Welcome To Amit Dhurandhar's Webpage..
I am originally from Pune, India. I am now a research staff member at IBM T.J. Watson in Yorktown Heights NY. I completed my Ph.D. in the Department of Computer and Information Science and Engineering at the University of Florida (UF), Gainesville. My advisor was Dr. Alin Dobra. My primary research areas are Machine learning and Data Mining.
I admire originality and brilliance but believe that having the right attitude is more important in life.
Here is the link to KDD Speaker Day that I organized at Watson Research in Aug. 2014.
Here is an interesting article comparing conference vs journal publications in computer science.
- Paper on teaching explanations accepted for a oral presentation to AIES, 2019.
- Invited to attend a Schoss Dagstuhl Seminar in 2019.
- Our work on improving simple models and contrastive explanations was featured in PC magazine, 2018.
- Paper on predicting smells using natural language and interpretable methods accepted to Nature Communications, 2018. (Featured in Quartz)
- Two first author papers on interpretable AI accepted to NeurIPS, 2018.
- Invited talk on formalizing interpretability given in the interpretability session at the European Conference on Data Analysis, 2018.
- Our paper on contrastive explanations for deep learning models featured in Forbes, 2018.
- Predicting Human Olfactory Perception from Chemical Features of Odor Molecules Paper accepted to Science, 2017. (New Yorker, Atlantic, Science News, The Biological Scene)
- It has been highlighted in the annual AAAS meeting as one of the breakthroughs published by Science. It is considered an advance in the field beyond what has been seen in the past three decades.
- First author paper on a new clustering paradigm accepted to SDM 2017.
- NSF-SBIR Grant Panelist, 2016-2017.
- Appeared in IBM Journal of Eminence, 2016.
- Paper published in KAIS Journal, 2016.
- ICDM paper was Best paper candidate, 2015.
- AAAI paper won Deployed Application Award, 2015.