Data, Machines, and AI (DMAI) Reading Group

Data, Machines, and AI (DMAI) is a reading group to discuss AI theory and methods, with a strong bent towards understanding what AI methods are most suitable for groundbreaking problems in biology and medicine, and how to advance the state-of-the-art.

Schedule

Reading group meets every two weeks. We have a speaker for every meeting. The speaker selects a paper and sends it to the group coordinator one week before the presentation. The coordinator shares the information with the group. Everyone is expected to read the paper before the group meeting.

Each meeting lasts for 1 hour and has three parts:

Paper presentation (30 minutes): The speaker presents the paper, including background, motivation, key challenges, methods and modeling assumptions, datasets, and experiments. The focus is on algorithms and carefully considering what makes them suitable for biomedical applications and why.
Insights (5-10 minutes): The speaker shares their insights with the group. This includes insights related to the merits of the research, possible future directions, how this research can be used in our ongoing projects, any drawbacks and ideas on how to fix them, any related-papers (other approaches to study the same problem), etc.
Discussion (20-25 minutes): Q&A and broader debate, brainstorming what biological or medical questions these methods can help us answer, dataset availability, source code implementation, any other topic attendees want to discuss.

These are interactive events; questions and comments are welcome throughout the meeting!

Speakers

Every meeting has a dedicated speaker responsible for selecting a paper and presenting it. We use a rotation system for speakers. Members of the reading group can expect to speak 1-3 times a year.

Paper selection

Papers presented at the reading group are published at various venues over the last two years. Following is a sampling of relevant journals and conferences.

Journals:
- Nature, Science, and Cell family, NEJM, PNAS, Lancet journals, JAMA journals
Machine learning and data science:
- Conferences: ICML, NeurIPS, ICLR, ACL, EMNLP, KDD, ICDM, AAAI, IJCAI, UAI, FAT*, AISTATS, WSDM, SIGIR
- Bioinformatics conferences: ISMB, RECOMB, PSB
- Journals: TPAMI, JMLR, TKDD, TKDE, Bioinformatics, JAMIA, PLoS Computational Biology, BMC journals, ACS family

We are generally interested in exciting, intriguing, and thought-provoking papers, no matter their publication venue, including preprints (e.g., arXiv, bioRxiv, and medRxiv).

Time

Every other Thursday at 4:30-5:30pm EST.

Location

Virtual meetings on Zoom. We will resume in-person meetings as soon as we return to campus.

Coordinator

Reach out to the reading group coordinator (Huan He, <huan_he@hms.harvard.edu>) with questions, comments, and suggestions.