* Ads backend* Efficient information retrieval* Experimentation frameworks* App ads ML (supervised and semi supervised learning)

Machine Learning and Data Science for Azure Compute.* Ranking algorithms (Information retrieval), supervised learning, contextual online learning (bandits)* Natural language processing (NLP)* Engineering (MLOps, data engineering)* Statistics, Data Science

I was a postdoctoral associate at the MIT Institute for Data, Systems, and Society (IDSS).* I contributed to hypothesis testing frameworks for understanding the skill involved (or lack thereof) in online Fantasy Sports games. * I was involved in developing courses for the MIT IDSS Micromasters program in statistics and data science. * Mentors: Karene Chu and Devavrat Shah* Check out the Micromasters program in data science: https://micromasters.mit.edu/ds/

* I was a teaching assistant for 9 electrical and computer engineering courses during my time at UCLA. This experience of learning by teaching gave me a strong grasp of fundamentals of probability, statistical methods, linear algebra, information theory, and communication systems.

Graduate Student Researcher in the Communication Systems Laboratory, Department of Electrical Engineering.* I contributed to the development of low-latency error-correction codes for modern communication systems (for example, 5G). My work spanned the mathematical areas of combinatorics, graph theory, integer programming, and non-convex optimization. * Awarded the 2015 IEEE Communication Theory Workshop's Best Poster Award. * I also was an active leader in the graduate student life and I mentored several undergraduate students. * For my teaching, I was elevated to the role of Teaching Fellow. * Advisor and Principal Investigator: Prof. Richard Wesel.* Co-advisor: Prof. Darius Divsalar, JPL and UCLA

* Mentor: Bazhong (BZ) Shen* During this internship, I explored spatially-coupled low-density parity-check coding solutions for real wireless applications.

* Mentor: Bazhong (BZ) Shen

* Analyzed Acoustic Resonance NDT using SonicTC. * I learnt how defects in industrial parts can be detected by training a simple classifier using spectrum emitted by the parts.