LabCompass

Fengguang Song

Computer Science · Indiana University

Mid career · publishing since 2004

Publications

90

Citations

696

Est. group size

~2

Recurring co-author estimate

Active years

23

Publishing since 2004

Research summary
AI-generated

Fengguang Song works in high-performance and parallel computing, with a strong focus on techniques for compressing large scientific datasets so they can be stored, moved, and processed more efficiently, often using GPUs and other specialized hardware. Recent projects also include workflow systems that coordinate computation across supercomputers and cloud resources, learned data structures for memory, and applying machine learning to large optimization problems. The work spans both foundational systems tools and applications such as water-science modeling and quantum circuit simulation.

Scientific data compression (lossy and lossless)Parallel and GPU computingDistributed and in-situ scientific workflowsHigh-performance data storage and memory systemsMachine learning for computing systems

Publication activity was higher in the late 2010s (around 8-11 per year), dipped in 2020-2022, and has since recovered to roughly 4-7 papers per year, indicating renewed but variable output.

Generated by claude-opus-4-8 from public bibliographic data · Jul 9, 2026

Funding
Public award records

Current awards run through September 2027 — about 1 year of funding on record from today. Awards are often renewed, so this is what is currently public, not a forecast.

  • ActiveNSF 2326495through Sep 2027 · $300k awarded

    Collaborative Research: SHF: Small: Reimagining Communication Bottlenecks in GNN Acceleration through Collaborative Locality Enhancement and Compression Co-Design

  • ActiveNSF 2311876through Jul 2027 · $580k awarded

    Collaborative Research: Frameworks: FZ: A fine-tunable cyberinfrastructure framework to streamline specialized lossy compression development

Matched to public NIH RePORTER and NSF records by name and institution. Awards from other agencies are not shown, and a match is not always found — this list may be incomplete.

In context
Among 848 mid career Computer Science PIs within our index
Citations: 696cohort median 432
h-index: 13cohort median 10
Publications / year (recent): 3.6cohort median 3.9

Typically publishes in teams of ~3 · 56% small-team papers (≤3 authors) · across 23 venues

Publication cadence
Publications per year over the last 10 years — averaging 3.6/year recently
2017: 10 publications172018: 11 publications11182019: 8 publications192020: 5 publications202021: 5 publications212022: 1 publication222023: 5 publications232024: 1 publication242025: 7 publications252026: 4 publications26
Collaborators per year
Distinct co-authors at Indiana University each year — a rough indication of whether the group around this researcher has been growing or contracting. An estimate from co-authorship, not a roster: collaborators are not necessarily lab members, and recent years can be under-counted while indexing catches up.
2017: 0 collaborators at the same institution2018: 0 collaborators at the same institution2019: 0 collaborators at the same institution2020: 0 collaborators at the same institution2021: 1 collaborator at the same institution2022: 0 collaborators at the same institution2023: 0 collaborators at the same institution2024: 0 collaborators at the same institution2025: 3 collaborators at the same institution1719212325
Recent publications
Publishes in
  • Author eBooks×8
  • Lecture notes in computer science×5
  • arXiv (Cornell University)×4
  • Future Generation Computer Systems×2
  • Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering×2
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Sep 1, 2026.

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