# Kaushal Paneri > Senior applied scientist at Microsoft, leading large-scale ML systems in auction and autobidding at Bing Ads. Work at the intersection of causal inference, reinforcement learning, and foundation models for large-scale recommender systems. Published at NeurIPS, AAAI, ACM RecSys. 16 peer-reviewed publications, 2 granted US patents. ## About Kaushal Paneri is a senior applied scientist at Microsoft, where he leads large-scale ML systems in auction and autobidding at Bing Ads. His work sits at the intersection of causal inference, reinforcement learning, and foundation models — figuring out how to safely improve systems that can only observe the consequences of their own past decisions. He completed his MS in Data Science (thesis track) at Northeastern University under Robert Ness, Jan-Willem van de Meent, and Olga Vitek, where his thesis on integrating Markov processes with structural causal models became a NeurIPS 2019 paper. He taught graduate machine learning (CS 6140) at Khoury College as a visiting lecturer from 2022–2024. Before Northeastern, he spent three years at TCS Research Lab in Delhi doing applied ML research and publishing in top-tier ML conferences, producing 7 publications and 2 US patents. ## Research Areas - Reinforcement learning and bandit algorithms for auction tuning and autobidding - Foundation models and world models for marketplace forecasting (Chronos) - Causal inference and counterfactual evaluation for recommender systems - Off-policy estimation in high-dimensional action spaces (SigIS method) - Structural causal models and Bayesian inference ## Pages - [Homepage](https://kaushal.us/): Bio, selected research, talks, teaching, writing - [Writing](https://kaushal.us/writing/): Short-form writing on causal ML, recommender systems, foundation models - [CV (HTML)](https://kaushal.us/cv/): Full curriculum vitae, web format - [CV (PDF)](https://kaushal.us/cv.pdf): Full curriculum vitae, PDF download ## Selected Publications - [Combining Open-box Simulation and Importance Sampling for Tuning Large-Scale Recommenders](https://arxiv.org/abs/2410.03697): CONSEQUENCES @ ACM RecSys 2024, oral presentation - [Adaptive Mixture Importance Sampling for Automated Ads Auction Tuning](https://arxiv.org/abs/2409.13655): CONSEQUENCES @ ACM RecSys 2024 - Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis: IEEE Transactions on Big Data, 7(1), 25–37, 2021 - [Integrating Markov Processes with Structural Causal Modeling Enables Counterfactual Inference in Complex Systems](https://proceedings.neurips.cc/paper/2019/hash/2d44e06a7038f2dd98f0f54c4be35e22-Abstract.html): NeurIPS 2019 - Regularizing Fully Convolutional Networks for Time Series Classification by Decorrelating Filters: AAAI 2019, 33(01) Total: 16 peer-reviewed publications, ~120+ citations (Google Scholar). ## Patents - System and Method for Visual Bayesian Data Fusion: US 10,430,417 (2019) - Multi-Sensor Visual Analytics: US 10,013,634 (2018, 8 patent citations) ## Teaching - DS 4400 — Machine Learning and Data Mining 1 (undergraduate) — Visiting Lecturer · Khoury College, Northeastern University, Spring 2023 - DS 5220 — Supervised Machine Learning and Learning Theory (graduate) — Visiting Lecturer · Khoury College, Northeastern University, Spring 2022 - DS 5220 — Supervised Machine Learning and Learning Theory (graduate) — Visiting Lecturer · Khoury College, Northeastern University, Fall 2021 ## Service - Program Committee Member, CONSEQUENCES 2025 @ ACM RecSys - Applied Scientist Interviewer, Microsoft (final-round certified, 2024–present) ## Selected Writing - [Hello, world](https://kaushal.us/writing/hello-world/): First post on the new site. Short note on what I plan to write about — causal inference, reinforcement learning, foundation models, and the occasional dispatch from teaching. ## Contact - Email: kaushalpaneri@gmail.com - Scholar: https://scholar.google.com/citations?user=jXsmTMQAAAAJ - Github: https://github.com/kaushalpaneri - Linkedin: https://www.linkedin.com/in/kaushalpaneri - Location: Boston, MA, US ## Optional - [RSS Feed](https://kaushal.us/feed.xml) - [Sitemap](https://kaushal.us/sitemap-index.xml) - [llms-full.txt](https://kaushal.us/llms-full.txt)