Dinesh Ramasamy Email & Phone Number

Menlo Park, Ca, Us

Ads Ranking

Bangalore, Karnataka, In

0 -> 1 ML for the short video platform Josh- Bootstrapped and maintained model training infrastructure- Transformer models: Retrieval (two-tower); Ranking (Multitask); LLM-like models for long content history based user models (Pinnerformer-like); Neural blending & diversification, etc- Vision-language models (BLIP2-like)

San Francisco, California, Us

Machine Learning- Lead for collaboration between Uber AI and Uber EATS organizations: E2E Recommendation system for UberEATS including Transformer architectures for ranking, Two Tower Embeddings (TTE) training framework, Graph Candidate Generation algorithms like PPR, etc - Led projects at the intersection of ML Infra and ML algorithms for UberAI (Michelangelo)Algorithms- Novel vector search algorithm in Lucene using LSH (SimHash) and the TMOR operator (WAND query)- Performant geospatial embedding JAVA library using s2 cells and random projections (ETAs)- Novel map matching architecture using Kalman filters that vastly improved the state of the art at Uber (JAVA Backend) - Part of team responsible for developing and maintaining a JAVA sensor fusion library for location improvement on Android

Seattle, Wa, Us

Modeling lead for maintaining a vertical of language understanding models for Alexa (from incubation to launch) and also worked on search and entity resolution

Santa Barbara, Ca, Us

- Performant word and graph embeddings using SVDs (published in NeurIPS '15) -- FastEmbed- Inference from time on Twitter: Proposed and evaluated a system for understanding the temporal evolution of topics on Twitter and for quantifying a user's interest in a topic from his/her tweet times. Investigated the value of user overlap for understanding the flow of topics with time on Twitter feeds.- Evaluated channel estimation and tracking algorithms for beamforming and tracking with compressive measurements / random projections. Gave a simple characterization of the design space made available by random projections using estimation theoretic / statistical bounds- Teaching assistant

San Diego, Ca, Us

Proposed algorithms and conducted simulations

West Lafayette, In, Us

Implemented computer vision algorithms (medical imagery)

Doctor Of Philosophy (Ph.D.), Signal Processing And Machine Learning

Master’S Degree

Bachelor’S Degree, Electrical Engineering