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.

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

Rivelle Zlatopolsky (Research coordinator), Min Zheng (PhD student), Shina Ebrahim Zadeh (PhD student), Steven Hansen (MS student), Mark Mirtchouk (Undergraduate researcher), Drew Lustig (Undergraduate researcher), Alexandra Smith (Undergraduate researcher). Ivan Ching (Undergraduate researcher)

Our mascot is the Honey Badger, for obvious reasons.

Study Participants

We are actively recruiting participants for ongoing studies in the Hoboken area!

Recent courses

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



  • August 2016 New paper: Using Uncertain Data from Body-Worn Sensors to Gain Insight into Type 1 Diabetes (Journal of Biomedical Informatics) [paper]
  • June 2016 New paper: Automated Estimation of Food Type and Amount Consumed from Body-worn Audio and Motion Sensors (UbiComp). [paper]

    Congrats to Mark on his first paper as lead and receiving a Best Paper Honorable Mention!
  • May 2016 R01 successfully renewed for 4 more years and $1.5 million. Thanks NIH!
  • March 2016 New paper: Multimodality Sensing for Eating Recognition (accepted to Pervasive Health)

    Upcoming talk: I'll be speaking at MLconf NYC on April 15
  • February 2016 New paper: Causal Structure of Brain Physiology after Brain Injury from Subarachnoid Hemorrhage. PLoS ONE