Salah Assana

Salah Assana

Research Assistant

Harvard Medical School


I am a Computer Science and Healthcare enthusiast with a background in research and software engineering. I have worked as a Research Assistant (RA) since 2015 at several laboratories including UVA Link Lab, MIT Media Lab and HMS Cardiac MR Center.

My research spans across signal processing, machine learning and medical imaging. I have published to ACM conferences including UbiComp and MobiCom as well as medical journals including JACC, JCMR and ISMRM.

Download my resumé.

  • Medical Imaging
  • Signal Processing
  • Artificial Intelligence
  • Master of Science, 2020

    Massachusetts Institute of Technology

  • BS in Computer Science, 2017

    University of Virginia

  • AS in Computer Science, 2015

    Northern Virginia Community College


Harvard Medical School
Research Assistant II
Jan 2021 – Present Boston, MA
  • Increased the speed of a free-breathing, free-running perfusion sequence by 1000% using deep learning.
  • Deployed ML models on Siemens scanner for real-time data processing using FIRE framework.
  • Collaborated with MRI technicians to add-on experimental scans to clinical patients.
MIT Media Lab
Research Assistant
Sep 2018 – May 2020 Cambridge, MA
  • Developed a novel mmWave sensor capable of contactless cardiovascular activity monitoring.
  • Used C++ Boost library to enable the use of multiple sensors concurrently and allow for real-time data evaluation.
  • Used MATLAB to filter signal and analyze the cardiac data for signs of heart illnesses.
Booz Allen Hamilton
Software Engineer
Sep 2018 – May 2020 Tysons, VA
  • Worked as full stack developer on a scrum team with C# and JavaScript libraries like AngularJS & Backbone.
  • Used Hadoop and Hive to build a scalable distributed data lake on AWS.
  • Built a abstractive text summarization tool using TensorFlow, NumPy, Pandas and Pyrouge
UVA Link Lab
Research Assistant
Sep 2015 – May 2017 Charlottesville, VA
  • Introduced a new doorway sensor capable of determine travel direction with 99.7% accuracy.
  • Wrote multi-threaded C driver to increase speed of sensor by 3000% & reduced energy consumption by 50%.
  • Develop optical flow based tracking algorithm robust to illumination changes & background movement in Python.