teaching

“Docendo discimus…By teaching, we learn.” - Seneca

Teaching is one of my greatest joys :-) Below are courses that I’ve developed and taught over the years, with relevant course materials and teaching evaluations. (Click the arrow on the left to see the course description.)

UCSD

COGS 180: Decision Making in the Brain · course website · syllabus · SET evals · course survey

This interdisciplinary course aims to unravel the complexities behind human decision making by integrating insights from psychology, economics, neuroscience, psychiatry, design, and machine learning. We will explore everything from the cognitive biases and heuristics that shape our everyday decisions, to how decision making is impaired in various psychiatric disorders. We will also discuss why it's so hard to make rational decisions, and how we can use AI to improve our decision making.

Prerequisites: COGS 14A and BILD 12 or COGS 17 and COGS 18 or permission of instructor.

Harvard University

From Bench to Bedside: Entraining Policy to Science · course website

Circadian rhythms have a profound impact on our health and well being. Beyond regulating our sleep, they influence cognitive alertness, gastric motility, and cardiovascular health and many other body processes. Yet, our industrialized, 24/7 world often brings us out of sync with these rhythms leading to pervasive but addressable health consequences. Students will learn about the molecular and circuit mechanisms that sync our circadian rhythms to environmental cues like light and food, how our everyday activities and societal issues impact these rhythms, and how we can make policies to keep our circadian health intact without sacrificing all the amenities of modern life. Course developed and offered through the MAHPING Pedagogy Fellows Program.

GENED 1125: Artificial and Natural Intelligence · course website · S2022 evals · S2021 evals

What is intelligence? An inquiry into the nature of intelligence can take different forms – philosophical, biological, mathematical or technological. In this course, we will use machine intelligence (everything from voice recognizing smartphones to game-playing computers) as a handle to think about natural intelligence (brains and behavior of animals). Although we will start with big, general questions, we will quickly move to concrete queries about brains and computers. This approach, rather than just starting with brains of animals, may be useful in framing more universal questions independent of the specific architecture of brains of animals. As machines increasingly perform tasks that were once thought to be solely in the domain of humans, there is an urgent need for discussions of the moral and societal implications of artificial intelligence.

Guest lectures:

NB314QC/NB212: Math Tools for Neuroscience · course website · syllabus · github · JTerm2020 evals · F2020 evals

Numerical data analysis has become a nearly indispensable tool in modern neuroscience. This course aims to equip graduate students with the fundamental mathematical skills in quantitative modeling and data analysis necessary for neuroscience research. The course is aimed at first or second-year students in the Neuroscience PhD program, and is open to other graduate students in the biosciences. This pilot course serves as a crash course to the basics of linear algebra, differential equations, and basic probability and statistics from a mathematical perspective. Each mathematical concept will be illustrated via applications to neural datasets. In 2021, the course became a foundational requirement for the PiN Certificate in Computational Neuroscience.

Rice University

COLL 158: How Music Plays the Brain · syllabus · course evals · teaching evals

Why do we love music? Why do certain songs get stuck in our head, or remind us of certain events in our life? What can music teach us about the human brain? This course examines the ways in which music has shaped the human brain and how it continues to shape the way we act, think, and create into the modern age. Students will discuss and critique the various ongoing topics of music cognition and neuroscience research that aim to delve into the biology of this universal human obsession. Recipient of the 2017 Rice University Student-Taught Course Teaching Award.

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