Draft:Zhilin Wang
Submission declined on 11 August 2026 by Theroadislong (talk).
Where to get help
How to improve a draft
You can also browse Wikipedia:Featured articles and Wikipedia:Good articles to find examples of Wikipedia's best writing on topics similar to your proposed article. Improving your odds of a speedy review To improve your odds of a faster review, tag your draft with relevant WikiProject tags using the button below. This will let reviewers know a new draft has been submitted in their area of interest. For instance, if you wrote about a female astronomer, you would want to add the Biography, Astronomy, and Women scientists tags. Editor resources
|  |
Zhilin Wang | |
|---|---|
| Education | Purdue University |
| Scientific career | |
| Fields | Federated learning; distributed systems; machine-learning security |
| Thesis | Towards Reliable Federated Learning: Decentralization and Fault Tolerance (2024) |
| Qin Hu | |
Zhilin Wang is a computer science researcher and technology entrepreneur whose research concerns federated learning, distributed computing, and machine-learning security. He is a co-founder and chief technology officer of Metix AI, a recruitment technology business formerly branded as OpenJobs AI.[1]
Education
[edit]Wang completed a Doctor of Philosophy degree in computer science at Purdue University. His dissertation, Towards Reliable Federated Learning: Decentralization and Fault Tolerance, was posted by the Purdue University Graduate School in December 2024. Qin Hu served as his dissertation advisor.[2]
An Indiana University Indianapolis directory listed Wang as a doctoral student advised by Hu and described his research areas as federated learning, edge computing, and the Internet of Things.[3]
Research
[edit]Wang's doctoral research examined the reliability of federated-learning systems. It included blockchain-based decentralization, incentive mechanisms and resource allocation, straggler mitigation in hierarchical systems, model-poisoning attacks, and defenses based on partial-parameter similarity.[2]
Wang was the first author of a study on incentive mechanisms for joint resource allocation in blockchain-based federated learning, published in IEEE Transactions on Parallel and Distributed Systems in 2023.[4] He also led work on resource optimization for blockchain-based federated learning in mobile edge computing, published in IEEE Internet of Things Journal.[5]
His research on federated-learning security includes a first-authored survey of defenses against model-poisoning attacks,[6] and a later study of vulnerabilities in similarity-based model evaluation, published in IEEE Transactions on Information Forensics and Security in 2025.[7] He also co-authored work combining blockchain and federated edge learning for privacy-preserving mobile crowdsensing.[8]
Entrepreneurship
[edit]Wang co-founded OpenJobs AI and became the company's chief technology officer. The business adopted the Metix AI brand in 2026 while retaining OpenJobs AI Inc. as its legal entity.[1][9] The company's biography of Wang describes his work as including multi-agent language-model systems and semantic search for recruiting applications.[1]
In May 2025, the YouTube channel TwoSetAI published an interview with an OpenJobs AI chief technology officer identified in the programme as Jerry Wang. The discussion concerned artificial intelligence, engineering roles, recruiting, compensation trends, and entrepreneurship.[10]
Selected publications
[edit]- Wang, Zhilin; Hu, Qin; Li, Ruinian; Xu, Minghui; Xiong, Zehui (2023). "Incentive Mechanism Design for Joint Resource Allocation in Blockchain-Based Federated Learning". IEEE Transactions on Parallel and Distributed Systems. 34 (5): 1536–1547.[4]
- Wang, Zhilin; Hu, Qin; Xiong, Zehui; Liu, Y.; Niyato, Dusit (2024). "Resource Optimization for Blockchain-Based Federated Learning in Mobile Edge Computing". IEEE Internet of Things Journal. 11 (9): 15166–15178.[5]
- Wang, Zhilin; Kang, Qiao; Zhang, Xinyi; Hu, Qin (2022). "Defense Strategies Toward Model Poisoning Attacks in Federated Learning: A Survey". IEEE Wireless Communications and Networking Conference: 548–553.[6]
- Wang, Zhilin; Hu, Qin; Zou, Xukai; Hu, Pengfei; Cheng, Xiuzhen (2025). "Can We Trust the Similarity Measurement in Federated Learning?". IEEE Transactions on Information Forensics and Security. 20: 3758–3771.[7]
References
[edit]- 1 2 3 "Zhilin Wang". Metix AI. Retrieved 11 August 2026.
- 1 2 Wang, Zhilin (4 December 2024). Towards Reliable Federated Learning: Decentralization and Fault Tolerance. Computer Science (PhD thesis). Purdue University Graduate School. doi:10.25394/PGS.27961677.v1.
- ↑ "Zhilin Wang". School of Science, Indiana University Indianapolis. Retrieved 11 August 2026.
- 1 2 Wang, Zhilin; Hu, Qin; Li, Ruinian; Xu, Minghui; Xiong, Zehui (2023). "Incentive Mechanism Design for Joint Resource Allocation in Blockchain-Based Federated Learning". IEEE Transactions on Parallel and Distributed Systems. 34 (5): 1536–1547. doi:10.1109/TPDS.2023.3253604.
- 1 2 Wang, Zhilin; Hu, Qin; Xiong, Zehui; Liu, Yuan; Niyato, Dusit (2024). "Resource Optimization for Blockchain-Based Federated Learning in Mobile Edge Computing". IEEE Internet of Things Journal. 11 (9): 15166–15178. doi:10.1109/JIOT.2023.3347524.
- 1 2 Wang, Zhilin; Kang, Qiao; Zhang, Xinyi; Hu, Qin (2022). "Defense Strategies Toward Model Poisoning Attacks in Federated Learning: A Survey". 2022 IEEE Wireless Communications and Networking Conference (WCNC). pp. 548–553. doi:10.1109/WCNC51071.2022.9771619.
- 1 2 Wang, Zhilin; Hu, Qin; Zou, Xukai; Hu, Pengfei; Cheng, Xiuzhen (2025). "Can We Trust the Similarity Measurement in Federated Learning?". IEEE Transactions on Information Forensics and Security. 20: 3758–3771. doi:10.1109/TIFS.2024.3516567.
- ↑ Hu, Qin; Wang, Zhilin; Xu, Minghui; Cheng, Xiuzhen (2023). "Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing". IEEE Internet of Things Journal. 10 (14): 12000–12011. doi:10.1109/JIOT.2021.3128155.
- ↑ Fu, Kin (7 July 2026). "We raised $5.5M, and we're now Metix AI". Metix AI. Retrieved 11 August 2026.
- ↑ Jerry Wang (8 May 2025). AI Will STEAL Your Job by 2028? | Jerry Wang @OpenJobsAI (Video). TwoSetAI. Retrieved 11 August 2026.
- provide significant coverage: discuss the person in detail, not brief mentions or interviews lacking independent analysis;
- are reliable: from reputable outlets with editorial oversight;
- are independent: not connected to the person, such as interviews, press releases, the subject's own website, or sponsored content.
Please add references that meet all three of these criteria. If none exist, the subject is not yet suitable for Wikipedia.