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.

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

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 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.

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 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

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?

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?

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".

Please note that topics offered by Ms. Sori Baek are marked with "B" next to them. Those offered by Mr. Brian E. are marked as "E". Those offered by Ms. Ellen R. are marked as "R". Those offered by Ms. Joanna S. are marked as "J". Those offered by Ms. Megha C. are marked as "M". Those offered by Ms. Ana Maria Pereira de Souza are marked as "A". Those offered by Mr. Andy S. are marked as "S". Those offered by Ms. Christa C. are marked as "C". Those offered by Jiyoung are marked as "I". Those offered by Ms. ChiChi M. are marked as "H". Those offered by Ms. Aliza are marked as "L". Those offered by Ms. Alex R. are marked as "X". Those offered by Ms. Jackie Katzman are marked as "K". Those offered by Mr. Alexander Jay are marked as "D". Those offered by Ms. Karly D. are marked as "Y". Those offered by Emily are marked as "Z".

Topics in Cognitive Psychology

1. How do people learn a new language? Is it different for adults and kids? [B, R, M]

2. What helps a memory stick? What helps us remember things better? [B, R, J, M, A, S, L, Y]

3. What makes memories become more accurate or inaccurate? What does this mean for eyewitness testimonies? [B, J, M, A, S, L, K, Y]

4. Why are we so good at seeing “faces” from objects, like an outlet or a smiley face [ :) ]? Does this have an evolutionary reason? [B, R, M, A, S]

5. Carrying a heavier backpack can make a hill look bigger. What are some other ways in which things change our perception? [B, R, S, Y]

6. What affects our attention, and what distracts us? How do we select what we pay attention to? [B, M, A, S]

7. How do other people affect how we think? How do opinions of others change our own opinions? [B, N, R, M, A, S, L, X, Y]

8. Why are we so captivated by surprising and unexpected things, like magic? Does this have an evolutionary reason? [B, S]

9. How do optical illusions work? How do they trick our brains? [B]

10. What happens in our brain when we make predictions that turn out to be wrong? How does this experience help us learn? [B, S, X, Y, Z]

11. We’re really good at hearing our name, even if it’s said by someone standing really far away in a loud room. Why does this happen? [B, R, M, A, S]

12. Are babies’ brains as good as adults’ brains? In what way? [B, R, H, Z]

13. What do babies do to learn? Are they good learners? [B, R, H, L, Z]

14. Can newborn babies tell their mothers apart from other people? In what way? [B, R, H, L, Y]

15. A lot of toys are marketed to be good for the brain. Is this true? Which toys? Why or why not? [B, H, Y]

16. What is our brain doing when we form memories and remember things from the past? [B, S, X, Y]

17. What is our brain doing when we see numbers and do math? [B]

18. What is our brain doing when we see alphabets and read a sentence? [B]

19. What is our brain doing when we’re not paying attention in class? [B, S]

20. How does the brain change when we learn a new skill and become better at it? [B, M, A, S, Y, Z]

21. What factors lead to differences in intelligence? Is IQ a good measure of how intelligent someone is? [R, M, A, C, L, Y]

22. What makes different education styles work better than others? What does it mean to be a certain type of learner? [L, Y]

23.What are the differences between short and long term memory? How do attention and memory interact? [J, M, A, L, Y]

24. What role does memory play in eating behaviors? Can we use memories to help us lose weight? [J]

25. What are the barriers to access to mental health services between different racial and ethnic groups? [H, L, Y]

26. Are there differences in how mental illness is perceived between different racial and ethnic groups? [H, L, Y]

27. Are there differences in perception of mental illness between men and women, and does this have long term consequences? [H, L, Y]

Topics in Clinical Psychology

Clinical psychology is concerned with identifying, understanding, and treating psychological disorders. This course will explore questions such as how we differentiate sadness from depression, why some people develop mental disorders while others don’t, what the best treatments for anxiety disorders are, and more. Students will have the option of focusing on specific mental disorders or studying basic psychological mechanisms that have clinical relevance.

1. Uncertainty is a core feature of our everyday lives, especially during current times. How do humans respond to uncertainty? How does it affect our cognition, emotions, and behavior? [N, M, A, L, Y]

2. How does the psychological trait of intolerance of uncertainty increase risk for anxiety disorders? [N, M, L, Y]

3. Does it make sense to think of mental disorders are discrete categories or as dimensions that we all vary on? [N, M, I, L, Y, Z]

4. How do cognitive factors like attention, memory, and interpretation contribute to depression? [N, M, L, Y]

5. What is the difference between fear and anxiety? [N, M, A, L, Y, Z]

6. How do we regulate our emotions? How does emotion regulation go awry in psychopathology? [N, M, A, I, L, Y, Z]

7. Is worry adaptive? [N, M, L, Y, Z]

8. Rumination refers to repetitive negative thought about the past, and worry refers to repetitive negative thought about the future. Are these two processes fundamentally the same or different? [N, M, A, L, X, Y]

9. Why are we not better at treating mental disorders? [N, M, L, X, Z]

10. Does it make more sense to call mental disorders (e.g., depression) a "brain disease"? Why or why not? [N, M, A, H, L, X, Y, Z]

11. What are the "active ingredients" in psychotherapies for emotional disorders? How do we know that these are really the mechanisms of change? [N, I, L, X, Y, Z]

12. What is depression, exactly? Is it one syndrome, or is it a collection of different syndromes that we've grouped under the same name? [N, M, I, H, L, X, Y, Z]

13. Are today's youth really more anxious and depressed than youth in the past? If so, what is contributing to this increase? [N, M, A, H, L, X, Y, Z]

14. What do we know—and what do we not know—about treatments for emotional disorders? [A, L, Y]

15. How do scientists study treatments for mental health problems? What are empirically supported treatments, why are they useful, and what are their limitations? [A, I, L, X, Z]

16. How can mental health treatments be delivered? What are the advantages and disadvantages of certain delivery formats? [A, I, L]

17. How can we increase access to mental health treatments? [I, L, Y]

18. Are apps and internet programs effective treatments for common mental health problems? [I, L, Y]

19. How have treatments been adapted for people in low- and middle-income countries? What strategies are used to ensure that treatments are effective and culturally appropriate? [H, Y]

20. What is the research-implementation gap? How long does it take for research evidence to reach clinical practice? [I, L, Y]

Topics in Pathology and Data Science

What causes mental illness? Mr. Jones's course explores competing theories on the origins of emotional disorders such as depression, social anxiety, and post-traumatic stress disorder. We examine how complexity approaches in statistics and machine learning, such as network analysis, can help us understand the problem. Depending on their interests, students can focus on a substantive area of mental health or delve deeper into the computational aspects.

1. The network theory of mental disorders states that mental disorders do not have a single underlying cause, but instead are the result of feedback loops in a complex system. How does this theory apply to depression? Anxiety? Trauma? Other psychological problems? [N, M, A, I]

2. Why do mental disorder co-occur at such high rates? How can network analysis inform the comorbidity between them? [N, M, A, I, L]

3. How can novel developments in data science (e.g., machine learning methods) contribute to the field of clinical psychology? [A, C, I, L, Z]

4. What can we learn from exploratory data analysis of mental disorder symptoms? What kinds of psychometric data analyses and visualizations are most helpful? [A, C, I, L]

5. Why are rates of emotional disorders often observed to be more common in developed nations compared to less developed nations? [L, Y, Z]

6. One hallmark of anxiety disorders is avoidance. What factors lead people to avoid versus approach their fears? [N, M, A, L, X, Y, Z]

7. Rates of violence across the world have been steadily decreasing. If this is indeed the case, why are rates of post-traumatic stress disorder (PTSD) stagnant or even increasing? [N, Y]

8. To what extent do mental disorders represent a "mismatch" between the modern world and our environment during evolution? What factors of modernity might influence mental illness? [E, M, A, Z]

9. Why do some individuals with PTSD seem to compulsively revisit their traumatic past? How does this square with research on avoidance? [N, M, A, L, Y]

10. Are trigger warnings or safe spaces effective approaches to helping those with PTSD? Why or why not? [N, M, A, L, Y]

11. Today, phones and devices capture a huge amount of data about individuals (e.g., location, movement, texts, phone calls, app usage). Can this data be used for good when it comes to mental health? How? [N, A, C, I, L, Z]

12. Can people really experience "post-traumatic growth" after a trauma? If so, what does this growth look like? [N, A, L, Y, Z]

13. What is idiographic science? How can we study one person at a time? [I]

14. Can we personalize psychotherapy interventions for each person? [A, I, L, X]

15. How can data science help us predict substance use for each person? [A, I]

16. Can a single survey item capture enough information, or do we always need multiple items? [I, Y]

17. How much can we generalize from group-level research? [I, Y]

18. How can we best capture fluctuations in people's emotions? What are affective dynamics? [I, L]

Topics in Psychology and Law:

1. For cases in which juvenile offenders are transferred to adult court, do jurors take their developmental vulnerabilities into account when they make decisions about them? [K]

2. Mistaken identification is the leading cause of wrongful conviction. What procedural best-practices can make eyewitness evidence more reliable? How can social psychological theory inform these practices? [K, D, Y]

3. Do the demograhics of the people selected as jury members affect their ultimate verdict decisions? [K, D]

4. What strategies can help jurors better understand complex evidence in the courtroom? [K, D]

5. Most all criminal cases are adjudicated thorugh plea negotiation. how can social psychological theory help attorneys better advise their clients? [K, D]

6. Racial disparities in the criminal justice system are well documented and widespread. How can we lessen racial bias in policing, prison populations, and participation on juries? [K, D, Y]

7. Why do people make false confessions? What aspects of police interrogations might increase the rate of false confession? [D, Y]

8. Why do innocent people plead guilty? What components of plea bargaining increase the odds an innocent person will plead guilty? [D]

9. How do the racial characteristics of a criminal case impact jurors' decision-making? [D, Y]

10. How do robust social cognitive processes, such as stereotyping, affect jurors' perceptions and decision-making in civil and criminal cases? [D, Y]

11. What is criminal profiling, and does it resemble the crime shows on t.v.? What does the science say about criminal profiling? How is it practiced by law enforcement agencies, and does it work? [D, Y]

12. Jurors are often presented with a lot of complex information presented in a disorganized fashion. How do jurors make sense of the evidence, and render their decisions? [D]

13. How do jurors' emotions impact their decision-making? [D]

14. How does pre-trial publicity impact jurors decision-making? [D]

15. What is 'juror rehabilitation'? Can it successfully reduce jurors' biases? [D]

16. Jurors are constitutionally required to be impartial at the outset of a trial, but are they? How effective are legal system safe-guards (e.g., voir dire and jury selection) at removing biases? What about implicit biases? [D]

Never before has there been so much collaboration between health researchers and computer scientists. This course examines applications of machine learning and predictive analytics in key areas of biology and health sciences. In this course, we first begin by reviewing key concepts in data analysis and machine learning and examine innovations in biotechnology enabled by machine learning. From there, we work with students in conducting original and novel analysis on large and complex data sets relating to a topic in health sciences such as cardiovascular disease, cancer diagnosis, epidemiological modelling, or drug discovery.

Pre-approved Topic List

Data Analysis and Statistics Based

Please note that topics offered by Dr. Parsa A. are marked as "A". Those offered by Mr. Perman J. are marked as "J". Those offered by Mr. Patrick Emedom-Nnamdi are marked as "N". Those offered by Mr. Rida Assaf are marked as "R". Those offered by Mr. Alex T. are marked as "T". Those offered by Ms. Emma R. are marked as "E". Those offered by Ms. Angelina W. are marked as "W". Those offered by Ms. Christa C. are marked as "C". Those offered by Mr. Daniel K. are marked as "K". Those offered by Ms. Lasya Sreepada are marked as "L".

1. Utilizing predictive machine learning models to learn more about cardiovascular diseases such as stroke and heart disease. [A, R, T, E, W, C, K, G, L]

2. Utilizing predictive machine learning models to learn more about cancer prognosis and diagnosis. [A, J, N, R, E, W, C, K, G, L]

3. Applications of machine learning in modeling the spread of infectious diseases such as COVID-19 and Ebola. [A, J, N, R, E, C, K, L]

4. Applications of machine learning training a 'convolutional neural network' to predict skin lesions which are either benign or indicative of skin cancer. [A, R, T, E, W, C, L]

5. Applications of Natural Language Processing in the health sector [R, C]

Literature Review Based:

6. Is the drug industry going bust? A review of the scientific literature and economic data. [A, T, E, K]

7. A review of supervised and unsupervised Machine Learning models. [A, J, N, R, T, E, W, C, K, G, L]

8. A review on computer-aided drug design and discovery [A, J, N, R, T, E, C, K, L]

Our neuroscience courses examine a variety of different aspects of the brain and the nervous system. Despite the incredible complexity of human behavior, we are able to take a deconstructive analysis to break down and better understand the various facets of behavior. Some of our instructors focus on integrative neuroscience, combining insights from psychology, data science, and philosophy together with traditional neuroscience, to better understand and reckon with deep questions about the nature of consciousness, perception, and memory. Some of our instructors focus specifically on neurodegenerative diseases and techniques that can be used to better understand and cure diseases like Alzheimer's and Parkinson's.

Pre-approved Topic List

Please note that topics offered by Mr. Patrick Liu are marked as "P". Those offered by Mr. Andy S. are marked as "S". Those offered by Ms. Marta Madureira are marked as "M". Those offered by Ms. Carolina C.R. are marked as "R". Those offered by Ms. Grace H. are marked as "G". Those offered by Ms. Natalya S. are marked as "N". Those offered by Ms. Ellen R. are marked "E". Those offered by Ms. Zeynep Ozturk are marked "Z". Those offered by Mr. Paras Minhas are marked "I". Those offered by Ms. Christa C. are marked "C". Those offered by Mr. Shivang are marked "H". Those offered by Ms. ChiChi M.are marked "CH". Those offered by Mr. Kenneth K. are marked "K". Those offered by Ms. Paula Martorell are marked "U". Those offered by Ms. Alex R. are marked "X". Those offered by Mr. Eshaan R. B. are marked "A". Those offered by Ms. Rui He are marked "RH". Those offered by Mr. Benjamin H. are marked "B". Those offered by Mr. Mason are marked "O". Those offered by Ms. Emily are marked "EM".

1. A review of important neurobiology fundamentals. [P, S, M, R, I, H, CH, K, A, RH, B, O]

2. How do genes and environment interact to shape who we are? How we determine their effects? Is one more important than the other? Where did our personality come from? [P, S, M, R, G, I, C]

3. How can we study the brain? How do we know which brain regions are responsible for certain behaviors? What are the limitations to studying the brain? [P, S, M, R, N, E, I, H, X, A, RH, B, EM]

4. How have evolutionary timescales and pressures carved human behavior? How can understanding the cellular basis of neural circuits explain our movements and the behaviors we make? Is human behavior entirely unique? What can we learn from the behavior of other animals in the evolutionary tree? [P, S, H]

5. How did consciousness evolve? How do consciousness and intellect connect? Is there a limit to human consciousness? [P, S, G]

6. How does the brain process and store information? How does emotion affect the brain’s judgment? More broadly, how do cognition, emotion, and memory mutually influence each other? [P, S, E]

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When Formulation Chemistry Meets Scientific Challenges

Have you ever been curious about the chemistry in the products you use everyday? 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 printed on your favorite drink or snack? How can you control the release of new therapeutic drugs in human bodies? If so, this program on formulation chemistry is made for you. In this class, we answer these questions and more. We first examine the main concepts on formulation chemistry (emulsion preparation, system stability, encapsulation techniques, characterization methods) before studying concrete applications in food, paints & coatings, cosmetics or pharmaceutical industries. The research project will then consist of an extensive literature review on a specific scientific challenge at the intersection of Formulation Chemistry and Material Science. The course taps into our instructors' research on chemistry at the University of Cambridge and at leading pharma companies like Sanofi.

Pre-Approved Applications and Topics

1. Food industry (e.g. Preparation of fat-free products with preserved textural properties)

2. Cosmetics (e.g. Preparation of shampoos with sustained release of active principles)

3. Plastics (e.g. Comparison of Plant-based vs oil-based materials)

4. Paints & Coatings (e.g. Preparation of non-toxic paintings with enhanced drying and resistance properties)

5. Pharmaceutical industry (e.g. Targeted drug delivery systems for controlled release of therapeutic compounds)

6. Agriculture (e.g. Controlled release of herbicides on crops)

7. Environmental applications (e.g. Composite materials for water pollutant removal)

8. Buildings and roads (e.g. Development of self-healing concrete)

9. Engine oil formulations (e.g. extending engine lifetimes and reducing CO₂ emissions)

10. Nanoparticles (e.g. imbuing formulations with countless properties, ie. conductivity, magnetism, catalysis and more)

Topics in Analytical Chemistry

The ways by which scientists elucidate the world around us rely on a complex but fascinating array of instrumental techniques and methodologies. Analytical chemistry stands at the cutting edge of scientific discovery, and this course will shine light (literally) on the many techniques that scientists use to solve and understand real-world problems. If you’re interested in the ways by which blood samples are analyzed, pollutants in the atmosphere are detected or how food and cosmetics pass the strict measures for quality control, then analytical chemistry is a key topic in your development as a scientist or entrepreneur. In your one-on-one lessons, you will be guided through the foundational theory that underpins the core techniques of analytical chemistry, and learn how to interpret actual data generated from real chemical systems. You will then apply these knowledge and skills as you explore a unique, scientific problem of your choosing, and produce a comprehensive literature review on the topic.

1. Atomic and molecular spectroscopy involves using light (of varying properties) to identify and quantify chemical species. Therefore, spectroscopy can be implemented for an enormous host of applications such as impurity or contaminant detection in food and pharmaceuticals, measuring amounts of toxins and pollutants in the environment and atmosphere, analyzing the properties of objects in astronomy, or increasing agricultural production.

2. Microscopy techniques are exploited when important phenomena are occurring far beyond the resolution of our eyes. From analyzing blood and tissue samples, to crime scene evidence, and then as far down as nanomaterials and single atoms, we gain insight into a myriad of systems through the art and ingenuity of microscopy.

3. Diffraction and scattering techniques allow us to use various forms of radiation such as light X-rays and neutrons to determine the size, shape and properties of particles and materials. If you want to characterize nanoparticles, elucidate crystal structures with sub-nanometer resolution or analyze protein deformation over time, scattering and diffraction techniques may hold the key.

4. Separations techniques allow scientists to purify and isolate single components from complex chemical mixtures. This may be for the purification of a new drug, to separate minerals from ore deposits or to remove pollutants from industrial effluent. Therefore, optimizing and innovating separations techniques is vital for economic and ecological benefits.

Topics in Physical Chemistry

Physical chemistry addresses the fundamental basis for the countless physicochemical phenomena exhibited by chemical systems. The mechanisms that underpin cloud formation, why water beads up on your living room window and how oil and water can be made to mix using emulsifiers, can all be explained within the grounds of physical chemistry. These lessons will rationalize the physical basis for these processes by describing and understanding the many interactions that take place between chemical species. Throughout the lessons, different chemical systems from particle dispersions to foamy fluids will be considered to aid in conceptualizing the complex interplay of forces involved in stabilizing these systems. This course is recommended for students that would like a challenge and are interested in consolidating their understanding of chemical systems with the relevant mathematical background. The mentor will also aid the student in conducting an extensive literature review on a related topic that the student desires to investigate.

1. Chemical thermodynamics concerns the transfer of energy between chemical species and justifies when a reaction (or interaction) is favored to occur.

2. Chemical kinetics concerns the timeframes of physicochemical phenomena and reactions.

3. Interfaces are represented as the surface or boundary between two distinct phase regimes (ie. solid and liquid, oil and water, water and air). How does chemistry change at interfaces and how do these processes influence the world we experience?

4. Chemical interactions dictate the overall behavior and reactivity of chemical systems. Understanding these complex interparticle forces is key in controlling system stability.

5. Surfactants or ‘detergents’ are a widely used class of molecules that are commonly found in cosmetic and cleaning formulations. Why are these molecules so good at their job? What chemistry underpins the way they behave in solutions and at interfaces?

6. Emulsions are formed when you achieve mixing of two liquids that would not normally mix (what?). Common examples include milk, mayonnaise and ice cream, and their formation and stability is owed to a unique array of interactions and processes.

7. Foams and aerosols are the gas/liquid opposites of each other, and both find countless uses and manifestations in industry and nature. How is it that gas molecules can be trapped in a liquid and how is it that aerosol droplets can appear out of thin air?

8. Liquid crystals are molecular assemblies that have the ordered structure of a crystal, but also the fluid/deformable properties of a liquid. Why and how do these unique structures emerge? What can they be used for?

Proteins are all over most introductions to biology and with good reason. Proteins are a, if not the, major result of the genetic code. Much of modern chemistry looks to proteins throughout biology as the “master chemists” to better understand the millions of chemical reactions they direct inside the bodies of all organisms, from humans to bacteria. But what are proteins and what do they really look like? 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. Biophysics is the application of physics to understand biology, and we aim to focus on its study of proteins for simplicity. We will begin by focusing on what proteins are, basic types of chemistry they perform, and the physical principles they use to control chemistry. From there we will review a few of the most common tools in biophysics and will introduce students to a variety of current topics of the field. We will focus on the topic our students are most interested in, the focus of their research project. The following (as well as those listed above) are examples. NOTE: AP Chemistry (or the equivalent since as IB HL Chemistry) is a prerequisite for this course. If your school does not offer AP or IB Chemistry, you will need to demonstrate extensive knowledge of chemistry through some other avenue to verify that you are familiar with the concepts covered in the AP Chemistry curriculum.

Pre-Approved Topics

1. Is it possible to build better enzymes than those found in biology?

2. What role do proteins play in the pharmaceutical industry?

3. How are current computational efforts used to understand proteins and with them, chemistry as a whole?

4. We produce many new industrial biological catalysts and drugs primarily by relying on methods which work but are random in nature and poorly understood. Could we ever understand these processes ourselves? What governs protein evolution? How does nature evolve on the molecular level?

5. All proteins are made of essentially the same 20 building blocks, but could that change and were these 20 building blocks just a coincidence?

6. What might we consider if we are interested in creating new proteins from a novel DNA sequence?

7. How does biology produce light? How much can it control the color of the different organisms throughout biology?

8. Why are plants green and other algae brown? Is there any reason for the colors we see all around us?

9. Green fluorescent protein and other fluorescent proteins are used ubiquitously throughout biology, but why do they exist in the first place?

10. What controls the muscles in your arm? Why does your bicep bulge when you flex and what do proteins have to do with that?

11. What can we see on the nanoscopic level (and smaller)? How fast do proteins and chemicals in general move?

12. Many proteins are masters at producing electric fields to control chemistry, but how do they do so? Can we measure fields at such a tiny scale?

Ancient Greek and Roman polities and empires stretch thousands of years into the past, but they continue to affect and inform ideas and events in the modern world. The languages, beliefs, and societies of these Mediterranean civilizations have left a deep footprint on modern philosophy, political science, sociology, architecture, aesthetics, linguistics, and the scientific method. And yet many beliefs held among members of these polities about love, social organization, identity, gender, and spirituality would sound quite alien to a modern observer. 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.

Pre-approved Topic List

1. How was slavery classified in the Greco-Roman world? What alternative forms of bondage existed alongside it?

2. What were the conditions of the slave systems during this time? How might we imagine the lives of those under bondage?

3. To what extent were slave able to express their autonomy?

4. How was love expressed among people in the Greco-Roman world? Are there any compelling cases in other eras that merit further comparisons?

5. What components were used to help develop a shared ethnic identity? Against whom was this ethnic identity juxtaposed?

6. What were some of the accepted gender roles in the Greco-Roman world? In what ways did people push against or defend these societal norms?

7. In what ways did religion influence the decisions and lives of the people of the Greco-Roman world?

8. How was the Greco-Roman family and household organized? What roles were available to the various members?

9. What was the culture of militaristic nations, such as Sparta and Rome, like? How did warfare shape their lives on and off the battlefield?

10. What were the opportunities available to women in the Greco-Roman world? How might we imagine their lives and treatment?

11. How can one utilize ancient literary sources as a means to better understand the history of the Greco-Roman world?

12. What messages can we gather from the mythology of this era to better understand the religious and personal beliefs of the Greco-Roman world?

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. What makes fluids so fascinating is you can sit and watch these natural phenomena for hours without ever seeing 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. Even without knowing the exact solution, insight to fluid motion has implications for world issues including predicting climate change, curing cancer, generating renewable energy sources, and producing clean water.

Candidates should have completed one year of Calculus and one year of Physics coursework. Students who do not meet these requirements will still be considered, but they are encouraged to list a secondary course preference since their likelihood of admission is significantly lower. No programming experience is necessary.

Pre-approved Topic List

1. Oceanic or atmospheric waves (e.g. Impact of underwater boundaries on wave propagation in the ocean)

2. Aerodynamic shape optimization (e.g. Reducing vehicle drag through geometry)

3. Animal locomotion (e.g. Mechanisms animals have evolved to efficiently propel themselves through various fluids)
 

4. Reusable energy (e.g. Production of energy through wind turbines)
 

5. Vortices (e.g. Formation and propagation of vortices throughout the ocean or atmosphere)
 

6. Stratification (e.g. Interaction between layers of flow with different properties)
 

7. Environmental flows (e.g. Weather patterns and prediction; Flow in porous media: e.g. managing drinking water supply, CO2 storage, contaminant transport)

8. Sports (e.g. water sports: rowing, kayak, canoe, as well as cycling: road and track)

9. Solidification of fluids (e.g. freezing pipes, melting ice cream, casting of metals)

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 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? How can an organizational leader change the culture of a company, and how else can organizational culture change? What makes a successful leader in an organization? What is the role of personality in receiving, maintaining, and excelling at a job? What predicts different levels of worker motivation and productivity? How do individual-level perceptions, attitudes, biases, and stereotypes shape an organization? What is at stake with contemporary discourse on diversity and inclusion? We will grapple with these questions, and you will develop an understanding of the antecedents and consequences of organizational behavior.

Pre-approved Topic List