Sina Rashidian

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

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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 CV is available here.


Highlights of my PhD journey:

  • 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 for 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, Special Computer Science Department Fellowship.
  • Aug 2015, Starting my PhD at Stony Brook University!