About me

I'm an Assistant Professor in the Computer Science department at Stevens Institute of Technology.

After completing my PhD in Computer Science in 2010 at NYU, I spent two years as a postdoctoral Computing Innovation Fellow at Columbia University, in the Department of Biomedical Informatics. Before that I was an undergraduate at NYU in Computer Science and Physics.

I've written an academic book, Causality, Probability, and Time, and another for a wider audience, Why: A Guide To Finding and Using Causes, that was published in 2015.

HAIL logo
Health and AI Lab website

We are primarily motivated by trying to improve human health, through the development of artificial intelligence methods. Most of these problems come back to the question of why things happen or how they change, so we focus on causal inference and time series data. We look at both clinical data as well as data generated outside of hospitals and aim to support both medical providers and patients in their decision making. Key application areas include stroke and diabetes. We are also working on devices that can automatically measure food intake, using body-worn sensors.

Lab members

Min Zheng (PhD student), Shina Ebrahim Zadeh (PhD student), Yiying Hu (MS student), Mark Mirtchouk (Undergraduate researcher), Drew Lustig (Undergraduate researcher), Alexandra Smith (Undergraduate researcher). Ivan Ching (Undergraduate researcher), Dana McGuire (Undergraduate researcher)

Our mascot is the Honey Badger, for obvious reasons.

Recent courses

Spring 2017 Health Informatics [CS-544]
Fall 2016 Causal Inference [CS-582]

Current Funding

James S. McDonnell Foundation Scholar Award, NSF CAREER Award, NIH R01

(email is my preferred contact method)

Lab twitter: @HealthAI_Lab

Current Openings

We're hiring postdocs and seeking undergrad and grad students. Join us!


Time and Causality in the Sciences (TaCitS) June 7-9, 2017


  • June 2017 The Health and AI Lab now has its own website!
  • May 2017 Congrats to Mark Mirtchouk on receiving the Stephen L. Bloom Theoretical Computer Science Award!

    I received the Provost's Early Career Award for Research Excellence.
  • January 2017 New paper: A Method for Automating Token Causal Explanation and Discovery (accepted to FLAIRS). Congrats Min!
  • November 2016 I was recognized as a Kavli Fellow. See my talk on causality from the Kavli Frontiers of Science meeting [here]
  • August 2016 New paper: Using Uncertain Data from Body-Worn Sensors to Gain Insight into Type 1 Diabetes (Journal of Biomedical Informatics) [paper]