Yang Zhang
Scholar

Yang Zhang

Google Scholar ID: egeD-DMAAAAJ
Assistant Professor, Miami University
Human-AI CollaborationGenerative AILarge Language Model
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Citations & Impact
All-time
Citations
1,792
 
H-index
24
 
i10-index
57
 
Publications
20
 
Co-authors
0
 
Contact
Emailzhang981@miamioh.eduCVOpen ↗GitHubOpen ↗LinkedInOpen ↗
Publications
1 items
Mitigating Artifacts in Pre-quantization Based Scientific Data Compressors with Quantization-aware Interpolation
2026
Cited
0
Resume (English only)
Academic Achievements
  • [2025] NSF OAC Core Award, National Science Foundation; [2023, 2024, 2025] Teachers Ranked as Excellent, University of Illinois; [2022] Best Paper Award, ACM/IEEE ASONAM; [2022] Best Paper Honorable Mention, IEEE SMARTCOMP; [2021] Outstanding Graduate Research Assistant Award, University of Notre Dame; [2021] Video Presentation Award, ACM/IEEE IWQoS; [2020] W. J. Cody Associate Award, Argonne National Laboratory; [2018, 2019] Conference Travel Award, IEEE; [2015] Data Science Scholar Fellowship, Indiana University.
Research Experience
  • Currently an Assistant Professor in the Department of Computer Science and Software Engineering at Miami University; Previously a Teaching Assistant Professor at the University of Illinois Urbana-Champaign (UIUC); Also worked as a Postdoctoral Research Associate at UIUC and a W. J. Cody Research Associate at Argonne National Laboratory.
Education
  • Ph.D. in Computer Science and Engineering from the University of Notre Dame.
Background
  • Research Interests: Human-Generative AI/LLM Alignment, Designing interactive neural and hyperparameter search frameworks, Enabling bidirectional learning between humans and AI systems, Generative AI/LLM Modeling, Enhancing model learning under sparse and limited data, Integrating multimodal inputs for unified generative understanding, Ensuring robustness, fairness, and trust across domains, Quantum-GPU Hybrid Design, Integrating quantum processors with GPU-based deep learning, Developing scalable quantum-classical hybrid architectures, Mitigating noise, decoherence, and interoperability issues.
Miscellany
  • We currently have openings for Ph.D. students in Computer Science and also welcome undergraduate and master’s students interested in participating in our ongoing research through independent study or guided research projects.
Co-authors
0 total
Co-authors: 0 (list not available)