I am a final year undergraduate pursuing a double major in Electronics and Biology and a Data Science minor at BITS Pilani, Goa.
I am in Boston pursuing my undergraduate thesis at QTIM Labs, HMS/MGH, with Dr. Chris Bridge, Dr. Albert Kim and Prof. Jayashree Kalpathy-Cramer, where I am working on creating deep learning methods for precision medicine. Previously, I worked closely with Prof. Ashwin Srinivasan and Prof. Raviprasad Aduri on knowledge-guided drug discovery at APPCAIR. During my time at APPCAIR, I have also had the pleasure of collaborating with UNSW and TCS research.
Feel free to connect on twitter or LinkedIn or reach out to shreyasbhat2001 at gmail dot com.
Research
My research broadly revolves around addressing fundamental AI challenges to enhance the reliability and generalizability of models in medical imaging and drug discovery. To this end, I am interested in looking at approaches grounded in neurosymbolic and foundational models for the above problems.
Outreach
I led the Society for Artificial Intelligence and Deep Learning(SAiDL) and Language Research Group (LRG), where I used to organize various research and outreach activities. We actively participate in open-source projects and paper-reading sessions. Get in touch if you are interested in taking part!
2024
March: My work with HMS/MGH abstract is accepted at ISBI 2024 !🥳
Feb: presented our AAAI paper in Vancouver, CA. Great city!
Jan: presented my work at "Science on Tap", a weekly seminar at Martinos Center, HMS/MGH
Happy New Year! ✨
2023 and before
December: Paper in collaboration with TCS research accepted at AAAI 2024!! 🥳🧬
August: Our abstract in collaboration with HMS/MGH is accepted at RSNA 2023 🎉!!
July: I will be in Boston at QTIM labs at HMS/MGH!
June: Paper in collaboration with UNSW/TCS research accepted at IEEE ICIP 🎉 which is fully funded by CSE dept., UNSW and I have also received a scholarship of 300 USD from IEEE SPS!!
Jan: I will be a TA for BITS F464: Machine Learning
- 2022
December: Delivered a talk in an interview talk series in collaboration with IEEE and SAiDL
September: We came second in poster presentation in the AI for Drug discovery track at ICDD 2022! 🎉
September: We at SAiDL and APPCAIR are organizing the 3rd edition of the AI Symposium. Register here
June: Selected to attend Amazon Summer School 2022!
June: Excited to start research at QTIM labs, Martinos Center, Harvard Medical School and MGH!
May: Accepted to attend Eastern European Machine Learning Summer School (EEML 2022)
May: Accepted to attend 3D Vision Summer School(3DVSS) @IIIT-H
March: Instructor for a course on "introduction to machine learning and deep learning"
March: Organized a Kaggle Competition as a part of TechWeekend by CTE
Jan: Started research at APPCAIR Labs
Jan: Helped in creating the SAiDL Spring Assignment and mentoring students in computer vision
- 2021
November: Instructor for workshop on "introduction to machine learning"
September: Joined CVRL at UIUC as an undergraduate researcher
September: Organized Summer Symposium on AI Research, invited top AI researchers as speakers.
August: Qualified Asia First round of ICPC along with my team
August: Accepted for 5th summer school on AI by IIITH
July: Accepted for summer school on Computational Neuroscience organized by neuromatch academy
June: Started research internship at VIGIL - IIT Hyderabad
May: Attended the "Nvidia Building Transformer-Based Natural Language Processing Applications" Workshop.
May: Machine Learning intern at LearningMate
