Dr. Chiu has published more than 25 research papers in IEEE/ACM international conferences and journals. Among these papers, journal papers were mainly published in impactful Q1 journals such as IEEE TSC, IEEE TWC, IEEE TMC, IEEE IoT Journal, IEEE Network, IEEE WCM. Moreover, conference papers were published in IEEE flagship conferences (e.g., ACM/IEEE ICDCS, IEEE ICRA, IEEE ICC, and IEEE GLOBECOM, etc.).
Dr. Chiu has participated in many international academic and industrial projects for B5G/6G communications, fog/edge computing, edge intelligence/AI. Dr. Chiu has joined several industrial projects with famous companies such as Qualcomm, Intel and OmniEyes startup to realize his research in commercialized products.
Research Directions
2. Zih-Yi Yang, Te-Chuan Chiu, and Jang-Ping Sheu,
“Reinforcement Learning-based Task Offloading of MEC-assisted UAVs in Precision Agriculture,”
in IEEE Global Communications Conference (GLOBECOM),
Kuala Lumpur, Malaysia, Dec. 2023.
3. Te-Chuan Chiu, Yuan-Yao Shih, Ai-Chun Pang, et al.,
“Semi-Supervised Distributed Learning with Non-IID Data for AIoT Service Platform,”
in IEEE Internet of Things Journal, Oct. 2020.
Edge Intelligence/AI,
Federated Learning (FL),
Privacy and Security
1. Kung-Hao Chang, Te-Chuan Chiu, and Jang-Ping Sheu,
“VISIT: Virtual-Targeted Sequential Training with Hierarchical Federated Learning on Non-IID Data,”
in IEEE International Conference on Communications (ICC), Denver, USA, Jun. 2024.
2. Tzu-Hsuan Peng, Te-Chuan Chiu, Ai-Chun Pang, and Wei-Chun Tai,
“SynFMPL: A Federated Meta Pseudo Labeling Framework with Synergetic Strategy,”
in IEEE International Conference on Communications (ICC), Rome, Italy, Jun. 2023.
3. Te-Chuan Chiu, Wei-Che Lin, Ai-Chun Pang, and Li-Chen Cheng,
“Dual-Masking Framework against Two-Sided Model Attacks in Federated Learning,”
in IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, Dec. 2021.
4. Ling-Yuan Chen, Te-Chuan Chiu, Ai-Chun Pang, and Li-Chen Cheng,
“FedEqual: Defending Model Poisoning Attacks in Heterogeneous Federated Learning,”
in IEEE Global Communications Conference (GLOBECOM), Madrid, Spain, Dec. 2021.
Fog/Edge Computing,
Ultra-low Latency Service
1. Te-Chuan Chiu, Chih-Yu Wang, Ai-Chun Pang and Wei-Ho Chung,
“Collaborative Energy Beamforming for Wireless Powered Fog Computing Networks,”
in IEEE Transactions on Wireless Communications, Oct. 2022.
2022 Best Journal Paper Award from Taiwan Association of Cloud Computing(TACC)
2. Te-Chuan Chiu, Ai-Chun Pang, Wei-Ho Chung, and Junshan Zhang,
“Latency-Driven Fog Cooperation Approach in Fog Radio Access Networks,”
in IEEE Transactions on Services Computing, Oct. 2019.
3. Ai-Chun Pang, Wei-Ho Chung, Te-Chuan Chiu, and Junshan Zhang,
“Latency-Driven Cooperative Task Computing in Multi-user Fog-Radio Access Networks,”
in IEEE International Conference on Distributed Computing Systems (ICDCS), 2017.
4. Yuan-Yao Shih, Wei-Ho Chung, Ai-Chun Pang, Te-Chuan Chiu, et al.,
“Enabling Low-Latency Applications in Fog-Radio Access Networks,”
in IEEE Network, Feb. 2017.
Fog/Edge Computing,
Mobility-aware Service
1. Chao-Lun Wu, Te-Chuan Chiu, Chih-Yu Wang, and Ai-Chun Pang,
“Mobility-Aware Deep Reinforcement Learning with Seq2seq Mobility Prediction for Offloading
and Allocation in Edge Computing,”
in IEEE Transactions on Mobile Computing, Jun. 2024.
2. Chao-Lun Wu, Te-Chuan Chiu, Chih-Yu Wang, and Ai-Chun Pang,
“Mobility-Aware Deep Reinforcement Learning with Glimpse Mobility Prediction in Edge
Computing,” in IEEE International Conference on Communications (ICC), Virtual Conf., 2020.
3. Ya-Ju Yu, Te-Chuan Chiu, Ai-Chun Pang, Ming-Fan Chen et al.,
“Virtual Machine Placement for Backhaul Traffic Minimization in Fog Radio Access Networks,”
in IEEE International Conference on Communications (ICC), Paris, France, 2017.