Keynote Speakers

2024 9th International Conference on Intelligent Information Technology (ICIIT 2024) aims to gather professors, researchers, scholars and industrial pioneers all over the world. ICIIT is the premier forum for the presentation and exchange of past experiences and new advances and research results in the field of theoretical and industrial experience. The conference welcomes contributions which promote the exchange of ideas and rational discourse between educators and researchers all over the world. We aim to building an idea-trading platform for the purpose of encouraging researcher participating in this event. ICIIT 2024 is welcome qualified persons to delivery a speech in the related fields. If you are interested, please send a brief CV with photo to the conference email box:

Keynote Speaker I

Prof. Vinod A. Prasad

Singapore Institute of Technology, Singapore

Dr. Vinod A Prasad is a Professor and Director of Research at Infocomm Technology Department, Singapore Institute of Technology (SIT). He is also a Visiting Senior Academician at SingHealth (Singapore Health Services) and a Visiting Professor at the Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India. Prior to joining SIT in May 2022, Vinod was a Professor of Engineering Practice at The Hong Kong University of Science and Technology, Hong Kong, a Professor at Indian Institute of Technology (IIT) and an Associate Professor at Nanyang Technological University (NTU), Singapore. Vinod’s research interests include digital signal processing, low power, reconfigurable circuits & systems for wireless communications, Brain Machine Interface and its applications. He has published over 280 papers in refereed international journals and international conferences, supervised and graduated 19 Ph.D. students, successfully completed research projects amounting $4 million funded by various agencies. He is an Associate Editor of five journals - IEEE Transactions on Human-Machine Systems, IEEE Transactions on Neural Systems and Rehabilitation Engineering, IEEE Transactions on Cognitive and Developmental Systems, IEEE Systems Man & Cybernetics Magazine, and Circuits, Systems & Signal Processing (Springer). He was the Co-Chair of Brain-Machine Interface Systems Committee of IEEE Systems, Man & Cybernetics Society which won the award of the ‘Most Active Technical Committee in Human-Machine Systems’ of IEEE Systems, Man and Cybernetics Society in three consecutive years – 2015, 2016 and 2017.

Speech Title: "Brain Machine Interface Systems – Interpreting and Translating Thoughts into Actions"

Abstract: Brain-Machine Interfaces (BMI) are systems that translate the user’s intention coded by brain activity measures into a communication and control signal without using the activity of any muscles or peripheral nerves. The decoded neural patterns can potentially be employed to substitute motor capabilities (e.g., brain-controlled prosthetics for amputees or patients with spinal cord injuries, brain-controlled wheelchairs); improve motor and cognitive (attention, memory, emotion, etc.) using neurofeedback training. BMI has emerging applications in other domains that include (but are not limited to) autonomous vehicles, advanced driver assistance systems, biometric identification, brain fingerprinting, neuromarketing, neuroergonomics (evaluation of cognitive workload, stress, vigilance and fatigue), training of personnel who are required to perform zero-error-tolerance operations (aircraft pilots, air traffic controllers, soldiers), performance error-based reinforcement learning, etc. This talk will commence by providing an overview of BMI, signal processing & machine learning tools, and design considerations for BMI. Further, the talk will cover some selected non-invasive BMI research work from our group (with video demonstrations), which includes decoding of movement kinematics from EEG, real-time closed-loop error-related potential-based self-correcting BMI, EEG-based neuroimaging, brainwave-controlled computer games for improving cognitive skills, biometric identification, image and audio familiarity detection, etc..

Keynote Speaker II

Prof. Eui-Nam Huh

Kyung Hee University, South Korea

Eui-Nam Huh (Member, IEEE) received the Ph.D. degree from The Ohio University, USA, in 2002. Currently, he is a Professor with the Department of Computer Science and Engineering, Kyung Hee University, South Korea. He served for 7.5 years as a chair of department and dean of Information Administration at Kyung Hee University. He is a director of ICT Research Center (ITRC) funded from national project subjected to Mobile Cloud, and Cloud Continuum starting from 2012, and 2023 for 6 & 8 years, respectively. His research interests include the diverse range of subjects, such as cloud computing, the Internet of Things, future internet, distributed real-time systems, mobile computing, big data, and security. He serves on the review board for the National Research Foundation of Korea. He has actively participated in community services for several organizations, including Applied Sciences, ICCSA, WPDRTS/IPDPS, APAN Sensor Network Group, ICUIMC, IMCOM, ICONI, APIC-IST, ICUFN, and SoICT, as different types of editors, and chairs.

Speech Title: "Challenges in Cloud Continuum Computing for Hyper-scale AI Services"

Abstract: Most of the major cloud service providers are launching AI services on conventional cloud services (PaaS & IaaS). Many computing HW resources (such as CPU, VPU, TPU,GPU,FPGA) are used to train large scale AI models handling huge amounts of data including multimodal information. Many companies also have been trying to incorporate AI services fastly to have marketing advantages among competitors using cloud computing infrastructures. Thus, cloud computing faces several issues to provide energy efficient management, highly scalable and new architectural resources for compute and store. Also distributed and parallel ML(machine Learning) technology is implemented to provide fast response. Thus analysis of current computing trends in cloud computing tells many new challenges considering future AI services on cloud computing. Therefore, this talk introduces trends of cloud computing, and discusses challenging issues in the cloud continuum as emerging infrastructure including diverse cloud resources for future AI services: training and serving of hyperscale AI model.