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Optimizing Data-Driven Federated Learning in UAV Networks

https://cis-linux1.temple.edu/~jiewu/research/publications/Publication_files/ICPADS2024.pdf

Abstract—Federated Learning (FL) is an emerging privacy-preserving distributed machine learning paradigm that enables numerous clients to collaboratively train a global model without transmitting private datasets to the FL server. Unlike most existing research, this paper introduces a Data-Driven FL system in Unmanned Aerial Vehicle (UAV) networks, named DDFL, which features an innovative ...

Kanghyun (Simon) Cho - Fox School of Business

https://www.fox.temple.edu/directory/kanghyun-simon-cho

Kanghyun (Simon) Cho is a Ph.D. candidate in Management Information Systems at Temple University. His research explores how artificial intelligence (AI) shapes expert decision-making in high-stakes domains such as healthcare and financial markets, with particular attention to the tension between algorithmic automation and augmentation.

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Temple University

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Microsoft Word - CV_Jian Sun.docx

https://www.fox.temple.edu/sites/fox/files/media/file/cv_Jian-Sun.pdf

JIAN SUN 70 Central Ave, Franklin Park, NJ, 08823 (T) 517-897-2220 (E) sunjian0422@gmail.com

Home - AI Tools for Research - Temple University

https://guides.temple.edu/ai-research-tools

This guide offers advice on AI-powered tools and functionality created for or used in academic research.

Kenneth Korzekwa, PhD - School of Pharmacy

https://pharmacy.temple.edu/kenkorzekwa

Research Gate Teaching & Academic Contributions PharmD Teaching: Pharmacokinetics Graduate Teaching: Advanced Pharmacokinetics Advanced Med Chem Pharmacokinetics and Mechanistic Modeling Certificates Advising: 1 doctoral student (TUSP) Research Focus & Activities Ken Korzekwa is a Professor of Pharmaceutical Sciences at Temple University School of Pharmacy. Ken received his B.S. in Chemical ...

DeepIDPS: An Adaptive DRL-based Intrusion Detection and Prevention ...

https://cis.temple.edu/~jiewu/research/publications/Publication_files/ICC2024.pdf

Abstract—Most intrusion detection systems (IDS) are vul-nerable to novel attacks and struggle to maintain a balance between high accuracy and a low false positive rate. Furthermore, the relevant features of Distributed Denial of Service (DDoS) attacks in conventional networks may not necessarily apply to the Software-defined network (SDN) environment. Additionally, weak feature selection ...

Yan Wang's personal website - Temple University

https://cis.temple.edu/~yanwang/publications.html

Yucheng Xie, Xiaonan Guo, Yan Wang, Jerry Cheng, and Yingying Chen. "Universal targeted adversarial attacks against mmwave-based human activity recognition." In Network Security Empowered by Artificial Intelligence, pp. 177-211. Cham: Springer Nature Switzerland, 2024. New!

PSFL: Parallel-Sequential Federated Learning with Convergence Guarantees

https://cis.temple.edu/~jiewu/research/publications/Publication_files/INFOCOM2024_PSFL%20Parallel-Sequential%20Federated%20Learning%20with%20Convergence%20Guarantees.pdf

Abstract—Federated Learning (FL) is a novel distributed learning paradigm which can coordinate multiple clients to jointly train a machine learning model by using their local data samples. Existing FL works can be roughly divided into two categories according to the modes of model training: Parallel FL (PFL) and Sequential FL (SFL). PFL can speed up each round of model training time through ...