The Distinguished Lecture Series Explores the Different Ways Machine Learning is Used in Research

The Distinguished Lecture series brings computer scientists to Columbia to discuss current issues and research that are affecting their particular fields.

This year, four experts covered topics on how machine learning is used in drug discovery, software testing, RNA splicing, and surrogate loss functions:

Regina Barzilay, MIT
Modeling Chemistry for Drug Discovery: Current State and Unsolved Challenges
Koushik Sen, UC Berkeley
Automated Test Generation: A Journey from Symbolic Execution to Smart Fuzzing and Beyond
Oded Regev, Courant Institute, New York University
Using Machine Learning for Scientific Discovery in Biology
Shivani Agarwal, University of Pennsylvania
Surrogate Loss Functions in Machine Learning: What are the Fundamental Design Principles?

Below are a couple of the lectures from prominent faculty from universities across the country.

Automated Test Generation: A Journey from Symbolic Execution to Smart Fuzzing and Beyond
Koushik Sen, UC Berkeley

Surrogate Loss Functions in Machine Learning: What are the Fundamental Design Principles?
Shivani Agarwal, University of Pennsylvania

Cross-disciplinary Research Highlighted in This Year’s Distinguished Lectures Series

The Distinguished Lecture series brings computer scientists to Columbia to discuss current issues and research that are affecting their particular fields. This year, eight experts covered topics ranging from machine learning, human-computer interaction, neural language models, law and public policy, psychology, and computer architecture.

Below are a couple of the lectures from prominent faculty from universities across the country.

Three Ways Machine Learning Fails and What to Do About Them
Costis Daskalakis, MIT

Intuitive Reasoning as (Un)supervised Neural Generation
Yejin Choi, University of Washington

Computer Science and Law: Opportunities and Research Directions
Joan Feigenbaum, Yale

Data Orchestration is the New Compute: Computer Architecture for the Post-Moore
Era Joel Emer, NVIDIA/MIT

Theoretical Reflections on Quantum Supremacy
Umesh Vazirani, UC Berkeley

The Distinguished Lecture Series Explores the Latest in CS Research

The Distinguished Lecture series brings computer scientists to Columbia to discuss current issues and research that are affecting their particular fields. This year, eight experts covered topics from machine learning, cryptography, privacy, algorithms, ethics, and computer vision.

Below are a couple of the lectures from prominent faculty from universities across the country.

- Lifting Lower Bounds, Communication, and Proofs
  Toniann Pitassi, University of Toronto

- Controlling the Black Box: Learning Manipulable and Fair Representations
  Richard Zemel, University of Toronto

- Towards anonymous and metadata private communication at Internet scale
  Srini Devadas, MIT

- From Ethical Challenges of Intelligent Systems to Embedding Ethics in Computer Science Education
  Barbara Grosz, Harvard University

- Using Sound to Help You See and Sight to Help You Hear
  Bill Freeman, MIT

- Divergences in Neural Machine Translation
  Marine Carpuat, University of Maryland

- Learning Language Through Interaction
  Hal Daume, University of Maryland

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