Starting September 2019, I am an Applied Research Scientist with
Dr. Alexander Anderson at the Integrated Mathematical Oncology Department, Moffitt Cancer Centre, Tampa, Florida.
Prior to that, I was a Postdoctoral Research Fellow with
Dr. Dana Pe'er at Memorial Sloan Kettering Cancer Centre, NYC and from October 2014, I was a Postdoctoral Research Scientist
at the same lab at the Department of Biological Sciences, Columbia University in the City of New York.
I received my Ph.D degree from Volker Roth's lab at the Department of Mathematics and Computer Science, University of Basel, Switzerland. My research deals with developing and applying statistical models, particularly to problems in Computational Biology. I work on clustering, network inference and sparsity selection models. I have an MSc degree in Intelligent Systems (Robotics) from University of Edinburgh, Scotland. My Master thesis was done at Subramanian Ramamoorthy's lab and was based on Knot theory.
Prior to academics, I have been an Assembler programmer working with the TCP/IP stack of the Mainframe Operating System (z/OS) at IBM Software Laboratories, Bangalore and have developed Mainframe applications at UST Global, Thiruvananthapuram.
I practise yoga and meditation and am also interested in Tae Bo, hiking and distance running. I have completed 4 out of 6 of the World Marathon Majors: the Tokyo Marathon (2019), the BMW Berlin Marathon (2018), Bank of America Chicago Marathon (2017), TCS NYC Marathon (2015, 2016), and multiple Half marathons.
Course tester and Senior TA for
Neuromatch Academy (July, 2020).
Mentor for the
MIT COVID-19 Datathon (May 10-16, 2020) for the Research
Track: Disparities in Health Outcomes from COVID-19.
Inaugural 2019 Depth First Learning Jane Street Fellow.
STEM Mentor for 1000 Girls, 1000 Futures by New York Academy of Sciences (NYAS) 2019.
- Journal/Conference/Workshop Reviewer
- 2021: ICML, ACM Conference on Health, Inference, and Learning (CHIL), ACL-IJCNLP, AISTATS, AAAI, ICLR,
FLAIRS-34 (Florida AI Research Society), PLOS Computational Biology, NeurIPS Reproducibility Challenge
- 2020: NeurIPS, PLOS Computational Biology, ML4H, ACL-IJCNLP, FLAIRS-33, ACM Conference on Health, Inference, and Learning (CHIL)
- 2019: NeurIPS, ICML, AISTATS, ICLR, IJCNN, SciPy, KDD, ML4H, CORE@Luxembourg National Research Fund,
IEEE/ACM Transactions on Computational Biology and Bioinformatics,
Pacific Symposium on Biocomputing (PSB), AAAI, Area Chair for WiML@NeurIPS, ML4Healthcare@NeurIPS, ML4Physical Sciences@NeurIPS, MLCB@NeurIPS, Bioinformatics Journal, NeurIPS Reproducibility Challenge
- 2018: NeurIPS, ICML, AISTATS, IJCNN, ICLR, Area Chair for WiML@NIPS, CORE@Luxembourg National Research Fund, IEEE/ACM Transactions on Computational Biology and Bioinformatics, ML4Healthcare@NeurIPS, BayesianNonParametrics@NeurIPS, Pediatric Research
- 2017: NIPS, ICML, AISTATS, IJCNN, MLDM, ML4Healthcare@NIPS
- 2016: NIPS, IJCAI
- Program Committee
STEM Mentor for 1000 Girls, 1000 Futures by New York Academy of Sciences (NYAS) 2017.
The RE•WORK AI in Healthcare & Pharma Summit (Panel Moderator for The Importance of Machine Learning in Diagnosing & Treating Cancer)
NIH Common Fund Human BioMolecular Atlas Program (HuBMAP) FISH-based imaging (March 2021)
Integrated Mathematical Oncology department seminar, Moffitt Cancer Center (February 2021)
normjam: New York Genome Center and
the Chan Zuckerberg Initiative's
Single-cell Normalisation Workshop and Jamboree, NYC,
Dataiku NYC Meetup (July 2019)
AI NEXTCon NYC (July 2019)
Integrated Mathematical Oncology Department, Moffitt Cancer Center, Tampa, Florida (June 2019)
Women in Data Science WiDS, Zurich (April 2019):
MLConf NYC (March 2019):
Bayesian Nonparametrics Workshop @ NeuRIPS (December 2018) (Spotlight)
Pilot Projects for a Human Cell Atlas East Coast Retreat (October 2018)
- 30th Anniversary AACR Special Conference Convergence: Artificial Intelligence, Big Data, and Prediction in Cancer
(October 2018) (Poster)
- NYC Machine Learning Meetup