Since May 2020, I’m an Applied Scientist at Amazon. I help innovate, develop, evaluate, and launch deep-learned models to fuel next-generation Amazon Search, with a focus on improving search quality in new and emerging locales.
I received my Ph.D. in Computer Science from Carnegie Mellon University, where I was advised by Prof. Christos Faloutsos and supported partially by the Snap Graduate Fellowship. My thesis focused on anomaly detection and semi-supervised learning in graphs. Prior to that, I received my B.Tech. (Hons.) in Computer Science and Engineering from Indian Institute of Technology Madras in 2015.
Outside of work, I like to run, play board games, solve puzzles, read, and travel. I am also learning kathak, a North Indian classical dance. I can be bribed with a good chai tea latte, some spicy biriyani, and a basundhi.
My CV is here.
On How People Navigate Through Their Personal Web of Things
Dhivya Eswaran, Shamsi Iqbal, Adam Fourney, Shane Williams, Paul Bennett
CHI 2020 Workshop on Speculative Designs for Emergent Personal Data Trails [paper]
ChangeDAR: Online Localized Change Detection for Sensor Data on a Graph
Bryan Hooi, Leman Akoglu, Dhivya Eswaran, Amritanshu Pandey, Marko Jereminov, Larry Pileggi, Christos Faloutsos
CIKM 2018 [paper]
GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid
Bryan Hooi, Dhivya Eswaran, Hyun Ah Song, Amritanshu Pandey, Marko Jereminov, Larry Pileggi, Christos Faloutsos
ECML/PKDD 2018 [paper] [code]
Why You Should Charge Your Friends for Borrowing Your Stuff
Kijung Shin, Euiwoong Lee, Dhivya Eswaran, Ariel D. Procaccia
IJCAI 2017 [paper]
Modeling Website Topic Cohesion at Scale to Improve Webpage Classification
Dhivya Eswaran, Paul N. Bennett, Joseph J. Pfeiffer III
SIGIR 2015 [paper]
Towards Creating Pedagogic Views from Encyclopedic Resources
Ditty Mathew, Dhivya Eswaran, Sutanu Chakraborti
NAACL 2015 Workshop on Innovative Use of NLP for Building Educational Applications [paper]