Horizon Labs features flexible start dates. Students should apply at least one month prior to their preferred start date.

 

Horizon Seminar Term Dates

Spring 2021: March 1, 2021 - June 14, 2021

The Spring 2021 application deadline for Horizon Seminar classes has passed. Applications for Horizon Labs remain open.

 

Summer 2021: July 3, 2021 - September 11, 2021

Application Deadline: June 9, 2021

 

Fall 2021: October 23, 2021 - February 21, 2022

Application Deadline: September 30, 2021

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.

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)

Additional 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 research focus will shine light on the many techniques that scientists use to solve real-world problems. From analyzing blood samples, detecting pollutants in the atmosphere, assessing the safety of food and cosmetics, analytical chemistry is a key topic for aspiring scientists or entrepreneurs.

9. Spectroscopy: using light to identify and quantify chemical species

10. Microscopy techniques: far beyond the resolution of the eye

11. Diffraction and scattering: determining size and shape at the nanoscale

12. Separations techniques: the methods by which scientists purify and isolate single components from complex chemical mixtures

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 Ms. Irene Li are marked as "I". 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 Mr. Andreas G. are marked as "G".

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

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

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]

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, I, T, E, W, C]

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

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

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. Julian Day Cooney are marked as "J". Those offered by Mr. Andrew Stier are marked as "A". 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 Castro-Rivera 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".

1. A review of important neurobiology fundamentals. [P, J, R]

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, A, R, G]

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, J, A, R, N, E]

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, A]

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

What is a ‘mind’? How do our minds hook onto the world? This course uses philosophy and cognitive science to investigate the nature of mind and cognition, with a particular focus on perception and thought. Depending on their interests, students can focus on interpreting scientific experiments or focus on the more philosophical issues that thinking about the mind raises. This is an adapted version of a course that Mr. Craig has taught at Oxford University.

Pre-approved Topic List

1. Perceptual Experience 1: What do perceptual illusions and hallucinations reveal about the nature of perceptual experience? In particular, do these phenomena show that we never ‘directly’ see the world as it is?

2. Perceptual Experience 2: Can a person’s perceptual experiences be influenced by that person’s prior beliefs, expectations and desires? What is the best interpretation of experiments that purport to show that the answer to this question is ‘yes’?

3. Explanation in Cognitive Science: What should cognitive scientists look for in a satisfying explanation of human behaviour?

4. The Nature of Mind: Is the mind a purely physical or material thing? Are mental states physical states?

5. The ‘Language of Thought’ Hypothesis: What is the language of thought hypothesis, and is it possible to understand mental processes as computational processes without a language of thought?

6. The Nature of Consciousness: Describe Ned Block’s distinction between ‘phenomenal consciousness’ and ‘access consciousness’. Does scientific work show that phenomenal consciousness can exist in the absence of access consciousness?

7. 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?

8. Modularity: What is the modularity thesis? Assess the scientific case for the thesis that the mind is modular.

【 Micheal D. 】

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?

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?

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?

Please note that topics offered by Ms. Baek are marked with "B" next to them. Those offered by Mr. Erik N. are marked as "N". Those offered by Mr. Brian Earp are marked as "E". Those offered by Ms. Ellen R. are marked as "R". Those offered by Ms. Joanna Szypula 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".

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]

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

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]

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]

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? [also offered by Mr. Quirk]

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]

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]

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

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

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

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

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]

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

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

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

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]

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

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

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

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

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

7. Is worry adaptive? [N, M]

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]

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

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

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]

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]

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]

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

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]

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

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

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

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?

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

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? [M, A, I]

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

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

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]

5. Why are rates of emotional disorders often observed to be more common in developed nations compared to less developed nations?

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

7. Rates of violence across 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]

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]

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]

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

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, M, A, C, I]

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

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]

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]

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

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

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 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 Mr. Leo Vo are marked as "V". 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".

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

Please note that topics offered by Dr. Parsa A. are marked as "A". Those offered by Mr. Patrick Emedom-Nnamdi are marked as "N". Those offered by Perman J. are marked as "J". Those offered by Mr. Rida Assaf are marked as "R". Those offered by Ms. Irene Li are marked as "I". Those offered by Mr. Derek S. are marked as "D". 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 Mr. Daniel K. are marked as "K". Those offered by Mr. Jordan A. are marked as "O". Those offered by Mr. Xiaoqi C. are marked as "C". Those offered by Mr. Matthew G. are marked as "G". Those offered by Mr. Andreas G. are marked as "S".

1. Applications of deep learning and reinforcement learning to train an autonomous agent to solve video game dynamics. [A, N, R, T, E, O, C, G, S]