Nadreddin are marked as "N". Those offered by Mr. Merrick S. are marked as "M". Those offered by Mr. Soufiane Aboulhouda are marked as "S". Those offered by Ms. Ana Queiroz are marked as "Q". Those offered by Mr. Everardo Hegewisch Solloa are marked as "H". Those offered by Ms. Niki G. are marked as "G". Those offered by Grace H. are marked as "R". Those offered by Ms. Christa C. are marked as "C". Those offered by Mr. William are marked as "W". Those offered by Mr. Eoghan are marked as "A". Those offered by Mr. Paul Gehret are marked as "P". Those offered by Mr. Corrado Mazzaglia are marked as "O".
1. How do CRISPR systems work on the molecular level? What was their original purpose? How did they evolve? [E, Z, B, N, M, S, Q, H, G, R, C, A, O]
2. Why are CRISPR systems useful for modern genome engineering? How do they compare to other techniques such as zinc fingers? [E, Z, B, N, M, S, Q, H, G, R, C, A, O]
3. CRISPR-based techniques rely on protein such as Cas12 or Cas9. Are some of the properties of these proteins undesirable? How might we engineer these proteins to work better? [E, Z, B, N, M, S, H, G, R, O]
4. On a molecular level, what components in living organisms are used to implement the specific genetic code that exists? How can we modify these components to create new genetic codes? What benefits would different genetic codes have for engineering purposes? [E, B, M, S, H, G, C, O]
5. What are recent developments in the field of CRISPR, such as CRISPR-guided base editors and prime editing? [E, Z, B, N, M, S, H, G, R, C, O]
6. How can CRISPR systems be used to modify the genomes of entire wild populations using ‘gene drive’ constructs? What are possible applications of gene drives? What are the technical challenges to implementing gene drives safely? What are the ethical implications of using gene drives? [E, Z, B, M, H, R, C, W, O]
7. Large-scale engineering projects require project management strategies. In biological engineering, what are good strategies for assessing the quality and feasibility of an idea? How should one go about rapidly de-risking and implementing a new engineering approach? [E, B, G, C, O]
8. When our engineering goals require biomolecules with functions not found in nature, we can attempt to create these new components with rational or computational design approaches, with directed evolution, or both. How do these protein engineering techniques work? How do we assess which approach is likely to be successful in a particular situation? [E, B, M, O]
9. How did life originate? How did the divide between genetic material (DNA) and functional biomolecules (proteins) come to exist? How did the genetic code come to exist? [E, Z, B, M, Q, H, R, C, O]
10. Why is the universally conserved genetic code structured the way it is? In particular, why does it use three-base codons, why are the codons assigned to specific amino acids, why do some amino acids have more codons, and why were the specific 20 amino acids chosen? [E, Z, B, M, Q, H, G, R, C, O]
11. What can directed evolution experiments teach us about how evolution works? Conversely, can evolution research of organisms in the wild guide best practices for directed evolution experiments in the laboratory? [E, B, H, C, O]
12. If we want to add a new amino acid to the genetic code, or rearrange which codon encodes which amino acid, what engineering approaches are available to us? What are the strengths and weaknesses of these different approaches? [E, B, M, H, C, O]
13. What inspiration can we take from computer science that may help us engineer biological systems? Do concepts like logic gates and abstraction exist in biology, and if not, how do we implement them? [E, M, C, O]
14. Proteins are chemically complex, enabling proteins to perform diverse chemical functions in the cell, but be difficult to engineer and model. In contrast, DNA less chemically complex. How can we exploit the simplicity of DNA’s chemical structure to predict the shape that a strand of DNA will adopt? How do we use this predictive capability to engineer custom DNA shapes (like smiley faces), or processes (like an AND logic gate)? What are the limits of DNA nanotechnology? [E, B, O]
15. CRISPR enzymes can have off-target effects that may have unintended side effects of a therapy. What are strategies that are used to identify these off-target effects. How are these off-targets avoided and how are CRISPR enzymes engineered to alleviate this problem? [E, Z, B, N, M, S, H, C, O]
16. Some CRISPR systems don’t act on DNA but, instead, on RNA. What function do these proteins have and how are these interesting proteins being harnessed for treating human disease? [E, B, N, S, G, H, R, C, O]
17. How can CRISPR systems be used to treat human disease outside of gene editing? How are CRISPR proteins being used to change the expression of genes and why would one want to do this? [E, B, Z, N, M, S, H, G, R, C, O]
18. If you wanted to insert an entirely new gene into the genome, how would you achieve this? What current technologies are used for gene insertion, what are their limitations, and what new technologies on the horizon can transform this problem? [Z, B, N, M, S, H, G, R, C, O]
19. How are CRISPR enzymes being used to treat humans today? What kinds of diseases are being treated, why were they chosen, and how are CRISPR enzymes critical to the success of the treatment? What are the limitations of CRISPR in the clinic that have limited its ability to treat more diseases? [Z, B, N, M, S, H, G, R, C, O]
20. If you wanted to treat a genetic disease in a living human with CRISPR, how would you get the enzyme to the diseased tissue of interest? How and why are viruses commonly used to deliver CRISPR to cells? [Z, B, N, M, S, H, G, R, C, O]
21. How can CRISPR enzymes be used to diagnose disease? SHERLOCK and DETECTR are two platforms for detection of diseases and viruses. What are these tools, why are they increasingly gaining popularity as diagnostics, and how are these platforms being applied to detect viruses like COVID-19? [B, Q, C, W, O]
22. New CRISPR enzymes are found every day from nature using computational tools. What are these computational tools, how do they work, and what new enzymes have been found using these techniques? [B, C, O]
23. Next-generation sequencing is a transformative technology used by companies like 23andMe and Ancestry.com, by enabling rapid and inexpensive reading of DNA. How does next-generation sequencing work and how is it applied in research and in the clinic? [B, N, M, Q, H, G, R, C, O]
24. Is it ethically appropriate to modify genomes including humans? What are the risks and how can we foresee the potential outcomes? [E, Z, B, N, M, S, Q, H, R, C, O]
25. How can we use online genetic data in order to study genetic diseases and roles of genes in cell biology? [Z, B, N, M, H, G, R, C, O]
26. Why is DNA sequencing important for scientific research? How does next generation sequencing compare with the previous sequencing methods