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Shengze Wang 王晟泽

Second-year Computer Science Ph.D. Student @ UCSC

Computer Networks and Systems Researcher & Enthusiast

AI Infrastructure, Systems for AI, AI for Systems & DB

Brief Bio
Brief Bio

Hello! This is Shengze (William) Wang, a second-year Computer Science Ph.D. student at the Baskin School of Engineering, UC Santa Cruz. My research interests revolve around Computer Networks & Distributed Systems and their applications in AI Infrastructure (Systems for AI), AI for Systems & DB, Datacenter Networks, Edge Computing, and Connected Autonomous Vehicles.

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Education
2023 - Present
University of California, Santa Cruz (UCSC) - San Francisco Bay Area

Ph.D. in Computer Science & Engineering; Regents Fellowship; BE Dean's Fellowship

2020 - 2023
University of North Texas (UNT) - Dallas Fort Worth Metroplex

B.S. in Computer Science; GPA: 4.0, Top 1%; CSCE Outstanding Student (Top 1 of Class 2023); President’s List

2019
King's College London (KCL) - London

Visiting Student in Computer Science; Grade: 95/100

Experience
2023 - Present
Graduate Student Researcher
2022
Research Mentor
2021 - 2023
Research Assistant

PROFESSIONAL SERVICES

Selected Publications

S. Wang, Y. Liu, X. Zhang, L. Hu, and C. Qian, "Poster: Distributed Learned Hash Table," 2024 IEEE 32nd International Conference on Network Protocols (ICNP), Charleroi, Belgium [Accepted]

Y. Hua,  S. Wang, X. Zhang, D. Zhu, A. Cheong, K. Mohindroo, A. Dewey, and C. Qian,  "CALID: Collabrative Accelerate LLM Inference with Draft Model with Filter Decoding," BayLearn 2024 - Machine Learning Symposium, Cupertino, CA, USA [Accepted]

S. Huang, Q. Yan,  S. Wang, and I. Lane, "Improving the Faithfulness of LLM-based Summarization with Unlikelihood Training," BayLearn 2024 - Machine Learning Symposium, Cupertino, CA, USA [Accepted]

S. Tang, S. Wang (Co-first Author), S. Fu, and Q. Yang, "Perception Workload Characterization and Prediction on the Edges with Memory Contention for Connected Autonomous Vehicles," in 2023 IEEE International Conference on Edge Computing and Communications (EDGE), Chicago, IL, USA, 2023 pp. 104-114.
doi: 10.1109/EDGE60047.2023.00026 [pdf] [code] [slide]

S. Wang, S. Feng, C. Pan and X. Guo, "FineFDR: Fine-grained Taxonomy-specific False Discovery Rates Control in Metaproteomics," 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Las Vegas, NV, USA, 2022, pp. 287-292, doi: 10.1109/BIBM55620.2022.9995401. [pdf] [code] [slide]

TECHNICAL SKILLS

Languages & Databases: C/C++, Rust, Python, Bash, Coq, Redis, LevelDB, Cassandra, DynamoDB, Oracle, MySQL

Platforms & Tools: Linux, Network Operating Systems, ROS, Supercomputers (TACC), AWS, Azure, GCP, Docker, Git

Highlights: Applied AI for Systems, Query processing, Key-value Pair Storage, Advanced Network Protocols, Hashing Algorithms, Workload Characterization & Balancing, Network Security, ML System Design, LLM Inference, Vector Database, Programmable Switches, Content Delivery Network, Quantum Networks, Edge-Cloud Systems, Vehicle Computing

Teaching experience