I am a Data Scientist at Microsoft, where I leverage my expertise to unravel the causal impact of features on end users’ experiences. My work in the Experimentation For Windows (EFW) team focuses on Causal Discovery, a sophisticated blend of statistics and machine learning that uncovers cause-and-effect relationships from observational data. Previously as a Data & Applied Scientist at Microsoft BingAds, I developed machine learning pipelines for the detection, rejection and removal of adversarial attacks on multi-media advertising such as Product and Text Ads that violates Microsoft's Editorial Policies or poses risks from Fraud, Account Compromise and Spoofing.
Academic Research : As a Gruaduate Research Assistant with Prof. Joseph Makin, I developed machine learning models to infer neural population dynamics in multi-unit cortical recordings from macaques performing motor-control tasks. I also explored Speech Decoding using machine learning from Electrocorticography (ECoG) Cortical Activity in humans.
Teaching : As a Graduate Teaching Assistant at Purdue, I guided students through the intricacies of Python programming in practical lab sessions.
M.S. in Electrical & Computer Engineering
Purdue University, West Lafayette
B.Tech in Electrical Engineering (Minor in Data Science)
Indian Institute of Technology, Madras
AISSCE, CBSE (XII)
Chinmaya Vidyalaya, Vaduhala
AISEE, CBSE (X)
Talent Public School, Njarakkal
TA for CNIT 15501 Introduction to Software Development.
Responsibilities include:
Built frameworks for the detection of Editorial Policy violations and risks in Product and Text Ads.
Responsibilities include: