Systems & Languages

Adobe Research works to empower developers with new techniques for productive development of efficient, cross-platform applications. We research programming language techniques, compiler technologies, and scalable systems.  Our scientists and engineers work on high performance domain-specific language compilers that make it easy to explore different optimization strategies across CPUs and GPUs on different platforms, and on new techniques based on program synthesis and program verification to assist programmers in developing correct, bug-free code.

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Shubham Agarwal

Research Associate

David Tompkins

Senior Principal Scientist and Lab Director, Research Engineering and Design Lab

Alex Reinking

Research Scientist/Engineer

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Cache-Craft: Managing Chunk-Caches for Efficient Retrieval-Augmented Generation

Agarwal, S., Sundaresan, S., Mitra, S., Mahapatra, D., Yu, T., Saini, S. (Jun. 22, 2025)

Special Interest Group on Management of Data (SIGMOD)

DiffServe: Efficiently Serving Text-to-Image Diffusion Models with Query-Aware Model Scaling

Ahmad, S., Yang, Q., Wang, H., Sitaraman, R., Guan, H. (May. 12, 2025)

The Annual Conference on Machine Learning and Systems (MLSys)

Thinking Forward: Memory-Efficient Federated Finetuning of Language Models

Panchal, K., Parikh, N., Choudhary, S., Zhang, L., Brun, Y., Guan, H. (Dec. 11, 2024)

The 38th Annual Conference on Neural Information Processing Systems (NeurIPS)

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Inside Halide, the open source language engineers use to make imaging tools faster

Halide is an open-source embedded programming language co-developed by Adobe Research and MIT to make imaging tools faster and more portable across devices. We spoke with five key contributors to learn how it continues to evolve and enable tools used by billions, from digital cameras to many of Adobe’s products!

Researcher Spotlight: Subrata Mitra uses machine learning to make big-data systems more efficient and reliable

We talked to Subrata Mitra, Senior Research Scientist with Adobe Research about how an early visit to a supercomputing center helped shaped his research interests, what it's like to use machine learning to make sense of massive amounts of data, and more. Check out the story!

Researcher Spotlight: Kanak Mahadik on machine learning for efficient large-scale systems

Research Scientist Kanak Mahadik uses machine learning so that large-scale systems—like Adobe’s cloud-based services—can use resources better. In this interview, Mahadik shared about her work and why Adobe Research is a great place to tackle big questions.
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