Hi, I am Ramin Mohammadi PhD, AI enthusiastic and Machine Learning researcher. I enjoy helping engineers like you to learn and build up a career path in this amazing domain.

Personal life

I enjoy outdoor activities and spending time with Family, our dog Leo and our cat Bumper. I love sports and am a calisthenic athlete. I play Tennis, Basketball, running, Snowboarding and trying to pick up surfing these days. I love indoor gardening and have a plant collection.

Primarily Work:

I am AI/ML lead at Tausight with a focus of applying deep learning, classical machine learning and natural language processing to cyber-security domain.

Teaching:

I am an adjunct professor at Northeastern University, College of Engineering

  • IE 7300 - Statistical Learning for Engineering
  • IE 7374 - ST : Machine Learning Operations (MLOps)
  • IE 7374 - ST : Machine Learning For Engineering
  • IE 6600 - Computation and Visualization for Analytics

I enjoy teaching and mentoring young minds and help them to understand the magic behind AI and teach them how to practically apply this knowledge’s to real life problems.

“Simple can be harder than complex: You have to work hard to get your thinking clean to make it simple. But it’s worth it in the end because once you get there, you can move mountains.”

Publications:

Title Link
An Analysis of Attention over Clinical Notes for Predictive Tasks Link
Diagnostic Accuracy of Shear Wave Elastography as a Non-invasive Biomarker of High-Risk Non-alcoholic Steatohepatitis in Patients with Non-alcoholic Fatty Liver Disease Link
Predicting Unplanned Readmissions Following a Hip or Knee Arthroplasty: Retrospective Observational Study Link
Factors Influencing Exercise Engagement When Using Activity Trackers: Nonrandomized Pilot Study Link
A Neural Network Based Algorithm for Dynamically Adjusting Activity Targets to Sustain Exercise Engagement Among People Using Activity Trackers Link
Development of an Engagement Engine to Support Long Term Use of Fitness Trackers and Sustain Physical Activity Link
Neural Network–Based Algorithm for Adjusting Activity Targets to Sustain Exercise Engagement Among People Using Activity Trackers: Retrospective Observation and Algorithm Development Study Link
Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data Link

Awards and Achievements


Family Image

Videos:

Boston Scientific Connected Patient Challenge III - Google, Boston

Work Experiences:

  • Principal Machine Learning Engineer / Leading Data Scientist - Tausight
  • Adjunct Professor - Northeastern University
  • Data Scientist - Partners Connected For Health
  • Deep learning Engineer Intern - Mitsubishi Electric Lab
  • Machine Learning Engineer Intern - Philips Lighting (Signify)
  • Data Scientist Intern - Partners Connected For Health
  • Geek Squad Precinct Lead
  • Student Mentors - Udacity
  • Multilingual Interpreter - UNHCR