Papers

Deep learning architectures have achieved state-of-the-art (SOTA) performance on computer vision tasks such as object detection and …

Using observational data to learn causal relationships is essential when randomized experiments are not possible, such as in …

Large biomedical datasets can contain thousands of variables, creating challenges for machine learning tasks such as causal inference …

Social and behavioral determinants of health (SBDH) are environmental and behavioral factors that are increasingly recognized for their …

In this paper, we aim to explore patient trajectories in time that evolve according to their risk of developing comorbidities. For our …

Experience

 
 
 
 
 
August 2019 – Present
New Jersey

PhD Student

Stevens Institute of Technology

Responsibilities:

  • Conducting research in the Scientific Artificial Intelligence Lab advised by Professor Nikhil Muralidhar
 
 
 
 
 
December 2015 – January 2019
New York

Research Assistant

Columbia University Medical Center

Responsibilties:

  • Worked with Professors Noémie Elhadad and Rajesh Ranganath to implement a distributed variational inference algorithm for a massive, simultaneous survival problem
  • Ran experiments on health record dataset of 300k+ patients on compute cluster
  • Conducted clinical abbreviation expansion research, model trained on 600k hospital discharge summaries
 
 
 
 
 
May 2009 – August 2015
New York

Lead Software Engineer

Conductor

Responsibilties:

  • Worked as a back-end engineer and technical lead on a highly scalable search analytics platform
  • Worked with my team to design and implement a collection, data processing, and ETL pipeline for Google/Adobe analytics reports using Hadoop, Hbase, Kafka, and Hive