Professional Experience

Specializing in the applications of search and generative AI. Designing solutions for information retrieval, retrieval-augmented generation (RAG), and data engineering workloads.

Partnering with enterprises seeking to deploy agentic RAG and deep document search over large knowledge bases, or scale search and recommendations.

Led search and recommendation initiatives at scale. Key contributions include:

• Led a team of 10+ engineers and researchers, shipping AI-enabled advances to search in first-party apps.
• Responsible to innovate, design, and ship search and recommendation systems for on-device and server search at scale using ranking models, NLP, and embeddings.
• Work highlighted in Apple WWDC as the “biggest update to search in years”.
• Collaborated cross-functionally with evaluation, QA, online measurement, and client teams.
• Managed and mentored engineers.

Led a research group that delivered breakthrough and foundational innovations in streaming algorithms, ML, graphs, and databases. Key accomplishments, honors, and awards include:

• 100+ publications in top-tier venues in ML, databases, and algorithms (KDD, NeurIPS, VLDB, ICDE, PODS, IEEE TKDE) with 3,700+ citations and an h-index of 34.
• Honored with the IBM Faculty Award, the Warren B. Boast Undergraduate Teaching Award, and named the Kingland Professor of Data Analytics.
• Co-authored papers invited to special journal issues for best papers from SPAA, IEEE IPDPS, SIAM Conference on Data Mining, ICDE, and Euro-Par.
• Designed and taught courses on software for big data and algorithms, including Software Tools for Large-Scale Data Analysis, Probabilistic Methods in Computer Engineering, Theoretical Foundations of Computer Engineering, and Operating Systems.
• Active in professional academic service, including steering committee and chair roles for ACM PODC, review board membership for VLDB, and program committee memberships for top-tier venues such as VLDB, ICDT, PODS, ICDE, CIKM, and IPDPS.
• Advised 12 Ph.D. graduates pursuing careers in academia and industry.
• Secured $6M+ sponsored funding from competitive sources (e.g. National Science Foundation, Industry, DARPA).
• Multiple patents on data stream processing and systems.

Designed and implemented parallel methods for databases, efficient cache management, and hashing.