Hanqi Guo is a computer scientist and specializing in visualization, analysis, and machine learning for scientific data. He is an awardee of the DOE Early Career Research Program in 2022. He has received the best paper awards in IEEE VIS, IEEE PacificVis, and ChinaVis, premier conferences in the visualization research community. Please see my curriculum vitae for more details.

I am constantly seeking for outstanding persons for PhD students and PostDocs in my group. Candidates are encouraged to send CV, transcript(s), and statement of research interests to guo.2154 [at] osu [dot] edu.

Selected Awards

• Best Paper Awards, IEEE VIS (2026 and 2019), IEEE IPDPS (2025), IEEE PacificVis (2021), IEEE LDAV (2025)
• Best Paper Honarable Mentions, IEEE VIS (2022 and 2021), IEEE LDAV (2018)
• College of Engineering Lumley Research Award, The Ohio State University (2026)
• DOE Early Career Research Program (ECRP) (2022)
• Outstanding Postdoctoral Performance Award in Basic Research, Argonne National Laboratory, 2017

News

• 9/2026. The paper titled EXaCTz: Guaranteed Extremum Graph and Contour Tree Preservation for Distributed and GPU-Parallel Lossy Compression won the Best Paper Award in IEEE VIS 2026.
• 10/2025. The paper titled Lossy Parallel Visualization of Large-Scale Volume Data with Error-Bounded Image Compositing won the Best Paper Award in IEEE LDAV 2025.
• 5/2025. The paper titled Enabling Efficient Error-controlled Lossy Compression for Unstructured Scientific Data won the Best Paper Award in IEEE IPDPS 2025.
• 8/2023. Awarded by the NSF OAC on Collaborative Research: OAC Core: Topology-Aware Data Compression for Scientific Analysis and Visualization, in collaboration with Bei Wang Phillips (U. Utah) and Xin Liang (U. Kentucky)
• 7/2023. Awarded by the NSF CSSI Program for a $3.2M collaborative project together with University of Chicago, Indiana University, and University of Alabama at Birmingham

Recent Selected Publications

• Yuxiao Li, Xin Liang, Bei Wang, and Hanqi Guo
  Preserving Discrete Morse–Smale Complexes in Error-Bounded Lossy Compression
  IEEE Transactions on Visualization and Computer Graphics, 2026. (In Press)
  | DOI | arXiv |

• Congrong Ren, Robert Underwood, Sheng Di, Emrecan Kutay, Zarija Lukic, Aylin Yener, Franck Cappello, and Hanqi Guo
  FFCz: Fast Fourier Correction for Spectrum-Preserving Lossy Compression of Scientific Data
  In IPDPS '26: Proceedings of the 40th IEEE International Parallel and Distributed Processing Symposium, 2026. (Accepted)
  | DOI | arXiv |

• Yuxiao Li, Mingze Xia, Xin Liang, Bei Wang, Robert Underwood, Sheng Di, Hemant Sharma, Dishant Beniwal, Franck Cappello, and Hanqi Guo
  pMSz: A Distributed Parallel Algorithm for Correcting Morse-Smale Segmentations for Lossy Compression
  In IPDPS '26: Proceedings of the 40th IEEE International Parallel and Distributed Processing Symposium, 2026. (Accepted)
  | DOI | arXiv |

• Congrong Ren, Randy Michael Churchill, Albert Mollén, Robert Hager, Seung-Hoe Ku, Choong-Seock Chang, and Hanqi Guo
  Fast and Invertible Simplicial Approximation of Magnetic-Following Interpolation for Visualizing Fusion Plasma Simulation Data
  Computer Graphics Forum (Proc. EuroVis 2025), 44(3), Article e70120, 2025.
  | DOI | arXiv |

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