CNS 100: Introduction to Computation and Neural Systems

Information

Description

How does the brain compute? Can we endow machines with brain-like computational capability? Faculty and students in the Computation and Neural Systems (CNS) program ask these questions with the goal of understanding the brain and designing systems that show the same degree of autonomy and adaptability as biological systems.

This course is designed to introduce undergraduate and first-year CNS graduate students to the wide variety of research being undertaken by CNS faculty. Topics from all the CNS research labs are discussed and span the range from biology to engineering.

Schedule

Week 1: September 30th, 2021

Speaker: Carlos Lois, MD, PhD
Research Professor

Week 2: October 7th, 2021

Important: Lecture will take place in Chen 100 at 5pm.
Speaker: Pietro Perona, PhD
Allen E. Puckett Professor of Electrical Engineering

Week 3: October 14th, 2021

Speaker: Athanassios Siapas, PhD
Professor of Computation and Neural Systems

Week 4: October 21st, 2021

Important: Lecture will take place in Chen 100.
Speaker: Betty Hong, PhD
Clare Boothe Luce Assistant Professor of Neuroscience

Week 5: October 28th, 2021

Important: Lecture will take place on Zoom.
Speaker: Anima Anandkumar, PhD
Bren Professor of Computing and Mathematical Sciences

Week 6: November 4th, 2021

Important: Lecture will take place in Chen 100.
Speaker: Erik Winfree, PhD
Professor of Computer Science, Computation & Neural Systems, and Bioengineering

Week 7: November 11th, 2021

Speaker: David Anderson, PhD
Seymour Benzer Professor of Biology

Week 8: November 18th, 2021

Speaker: Shinsuke Shimojo, PhD
Gertrude Baltimore Professor of Experimental Psychology

Week 9: November 25th, 2021

Thanksgiving Break (No Speakers)

Week 10: December 2nd, 2021

Speaker: Viviana Gradinaru, PhD
Professor of Neuroscience and Biological Engineering

Week 11: December 9th, 2021

Important: Lecture has been cancelled.
Speaker: Paul Sternberg, PhD
Thomas Hunt Morgan Professor of Biology

Policy

This course is graded on a pass/fail basis. Course registrants are expected to arrive on time. Undergraduate students have four unexcused absences to receive passing marks. Graduate students have two unexcused absences to receive passing marks. Excused absences can be arranged beforehand with the teaching assistant.