Sina Rashidian


  • Ph.D. student, Computer Science, Stony Brook University
  • Research area:
    • Data Analytics
    • Machine Learning/Deep Learning
  • Contact: Old CS 2212
  • Email: srashidian [at]


I'm fifth year PhD candidate at the Department of Computer Science in Stony Brook University. I am privileged to work under the supervision of Prof. Fusheng Wang. I received my B.S. in Software Engineering from Sharif University of Technology, Iran.

My prospective graduation date would be in Dec 2020.

Highlights of my PhD journey:

  • Dec 2020, I have successfully defended my PhD thesis “Data generation and predictive modeling using deep learning with electronic health records” on Dec 14th 2020. Committee members: Dr. Fusheng Wang, Dr. Joel Saltz, Dr. Zhaozheng Yin, and Dr. Hossein Estiri.
  • Sept 2020, I am thrilled to announce “Detecting Miscoded Diabetes Diagnosis Codes in EHR for Quality Improvement: A Temporal Deep Learning Approach” got accepted in JMIR Medical Informatics (JMI) journal.
  • June 2020, our paper “SMOOTH-GAN: Towards Sharp and Smooth Synthetic EHR Data Generation” is accepted for a long presentation at AIME 2020! Very excited to share my research in this conference which is virtual this year. Update (Aug 2020): My presentation is available from here.
  • May 2020, I have successfully passed my prelim exam. Committee members: Dr. Fusheng Wang, Dr. Joel Saltz, Dr. Zhaozheng Yin.
  • April 2020, I won the grand prize for Graduate Student Employee of the Year 2020!!!!! I wrote a long post on my LinkedIn about this amazing honor. Anyhow, do not miss this 2 miniutes and 32 seconds video, it is a must watch :D
  • June 2019, “Machine Learning Based Opioid Overdose Prediction Using Electronic Health Records” is accepted at AMIA 2019 Annual Symposium.
  • June 2019, Unfortunately, due to unreasonably long processing time of export licenses these days, I cannot make it to my summer internship position at Verily.
  • April 2019, presenting my recent findings “Using AI to Optimize Methods for Decision Support for Population Health: A Diabetes Case Study” at 3rd NorthEast Computational Health Summit (NECHS) 2019.
  • March 2019, “Geographic, temporal, and sociodemographic differences in opioid poisoning” is accepted at American Journal of Preventive Medicine (AJPM) journal.
  • Jan 2019, Happy to announce I accepted an internship position at Verily Life Sciences for the incoming summer.
  • Nov 2018, “Disease phenotyping using deep learning: A diabetes case study” is accepted at Machine Learning for Health (ML4H) workshop at NeurIPS 2018 .
  • Oct 2018, Winning Mount Sinai Health Hackathon on rare diseases as the EyeCanDo team. You can see the demo and the moment we win the award + our speech.
  • Sept 2018, “Deep Learning on Electronic Health Records to Improve Disease Coding Accuracy” is accepted at AMIA Informatics Summit 2019 .
  • Sept 2018, “EaserGeocoder: Integrative Geocoding with Machine Learning” is accepted at ACM SigSpatial 2018 .
  • Sept 2017, “Effective Scalable and Integrative Geocoding for Massive Address Datasets” is accepted at ACM SigSpatial 2017 .
  • Aug 2017, I have successfully defended my research proficiency exam (RPE). Committee members: Dr. Fusheng Wang, Dr. Paul Fodor, Dr. Niranjan Balasubramanian.
  • Aug 2015, Received the Special Computer Science Department Fellowship.
  • Aug 2015, Starting my PhD at Stony Brook University!