[Tutorial I]: 15:30 ~ 16:20, February 19, 2024 (Monday)
Prof. Atsushi Uchida (Saitama University, Japan)

Photonic artificial intelligence: Reservoir computing and decision making based on complex photonics

We overview recent technologies of photonic artificial intelligence using reservoir computing and decision making. We propose photonic integrated circuits for reservoir computing using semiconductor lasers with optical feedback, and construct multiple reservoirs for performance improvement of chaotic-time series prediction. We also demonstrate several decision-making schemes for solving the multi-armed bandit problem using optical spatio-temporal dynamics and mode competition dynamics of semiconductor lasers.


Prof. Atsushi Uchida received the Ph.D. degrees in electrical engineering from Keio University, Japan, in 2000. He was a JSPS Postdoctoral Fellow with the University of Maryland, College Park, USA, from 2002 to 2004. He was an Associate Professor with the Department of Information and Computer Sciences, Saitama University, Saitama, Japan, from 2008 to 2015. Since 2015, he has been a Professor with the Department of Information and Computer Sciences, Saitama University, Saitama, Japan.
He is currently working on synchronization of chaotic lasers and its applications for optical secure communications, secure key generation using chaotic lasers for cryptography, fast physical random number generation using chaotic lasers, reservoir computing using complex photonics, photonic decision making, and consistency in nonlinear dynamical systems.

[Tutorial II]: 10:40 ~ 11:30, February 21, 2024 (Wednesday)
Prof. Sungtek Kahng (Incheon Nat셪 Univ., Republic of Korea)

Automated solution finding approaches based on stochastic optimization methods in the A.I.-inundated society

This tutorial deals with stochastic automatic optimization methods known as programing-based optimization approaches such as Evolutionary Strategy, Genetic Algorithm, Particle Swarm Optimization whose relatives are Marine Predator Algorithm and Weed Colonization from the standpoints of principles and the applications to Engineering problems. These methods will be mentioned by being compared to ANN, Machine Learning, and their up-to-date optimization techniques.


Prof. Sungtek Kahng received his Ph.D. degree from Hanyang University, Korea in 2000, with a specialty in Radio Science and Engineering. From 2000 to 2004, he worked for the Electronics and Telecommunication Research Institute(briefly, ETRI), and developed Satellite Payloads of GEOs, Computational EM methods and Electromagnetic Field Measurement Techniques. Currently, in Dept. of Info. & Telecomm. Eng. of Incheon National University, he works on WPT devices, PD sensors, EMI/EMC, RF components for UAMs, Radars and satellites, smart antennas for 5G/B5G/IoT networking. He in the committee evaluating Korean Satellite Development Programs appointed by NRF has cooperated mainly with LGE, LIGNEX1, ETRI, KARI, ADD, CAMM, Corning(USA), Samsung, AceTechnology, Hyundai, LG Innotek, Amotech, Innertron, and NISSHA(Japan) where he holds a fellow position. Along with roles of IEEE APS STC judge, IEEE APS TC Antenna Measurements, ISAP, APMC, KICS executive director, KIEE journal editor, etc., he served as the ICCR 2022 TPC Chair, Chair of LOC for ICEE 2026 and General Chair for IEEE APCAP 2019. Recently, he was invited to give keynote speeches at several conferences including IEICE 2021 General Conference, JC-SAT 2023 and International Symposium on Antennas and Propagation 2023 under the themes on RIS technologies, LEO Satellite communication with 5G ground networks in the era of 6G mobile services, and technical details of ITRC funded by the Korean Ministry of Science and ICT and his task as the center director.