Link Search Menu Expand Document

Nandita Bhaskhar

nanbhas at stanford dot edu


About Me

I'm on the job market this quarter!

I am a PhD student at Stanford University, where I develop Robust, Data-efficient and Trustworthy ML for healthcare. At Stanford, I am lucky to be advised by Daniel Rubin and work with amazing collaborating PIs - Akshay Chaudhari, Christopher Lee-Messer, Jonathan Chen, and Wui Ip. I am affiliated with Stanford AIMI (Center for Artificial Intelligence in Medicine and Imaging) and Stanford CRFM (Center for Research on Foundation Models).

Broadly, I am interested in robust representational learning, where I leverage modern self-supervision to train large foundation models to learn robust representations of the world in a label-efficient manner. I am also interested in trustworthy ML research. Most models assume a closed-world scenario even though data during deployment may come from an open-world, i.e., from shifted distributions and containing unseen new concepts. This makes predictions from models untrustworthy, leading to ineffective deployment and AI safety issues. I develop methods to quantify model trust and decide when we can trust these models' predictions and when we should not. I am also excited by few-shot/zero-shot learning and continual learning (with non-stationary data and concepts, how can we ensure the model learns to adapt efficiently?) as well as active learning (what are the most representative samples in the data the model can learn effectively from?).

Since Spring 2021, I founded and co-organize the Stanford MedAI Group Exchange Sessions, an inter-institutional weekly seminar series featuring speakers from around the world on advances in medical AI research. Check out our YouTube channel!

Outside of research, I have several interests that span a wide gamut of things - including but not restricted to - travelling, social dance, gardening, music, art, creative writing, getting lost, hiking, biking and exploring new things.

Resume Academic CV

Timeline / Bio / Github / LinkedIn / Twitter /  Google Scholar


  • [Media] (2023/07/07) My thesis dissertation has been featured on the Computer Vision News, July 2023 edition!
  • [Award] (2023/06/05) Had an amazing time at MIDL 2023 in Nashville. Wonderful music, people and research! Our work was judged to be in the Top 8 submissions and gets an automatic accept to the Medical Image Analysis journal.
  • [Media] (2023/06/05) Our work on domain-specific augmentations has been featured on the Computer Vision News, June 2023 edition!
  • [Defense] (2023/05/30) I successfully defended my PhD dissertation! Yay!
  • [Award] (2023/04/21) My Friday lectures for Spring CS229 have been chosen for the official Stanford SCPD offering of the course!
  • [Presentation] (2023/04/17) Had a wonderful time giving a guest lecture in Minhaj Alam's course, ECGR 4090/5090 - Artificial Intelligence in Biomedical Applications, at UNC Charlotte
  • [Award] (2023/04/04) We have been selected for an Oral Presentation at MIDL for our work, Exploring augmentions for Siamese Representation Learning for Chest X-rays! Excited to present this in person!
  • [Teaching] (2023/03/31) I'll be TAing Stanford ENGR76 (Information Science and Engineering) this Spring 2023 with Prof. Ayfer Ozgur and an amazing teaching team! Excited to join the scaling efforts going from a ~30 student enrollment to a ~200 student enrollment!
  • [Teaching] (2023/03/27) Wrapped up ENGR108! What a fun course to teach - holding sections and getting to know my sectionees was amazing! Brad is one of my favourite lecturers on campus and I highly recommend taking this course!
  • [Paper] (2023/02/27) Our paper, Exploring augmentions for Siamese Representation Learning for Chest X-rays, has been accepted to the Medical Imaging with Deep Learning (MIDL) Conference!
  • [Paper] (2023/02/14) My paper, Trust-Lapse - a mistrust scoring framework for continuous model monitoring, has been accepted for publication in the IEEE Transactions on Artificial Intelligence (IEEE-TAI)
  • [Teaching] (2023/01/02) I'll be TAing Stanford ENGR108 (Introduction to Matrix Methods) this Winter 2023 with Prof. Brad Osgood and a wonderful, close-knit set of TAs!
  • [Award] (2022/11/29) I'm attending NeurIPS 2022 at New Orleans and presenting my work at the WiML workshop! So many exciting research works and amazing community. Thank you, WiML for the registration and travel award!
  • [Teaching] (2022/09/29) Honored to be the Head TA for Stanford CS229 (Machine Learning) this Fall 2022. We have an amazing set of TAs this quarter as well. Excited to handle all aspects of the course and lead the team.
  • [Professional] (2022/09/15) I'll be joining the Stanford CRFM Publicity and Community Team for 2022-23
  • [Presentation] (2022/09/07) I've been selected to present an Oral talk at BayLearn 2022 (one amongst 6 presenters from both industry and academia from over 100 applicants), held at Genentech this year!
  • [Mentorship] (2022/09/04) Excited to be a part of the Google CSRMP Fall 2022 program! Amazing mentors and community!
  • [Teaching] (2022/06/10) Teaching CS229 in person was a blast! I taught all the Friday TA lectures again this quarter and it was amazing. Thanks all for the wonderful quarter
  • [Teaching] (2022/03/22) I'll be TAing (decided not to be the Head TA, research calls!) Stanford CS229 (Machine Learning) this Spring 2022 with Profs. Tengyu Ma and Chris Re and an amazing teaching team! Finally back in person.
  • [Teaching] (2021/09/15) I'll be TAing Stanford CS229 (Machine Learning) this Fall 2021 with Profs. Andrew Ng, Moses Chariker and Carlos Guestrin and an amazing teaching team! This is going to be an all remote quarter!
  • [Presentation] (2021/05/01) I'll be presenting our work on out of distribution detection at SIIM 2021!
  • [Blog] (2021/04/21) Check out my post on browser tab management to sort out your digital life
  • [Blog] (2021/04/15) My first post in the ML workflow series is out. Learn more about port forwarding and use it in your daily worklife!
  • [Blog] (2021/04/02) My post on multiplication amongst other things is out. Read on to know why (-1) x (-1) = 1 and some abstract algebra along with it!
  • [Professional] (2021/03/24) I'll be co-organizing the Stanford MedAI Group Exchange series from next week. We have an exciting line up of speakers!
  • [Mentoring] (2021/03/10) I'll be mentoring 3 undergrads over the summer for research as part of Stanford REU 2021 (Research Experience for Undergrads)!
  • [Presentation] (2020/12/10) I presented our work on predictive uncertainty estimation for EEG analysis at AES 2020!
  • [Grant] (2020/11/20) Won my first research grant (HAI)! Huge shout out to Daniel for all the help and support!
  • [Award] (2020/11/01) I won the 3rd place at the IIBIS AIMI Poster Session for my work on predictive uncertainty estimation for EEG analysis!
  • [Presentation] (2020/10/05) I'll be presenting our work on out-of-distribution detection for EEG analysis at the Pioneering NeuroHealth Symposium, 2020!
  • [Professional] (2020/08/20) I won the SPICE grant for my GradsTeachGrads initiative!
  • [Blog] (2020/08/17) My post on extracting activations from pre-trained models in PyTorch is out!
  • [Blog] (2020/08/10) My post exploring the nuances between sigmoids and softmax in ML applications is out!
  • [Blog] (2020/07/03) My post compiling some unifying notation on probabilistic classifiers from CS, math and stats is out!
  • [Blog] (2020/03/19) My post summarizing the pluses and minuses of each number system is out!
  • [Blog] (2020/03/18) My post on understanding one's cognitive distortions for better mental health is out. Check out those sketchonotes!
  • [Blog] (2020/03/01) I'm starting my new blog, Roots of my Equation. Keep an eye out for my blog posts!
  • [Teaching] (2019/05/31) I'll be TAing Stanford CS229 (Machine Learning) this Summer with Anand Avati and an amazing teaching team!
  • [Professional] (2019/05/25) I've agreed to serve as the Student Advisor to the SERC team at DBDS! Excited!
  • [Award] (2019/05/20) I've been selected to be a CIRS scholar! I'll be starting to work with the this Fall!
  • [Mentoring] (2019/04/01) I'll be mentoring high school students this summer for research as part of SIMR 2019 (Stanford Institute of Medicine Summer Research)!
  • [Award] (2019/03/01) I've been awarded the UnifyID fellowship for this Spring!
  • [Professional] (2019/02/25) I'll be continuing this year as well as a resident EV Woods CA!
  • [Research] (2018/10/15) I'm switching fields!! I'll be working on machine learning for medical applications! Excited for this new direction!
  • [Teaching] (2018/08/22) I'll be TAing CS217 (Hardware accelerators for Machine Learning) this Fall with Prof. Kunle Olukotun. This is the first time it is being offered!
  • [Professional] (2018/05/31) I've been elected the Co-President of GradSWE! Excited about the coming year!
  • [Professional] (2018/05/31) I'll be joining the Stanford IEEE student chapter this year as the Industry Chair!
  • [Internship] (2018/04/15) I'll be joining the SmartRF team at Qualcomm Coorporate R&D for a summer internship in San Diego!
  • [Professional] (2018/02/25) I'll be continuing as a resident EV Woods CA this year!
  • [Presentation] (2017/09/24) We'll be presenting our poster on Axon Bundle Activation at TEATC (The Eye and the Chip) conference at Denver!
  • [Award] (2017/08/01) I've been awarded the IEEE Santa Clara Valley Women In Engineering (WIE) Scholarship!
  • [Paper] (2017/08/01) Our work on axon bundle detection is now published in the Journal of Neurophysiology!
  • [Professional] (2017/05/31) I'm honoured to serve as the Vice-President of GradSWE during the upcoming year!
  • [Professional] (2017/05/31) I'll be continuing as the Faculty Liaison in WEE this year!
  • [Award] (2017/03/22) Our team is a finalist at the Qualcomm Innovation Fellowship - top 30 from among 200! We'll be flying to San Diego to present our work
  • [Teaching] (2017/03/01) Based on last time's success, Ashwin and I are re-offering our Splash course this Spring -- Magic, Mystery and Math!
  • [Teaching] (2017/02/25) I'll be TAing PSYCH287 (Brain Machine Interfaces) this Spring with Profs. E. J. Chichilnisky and Justin Gardner!
  • [Professional] (2017/02/25) I've joined the amazing Graduate Community Associate (CA) team for Escondido Village (EV)! Go Woods!
  • [Award] (2016/09/01) Our research on Axon Bundle Activation detection has been awarded the Best Poster amongst over 200 at the BioX Annual IIP Seed Grant Symposium
  • [Professional] (2016/05/31) I've been elected the Faculty Liaison for WEE this year!
  • [Teaching] (2015/12/20) I'll be TAing EE271 (Intro to VLSI systems) this Winter with Profs. Binh Le and Subhasish Mitra!
  • [Teaching] (2015/09/21) I'm teaching another Splash course this Fall with Ashwin -- Magic, Mystery and Math!
  • [Teaching] (2015/09/01) I'll be TAing ENGR40M (Intro to Making) this Fall with Prof. Mark Horowitz and an amazing teaching team led by Steven Bell!
  • [Internship] (2015/03/15) I'll be joining the Advanced Technology team at Proteus Digital Health for a summer internship!
  • [Teaching] (2015/03/01) I'm teaching a Splash course this Spring with Ashwin -- the P in Poker!
  • [Award] (2015/02/07) Hurray! I passed the (notorious) EE quals at Stanford! Yup, ten 10-minute interviews with 10 professors who can quiz you on ANYTHING!
  • [Award] (2014/03/15) I've been awarded the Stanford EE departmental fellowship!
  • [Research] (2014/03/15) I'll be joining Stanford this Fall for grad school! Super excited!