Abhishek Tanpure — AI Researcher

I’m a Senior Applied Machine Learning Scientist and Researcher focused on LLMs, forecasting, and scalable ML systems, with experience spanning industry deployment and academic research. At StackAdapt, I build high-performance ML pipelines for ad optimization, attribution, and personalized targeting. My work combines representation learning, large-scale data engineering, and distributed training, delivering significant improvements in model efficiency, scalability, and campaign performance. Earlier, at Google Research and UCSD’s Rose-STL Lab, I helped develop MultiModalForecaster (MMF), a novel framework that fuses large language models with time series data. I worked on decoding strategies, GPU optimization, and evaluation across real-world datasets, contributing to research at the intersection of foundation models and forecasting. My academic background includes an M.S. in AI from UC San Diego and a B.Tech with Honors from IIT Bombay, where I built a strong foundation in machine learning, optimization, and systems. I’ve also taught and mentored students as a TA for courses in neural networks, computer vision, and algorithms. I’m particularly excited by problems involving: LLMs beyond text (forecasting, reasoning, constraints) Multimodal and time series learning Reinforcement learning for decision-making Scalable ML infrastructure and MLOps Always open to discussions around applied research, ML systems, and impactful AI.

Stackforce AI infers this person is a Machine Learning expert with a focus on research and scalable systems in the tech industry.

Location: San Diego, California, United States

Experience: 3 yrs 11 mos