About

Bogdan Nicolae
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Welcome to my web page! I’m a Computer Scientist at Argonne National Laboratory. My research interests are broadly around scalable storage, data management and resilience at the intersection of high performance computing, big data analytics and machine learning. Specifically, I focus on areas such as checkpoint-restart, state capture and migration, caching and prefetching, data and metadata decentralization and high availability, concurrency control in data management, multi-versioning and provenance, memoization and reuse, declarative data models, etc. Much of my research is applied to artificial intelligence to improve the accuracy, performance and scalability of pre-training, inference serving and agentic AI workloads (data pipelines, data/model parallelism, KV caching, batching and scheduling, provenance and explainability, reasoning strategies, agentic memory, etc.)

In addition to my main position, I hold a Research Professor appointment at the Illinois Institute of Technology (IIT) and a Scientist-at-Large appointment at the University of Chicago, within the Consortium for Advanced Science and Engineering (UChicago CASE). I am a Distinguished Member of ACM and a Senior Member of IEEE.

I am a recipient of U.S. Department of Energy 2020 Early Career Research Program Award. My PhD Thesis won the 2nd 2011 Gilles Kahn Award.

Short bio

Bogdan Nicolae is a Computer Scientist with Argonne National Laboratory (Chicago, USA) and Research Professor at Illinois Institute of Technology (Chicago, USA). He specializes in scalable storage, data management and fault tolerance for large scale distributed systems, in particular at the intersection of high performance computing, and artificial intelligence. He is interested by and authored numerous papers in areas such as checkpoint-restart, caching and prefetching, scalable memoization and reuse, data and metadata decentralization and high availability, multi-versioning and provenance. Much of his research is applied to artifical intelligence to improve the accuracy, performance and scalability of pre-training, fine-tuning, inference serving and agentic workloads. He is a regular PC memeber and participates in the organization of major international conferences around parallel and distributed systems as well as AI: SC, IPDPS, HPDC, CCGrid, CLUSTER, ICS, HIPC, EACL, EMNLP, etc. He is a regular reviewer for journals such as: TPDS, JPDC, FGCS, PARCO, TC, TCC, IJHPCA.

Areas of interest