ML Resources

 

 

Below we have a description of different ML reading groups, events, and resources available at MIT! We are continually growing this list and would love to hear about more opportunities :)

 

ML Reading Groups

  1. ​Computational Medicine and Healthcare Reading Group
    1. Meets every other week in E25 on Mondays and Tuesdays
    2. Related Labs: Collin Stultz's Lab
    3. For more information: https://mit-ccrg.github.io/
  2. Medical Vision Reading Group
    1. Meets every Monday at 2:30-4:00 in 32D-451
    2. Related Labs: Polina Golland's Lab
    3. For more information: http://groups.csail.mit.edu/vision/golland/group_meeting/doku.php
    4. Focus on CV/ML methods for medical imaging
  3. FastML
    1. Meets every Monday at 12pm in 32-370
    2. There is food! 
    3. Read papers related to efficient ML, from algorithms (e.g. pruning, quantization, optimization algorithms) to systems (e.g. deep learning ASICs)
    4. Mailing list: fastml-reading-group@csail.mit.edu
  4. Stats Reading Group
    1. Meets every Friday at 9:30-11am in 32-D451
    2. Related Labs: Tamara Broderick's Lab
    3. Mailing list:  readstat@lists.csail.mit.edu 
    4. Topics change depending on the semester -- this semester, mostly covered variable selection methods
  5. Embodied Intelligence Seminars and Reading Group
    1. Meets Wednesdays 2-3pm (starting Feb 12) in the Star conference room (32-D463)
    2. Most meetings will have invited talks from PIs and the other meetings will include reading group discussions or debates
    3. Food and discussion after each meeting
  6. ML + NLP for clinical applications 
    1. Meets most Tuesdays 4-5pm
    2. Related Labs: Pete Szolovits's group (Clinical Decision Making group)
    3. Mailing list: medg-active-reading-group@googlegroups.com
    4. Coordinated by Tiffany Min (symin95@gmail.com)
  7. Value Alignment Reading Group
    1. Meets on Thursdays, 10.30am-12pm @ 46-4062
    2. Mailing list: ai-alignment@mit.edu
    3. Agenda:  https://bit.ly/2PlfsYI
    4. Description: An interdisciplinary reading group focused on the philosophical and computational foundations of representing and learning human values in order to build robustly beneficial AI. Readings drawn from AI, economics, cognitive science, philosophy, and more.
  8. SIPB Deep Learning Reading Group
    1. Meets on Thursdays in room 2-135
    2. Mailing list: sipb-deeplearning@mit.edu
    3. Coordinated by Alex Coventry (alx@mit.edu) 
  9. ML Interpretability Reading Group
    1. Meets Mondays at 1pm in 32G-631
    2. Mailing list: mlirg@mit.edu
  10. Theory of Modern Machine Learning Seminar (at Harvard)
    1. Agenda: https://mltheory.org/#calendar 
    2. Related Labs/Professors: Boaz Barak
  11. MIT Machine Intelligence Community (MIT MIC)
    1. Information at https://github.com/MIT-MIC/Reading-Groups