Zihao Zhou
Machine Learning PhD Student
Research interests
Deep generative models, Spatiotemporal modeling
Foundation Models, Multimodality, Anomaly Detection
Education
Sep 2022 - Now (Expected: Summer 2026)
University of California, San Diego
- PhD candidate in Computer Science
- Advisor: Rose Yu
Sep 2020 - Mar 2022
University of California, San Diego
- MS in Computer Science
- GPA: 4.0
- Advisor: Rose Yu
Aug 2016 - Jun 2020
University of California, San Diego
- BS in Applied Math
- BS in Cognitive Science Spec. in Machine Learning
- Minor in Computer Science.
- Magna Cum Laude
- GPA: 3.941 / 4.0, Major GPA: 4.0
Publications
[1] Zhou, Z. & Yu. R., Automatic Integration for Spatiotemporal Neural Point Processes., Neural Information Processing Systems (NeurIPS), 2023
[2] Zhou, Z. & Yu, R., Automatic Integration for Fast and Interpretable Neural Point Processes., Learning for Dynamics and Control (L4DC), 2023
[3] Zhou, Z., Yang, X., He, X., Rossi, R., Zhao, H., & Yu, R., Neural Point Process for Learning Spatiotemporal Event Dynamics., Learning for Dynamics and Control (L4DC), 2022
[4] Zhou, Z., Yu, R., Can LLMs Understand Time Series Anomalies?, The International Conference on Learning Representations (ICLR), 2025
[5] Li, A.*, Zhou, Z.*, Jortberg, E. & Yu, R., Generalization of Deep Sequence Models for Forecasting Aortic Pressure Cross Cohort., Computing in Cardiology (CinC), 2022 (* equal contribution)
[6] Zhang, H., Zhou, Z., Orso, P., Pham, D., Montenegro, H., … & Caso, J. Triton RCSC 2021 Team Description Paper., Robocup Small Size League (RCSSL), 2021
[7] Sun, S., Chen, W., Zhou, Z., Jortberg, E. & Yu, R., Data-Driven Simulator for Mechanical Circulatory Support with Domain Adversarial Neural Process, Learning for Dynamics and Control (L4DC), 2024
[8] Duan, M., Qian, Y., Zhao, L., Zhou, Z., Rasheed, Z., Shafique, K., Back to Bayesics: Uncovering Human Mobility Distributions and Anomalies with an Integrated Statistical and Deep Learning Framework, 1st ACM SIGSPATIAL International Workshop on GeoSpatial Anomaly Detection (GeoAnomalies), 2024
[9] Stanford, C., Adari, S., Liao, X., He, Y., Jiang, Q., Kuai, C., Ma, J., Tung, E., Qian, Y., Zhao, L., Zhou, Z., Rasheed, Z., Shafique, K., NUMOSIM: A Synthetic Mobility Dataset with Anomaly Detection Benchmarks, 1st ACM SIGSPATIAL International Workshop on GeoSpatial Anomaly Detection (GeoAnomalies), 2024
[10] Kai, K., Tsai, Z., Zhou, Z., Yu, R., The TimeText Corpus and Multi-Modal Forecaster: a Dataset and Model for Jointly Predicting Time Series and Textual Data, arXiv, 2024
[11] Zhou, L., Yashwante, P., Fisher, M., Sampieri, A., Zhou, Z., Galasso, F., Yu, R., CaTS-Bench: Can Language Models Describe Time Series?, Findings of the Association for Computational Linguistics: ACL 2026, 2026
[12] Cao, Y., Lai, S., Huang, J., Zhang, Y., Lawrence, Z., Bhakta, R., Thomas, I.F., Cao, M., Tsai, C.-H., Zhou, Z., Zhao, Y., Liu, H., Marinoni, A., Arefiev, A., Yu, R., SimulCost: A Cost-Aware Benchmark and Toolkit for Automating Physics Simulations with LLMs, International Conference on Machine Learning (ICML), 2026
[13] (Pending) Zhou, Z., Wen, H., Yu, R., STEventsBench: A Comprehensive Benchmark for
Spatiotemporal Event Anomaly Detection
Professional Experience
Jun 2026 - Present
Co-Founder & CTO, GistFlow
• Co-founding CTO of GistFlow, an AI foresight agent platform that turns fragmented supply chain data into forecasts, research, and actionable decisions through natural language.
• Built the full-stack product from scratch, including multi-agent AI orchestration, interactive 3D globe visualization, and production infrastructure; leading engineering, hiring, and technical strategy.
Jun 2025 - Sep 2025
Apple Software Engineer Intern, Machine Learning
• Developed patent-pending Entity Schema architecture for spatiotemporal LLM agentic memory, improving personal video recall from SOTA’s 60% -> 97%
• Built dual-database system integrating graph structures with vector embeddings for real-time spatiotemporal relationship modeling across personal media assets
• Optimized spatiotemporal query latency by 90% through LLM switching and streaming architecture for Apple Photos’ on-device personalization features
Jun 2024 - Sep 2024
Machine Learning Scientist Intern, Novateur Research Solutions
• Led the development of the deep learning model for HAYSTAC project under the IARPA program, focusing on human mobility patterns.
• My work resulted in a 30% -> 66% AUPRC improvement of the deep learning model for detecting anomalies with no extra computational cost.
• Secured the highest agent accuracy score on detecting synthetic human mobility segments among five competing companies.
Jun 2019 - Aug 2019
ML Research Engineer Intern, Mininglamp Tech. Gr.
• Surveyed the current state of the art of deep temporal point process, with an emphasis on modeling dynamic knowledge graph
• Filed a patent on user identity linkage system from heterogeneous trajectories using a new trajectory similarity measure
Open Source Contributions
• Gemini-OpenAI-Proxy multimodal support
• vLLM ARM build
• Sakura-LLM calibration and quantization
Skills
Leading System Administrator & System Integrator
UCSD CSE Shared Servers Admin, Rose Lab Server Admin
• Hosted the lab LLM deployment frontend and backend, with lab wiki RAG
• Assessed and optimized the performance of the Nautilus Kubernetes cluster
• Authored the Nautilus User Guide
• Led end-to-end procurement and deployment for CSE shared, Roselab and SDSC share of Nautilus servers, including quote solicitation, configuration comparison, equipment purchasing, server installation, and software setup & maintenance
Software Engineer
Docker, Kubernetes, Ubuntu, Arch Linux & RHEL derivatives (CentOS, AlmaLinux), Git, PyCharm, Pytorch Lightning, Huggingface, IntelliJ, Amazon EC2, Amazon S3, MinIO
Coding
Python, Java, MatLab, C/C++, R, Go, VueJS
Media
NodeJS, Photoshop, Illustrator, Vegas, Final Cut Pro
Awards / Honors
Sep 2019 - Jul 2021
Robocup SSL Team TritonsRCSC Software Team Leader
TritonsRCSC homepage | Github codebase | Poster
· TritonRCSC is the first UCSD team that receives qualification for competing in the RoboCup Small Size League
· Designed the team software architecture (Java/C++ socket-based) and coordinated the development [4]
· Implemented the robot’s path search, obstacle avoidance, motion prediction and ball passing algorithms
Jun 2020 - Present
Phi Beta Kappa Honor Society Membership
Jun 2019 - Aug 2019
China National Smart Weather Service
Innovation Competition, 2nd Prize
Sep 2016 - Jun 2020
UCSD Provost Honor
Teaching Experience
Sep 2021 - Dec 2021
Teaching Assistant
Principles of Artificial Intelligence, CSE 250A, UCSD
Sep 2019 - Dec 2019
Instructional Assistant
Intro to Machine Learning II, COGS 118B, UCSD
Last updated: Jul 2026