CV
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Education
- Ph.D. in Computer Science, Old Dominion University, Sept 2024 – present
- Advanced to candidacy; written and oral comprehensive examinations passed
- GPA 4.00/4.00
- Research focus: AI for physics — machine learning methods for scientific inference
- M.S. in Computer Technology, Northeast Normal University, 2021 – 2024
- Thesis: Machine Learning Applications in Combinatorial Optimization
- B.S. in Computer Science, Fujian University of Technology, 2016 – 2020
Graduate coursework in computer science
31 graduate semester hours earned under the CS prefix at Old Dominion University, at a 4.0 GPA:
| Course | Title | Credits | Grade |
|---|
| CS 800 | Research Methods | 3 | A |
| CS 833 | Natural Language Processing | 3 | A |
| CS 872 | Advanced Computer & Network Security | 3 | A |
| CS 895 | Topics: Pattern Recognition & Analysis | 3 | A |
| CS 895 | Topics: Practical Machine Learning & Applications | 3 | A |
| CS 898 | Doctoral Research | 9 | Pass |
| CS 899 | Doctoral Dissertation | 7 | Pass |
| | Total | 31 | |
15 hours are graded 800-level didactic coursework; 16 are doctoral research and dissertation. A further 3 hours of CS 899 are in progress.
Teaching experience
- CS 471 — Operating Systems, Teaching Assistant, Fall 2024
- Supported 40+ students through process management, memory allocation, and concurrency
- Designed and graded assignments on system calls and synchronization; ran weekly problem sessions
- CS 312 — Internet Concepts, Teaching Assistant, Spring 2025
- HTML5, CSS3, JavaScript, responsive web design; built hands-on exercises used across the section
- CS 270 — Computer Architecture, Guest Lecturer, Spring 2025
Instructional training and service
- Graduate Teaching Assistant Instructors’ Institute, Old Dominion University — Fall 2025
- Mathematics Tutor, ForKids, Inc. — 2025 to present
Research experience
- Graduate Research Assistant, Old Dominion University, Sept 2024 – present
- Doctoral research in AI for physics
- Algorithm Engineer, Intern, SmartAHC, Shanghai, Mar – July 2020
- YOLOv3-based CNN models for real-time detection, deployed to Android with Keras
Publications
Jitao Xu, H. Jang, Z. Panjsheeri, G. W. Chern, Y. Li, S. Liuti, D. Adams, et al. (2026). "Neural Network Representation of Generalized Parton Distributions (NNGPD)." arXiv preprint arXiv:2605.06994.
Jitao Xu, C. Cocuzza, K. Braga, D. Lersch, N. Sato, Y. Li. (2026). "Learning Transverse Momentum Distributions from Raw Scattering Events via Conditional Diffusion." Conference on Physics and AI (PAI26).
Jitao Xu, N. Sato, Y. Li. (2026). "Active Diffusion-Based Inference for Ill-Posed Inverse Problems Under Incomplete Priors." Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2026), Main Track.
T. Alghamdi, Jitao Xu, N. Ramachandra, N. Sato, Y. Li. (2025). "Towards an Event-Level Analysis in Hadronic Physics Using Generative AI-Based Surrogates." 2025 IEEE 37th International Conference on Tools with Artificial Intelligence (ICTAI).
Jitao Xu, Y. Wu, H. Li, M. Yin. (2025). "Prediction-Based Adaptive Variable Ordering Heuristics for Constraint Satisfaction Problems." Proceedings of the AAAI Conference on Artificial Intelligence, 39(11), 11390.
Jitao Xu, H. Li, M. Yin. (2024). "Finding and Exploring Promising Search Space for the 0-1 Multidimensional Knapsack Problem." Applied Soft Computing, 164, 111934.
Skills
- Languages: Python, C/C++, JavaScript, HTML/CSS
- Frameworks: PyTorch, TensorFlow/Keras, scikit-learn, OpenCV
- Tools: Linux, Git, LaTeX, Jupyter, MATLAB
- Instructional platforms: Canvas, Blackboard, Zoom, Microsoft Teams