Aohan Li [S'17, M'20] is currently an Assistant Professor at the University of Electro-Communications, Tokyo, Japan. She is also a Visiting Researcher at the Tokyo University of Science, Tokyo, Japan, where she was an Assistant Professor from 2020 to 2022. She received her Ph.D. degree from Keio University, Yokohama, Japan, in 2020. Her current research interests include resource management, quantum annealing, machine learning, and the Internet of Things. She has published over 80 peer-reviewed journal and international conference papers. She was the recipient of the 9th International Conference on Communications and Networking in China 2014 (CHINACOM'14) Best Paper Award, the 3rd International Conference on Artificial Intelligence in Information and Communication (ICAIIC'21) Excellent Paper Award, and the Telecom System Technology Student Excellent Paper Award of the Telecommunications Advancement Foundation, Japan in 2021. 


Assistant Professor (助教)

Visiting Researcher (客員研究員)

Add.:1-5-1, Chofugaoka, Chofu-shi, Tokyo, 182-8585 Japan

TEL: 042-443-5507

E-mail: aohanli@ieee.org

Research Interests

Google Scholar 

        Research Student, Information and Computer Science, Keio University, Tokyo, Japan. (Ohtsuki Lab.) (Sept.2016~Mar. 2017, Japanese Government Scholarship.)

        Japanese, Northeast Normal University, Changchun, China. (Oct. 2015~Aug. 2016)

Graduate School of Informatics and Engineering, The University of  Electro-Communications, Tokyo, Japan.

Department of Electrical Engineering, Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan. (Hasegawa Lab.)

Department of Electrical Engineering, Graduate School of Engineering, Tokyo University of Science, Tokyo, Japan. (Hasegawa Lab.)

Communications Network Business Group, Realsil Microelectronics (Suzhou) Corp. Suzhou, China.

Ongoing:

Principal Investigator:

Research Topic: AI based optimization of the spectrum and energy efficiency for intelligent 6G.

Research Topic: Research on autonomous and distributed transmission parameter selection methods for AI devices in massive IoT systems (IoT システムにおける超多数 AI デバイス接続のための自律分散型送信パラメータ選択手法に関する研究)

Under Review: 3

In preparation: 3

Finished:

Principal Investigator:

Research Topic: Deep Learning Based Dynamic Spectrum Access for Next Generation Wireless Communication.

Research Topic: Deep Reinforcement Learning Based Spectrum Allocation for Cognitive Internet of Things

 Research Topic: Machine Learning-based Optimal Channel Selection for Dynamic Spectrum Access

Research Topic: Rendezvous Problem for Dynamic Spectrum Access

 Research Topic: Optimal Control Channel Establishment for Cognitive Radio Networks

Co-Investigator:

Research Topic

(Joint Research on IoT wireless networks for solving regional issues.)

Research Topic: コヒーレントイジングマシンの応用に関する研究

(Research on the applications of coherent Ising machine.)

Research Topic: 自律移動ロボットによる除菌システム及び除菌センサに関する共同研究

(Joint Research on sanitization systems by autonomous mobile robots and sanitization sensors.)

Research Topic:  適応型無線通信技術の研究

(Research on adaptive wireless communication technology.)

IEEE Communications Letters, IEEE Communications Magazine, IEEE Wireless Communications Magazine, IEEE Network, IEEE Transactions on Industrial Informatics, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Vehicular Technology, IEEE Transactions on Wireless Communications, IEEE Internet of Things Journal, IEEE Transactions on Cognitive Communications and Networking, IEEE Transactions on Green Communications and Networking, ACM Transactions on Internet Technology, IEEE ACCESS, IEEE Systems Journal, IEICE Transactions on Communications, China Communications, ICT Express.

The Year 2023 (4 Students)

X. Lu@UEC: IoT, Machine Learning

S. Sugiyama (B4): IoT

R. Ariyoshi (B4): IoT

Y. Negoya (B4): IoT

The Year 2022 (10 Students)

Research Student:

X. Lu@UEC: IoT, Machine Learning

S. Hasegawa@TUS: IoT, Decentralized Reinforcement Learning, Optimization, Millimeter Wave, UAV

T. Otsuka@TUS: NOMA, Quantum Annealing, Coherent Ising Machine

I. Urabe@TUS: LoRa, Decentralized Reinforcement Learning

M. Sugiyama@TUS: HARQ assisted NOMA, Laser Chaos, Reinforcement Learning

T. Ling@TUS: 6G, IoT, Federated Learning

Y. Li@TUS: RIS, Quantum Annealing

T. Fujita@TUS: UAV, Quantum Annealing

S. Ishibashi@TUS: NOMA, Quantum Annealing

S. Matsuoka@TUS: Laser Chaos, Reinforcement Learning, NOMA

The Year 2021 (7 Students)

Z. Duan: Grant-free NOMA System, Resource allocation, Laser Chaos, Reinforcement Learning

T. Otsuka: NOMA, Quantum Annealing, Coherent Ising Machine

I. Urabe: LoRa, Decentralized Reinforcement Learning

M. Sugiyama: HARQ assisted NOMA, Laser Chaos, Reinforcement Learning

M. Fujisawa: IoT, Reinforcement Learning

T. Ling: 6G, IoT, Federated Learning

Y. Li: RIS, Quantum Annealing

The Year 2020 (21 Students)