Yuhao Zhong (钟毓豪)
Ph.D. Candidate, advised by Prof. Satish Bukkapatnam
Wm Michael Barnes '64 Department of Industrial and Systems Engineering
Texas A&M University
[hirobin_zhong at tamu.edu] [CV] [Google Scholar] [Linkedin]
My research focuses on advancing Data Science methodologies to address fundamental challenges related to quality, safety, and performance assurance, as well as knowledge discovery, primarily in Manufacturing processes and systems in the context of Industry 4.0/5.0. I am currently on the job market!
Current Research Areas
- Advancement of explainable AI and generative AI methods
- Process-structure-property (PSP) knowledge discovery and uncertainty quantification
- Anomaly detection and localization
- Human-centric autonomous robotic control and monitoring
Awards
- U.S. Senator Phil Gramm Doctoral Fellowship, 2024
- Fox Graduate Fellowship, 2024
- Texas A&M Institute of Data Science (TAMIDS) Student Ambassador Scholarship, 2023 & 2024
- Winner, IISE Data Analytics & Information Systems (DAIS) Student Best Paper Contest, 2023
Latest News
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INFORMS TAMU Student Chapter has once again won the highest distinction, Summa Cum Laude! - October, 2024
As Vice President of the INFORMS TAMU Student Chapter, I am proud to announce...
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Welcome to my session TA26 at the 2024 INFORMS Annual Meeting! - October, 2024
Time & Location: Tuesday, October 22nd, from 8:00 AM to 9:15 AM in Summit 346
Selected Papers
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EBLIME: Enhanced Bayesian Local Interpretable Model-agnostic Explanations
Authors: Yuhao Zhong, Anirban Bhattacharya, Satish Bukkapatnam
In: arxiv preprint, 2024
TLDR: A Bayesian regularized approach to locally explain black-box model and quantify the explanation uncertainty more accurately. It can also be applied to defect segmentation and knowledge discovery.
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Detecting Anomalous Robot Motion in Collaborative Robotic Manufacturing Systems
Authors: Yuhao Zhong, Yalun Wen, Sarah Hopko, Adithyaa Karthikeyan, Prabhakar Pagilla, Ranjana K. Mehta, and Satish T.S. Bukkapatnam
In: IEEE Internet of Things Journal, 2024
TLDR: External IoT surveillance cameras combined with marker pose estimation and LSTM to track fast-moving robot and detect anomalous robot motion based on risks in human-robot collaborative industrial environment.
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Identifying the Influence of Surface Texture Waveforms on Colors of Polished Surfaces using an Explainable AI Approach
Authors: Yuhao Zhong, Akash Tiwari, Hitomi Yamaguchi, Akhlesh Lakhtakia, Satish T.S. Bukkapatnam
In: IISE Transactions, 2023
TLDR: Consolidating LIME local explanations into consistent global knowledge using a query-by-expert algorithm. We identified the influence of surface morphology on the colors exhibited by stainless steel 304 parts polished through the Magnetic Abrasive Finishing (MAF) process. This discovered physical knowledge was validated through confirmatory experiments and blind tests.