LabCompass

Jinfeng Liao

Physics and Astronomy · Indiana University

OpenAlex ORCID
High-Energy Particle Collisions ResearchQuantum Chromodynamics and Particle InteractionsParticle physics theoretical and experimental studiesPulsars and Gravitational Waves ResearchCold Atom Physics and Bose-Einstein Condensates

Publications

183

Citations

6,459

Est. group size

—

Recurring co-author estimate

Active years

24

Publishing since 2002

Research summary
AI-generated

Jinfeng Liao studies the physics of matter under extreme conditions, focusing on the quark-gluon plasma produced when atomic nuclei collide at very high energies. Key topics include the chiral magnetic effect (how strong magnetic fields influence particle behavior in these collisions), the behavior of heavy quarks and exotic particles in this hot medium, and the structure of matter described by quantum chromodynamics (QCD), the theory of the strong nuclear force. Recent work also applies quantum computing methods to particle-physics calculations.

Heavy-ion collisions and quark-gluon plasmaChiral magnetic effectQCD phase structure and matter under extreme fieldsHeavy quarks and exotic hadronsQuantum computing for particle physics

Publication output was high in the late 2010s (peaking around 2021) and has slowed in recent years, averaging about 4-5 papers per year over the last five years.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 4.4/year recently
2017: 11 publications172018: 13 publications182019: 8 publications192020: 11 publications202021: 17 publications17212022: 8 publications222023: 4 publications232024: 6 publications242025: 4 publications2526
Recent publications
Publishes in
  • Nuclear Physics A×16
  • arXiv (Cornell University)×14
  • Physical Review C×10
  • Physical review. D/Physical review. D.×10
  • Physics Letters B×5

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

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