Dennis Shen

Dennis Shen

PhD Candidate in EECS

MIT

Biography

I am a PhD candidate in Electrical Engineering and Computer Science (EECS) at MIT, affiliated with the Laboratory for Information and Decision Systems (LIDS) and Institute for Data, Systems, and Society (IDSS). I am fortunate to be advised by Professor Devavrat Shah.

Interests

  • Machine Learning
  • High-dimensional Probability & Statistics
  • Matrix/Tensor Estimation
  • Causal Inference

Education

  • PhD in EECS (expected), 2020

    Massachusetts Institute of Technology

  • MSc in EECS, 2017

    Massachusetts Institute of Technology

  • BSc in EE, 2015

    University of California, San Diego

Recent Publications

Synthetic Interventions

Under Submission, 2020. Workshop version in NeurIPS Workshop on CausalML, 2019

Two Burning Questions on COVID-19

Memo, 2020

On Robustness of Principal Component Regression

NeurIPS, 2019 (oral presentation). To also appear in Journal of American Statistical Association (JASA)

Multi-dimensional Robust Synthetic Control

POMACS, 2019. Also in ACM Sigmetrics, 2019

Model Agnostic Time Series Analysis via Matrix Estimation

POMACS, 2018. Also in ACM Sigmetrics, 2019

Robust Synthetic Control

Journal of Machine Learning Research (JMLR), 2018

Ongoing Projects

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COVID-19

Two Burning Questions: Did shutting down the economy help? Can we (partially) reopen the economy without risking the second wave?

Drug Discovery

Predicting impact of chemical therapies on cell types

Work & Research Experience

 
 
 
 
 

Core Data Science Research Intern

Facebook

Jun 2018 – Aug 2018 Menlo Park, California
 
 
 
 
 

Graduate Research Assistant

MIT SPPIN

Sep 2015 – Present Cambridge, MA
 
 
 
 
 

Undergraduate Research Assistant

UCSD Computer Vision and Robotics Research

Sep 2014 – Jun 2015 La Jolla, California
 
 
 
 
 

Undergraduate Research Assistant

UCSD Mobile Systems Design Lab

Jan 2013 – Sep 2014 La Jolla, California

Teaching

MIT 6.s077 Introduction to Data Science and Statistics (Spring 2019)
  • undergraduate-level introduction to principles, models, and algorithms for data science
UCSD ECE 35 Introduction to Analog Design (2013 - 2015)
  • undergraduate-level introduction to fundamental circuit theory concepts
UCSD ECE 25 Introduction to Digital Design (2013 - 2015)
  • undergraduate-level introduction to digital electronics

Contact