
Prof. Minoru Sasaki
Profile
Prof. Minoru Sasaki is a well-recognized educator and researcher in the field of control engineering, mechanical vibration, intelligent machines and robotics. He has been associated with the Gifu University, Japan since April 1993 till his retirement in March 2022. He was a Senior Professor at the University since 2015.
Prof. Sasaki has made original contributions through basic and applied research in the field of mechatronics and robotics, with pioneering work covering specialized topics such as actuator position/force control, autonomous flying robots, bio-signal interfaces, flexible manipulators and smart actuators, among others. Apart from his illustrious career as an educator and researcher, Prof. Sasaki has served with distinction as an able academic administrator in many senior positions of responsibility at the Gifu University. He has been closely associated with various projects of Japan’s Ministry of Education, Culture, Sports, Science and Technology and has made significant contributions in promoting regional development through cooperation with various entities.
As a mentor and research supervisor, Prof. Sasaki has guided many international students and actively collaborated with foreign universities such as Seoul University of Science and Technology (Korea), University of Brunei Darussalam (Brunei), and Dedan Kimathi Institute of Technology (Kenya). He was also awarded an honorary Doctor of Engineering degree by the Dedan Kimathi Institute of Technology.
Some of Prof. Sasaki’s numerous awards and accolades include: Japan AEM Society Distinguished Service Award (twice), the Society of Instrument and Control Engineers System Integration Division Contribution Award, the Society of Instrument and Control Engineers Award, the System Integration Division Contribution Award and the Nigerian Institution of Mechanical Engineers Distinguished Award of Recognition. Many of his papers and presentations received recognition, such as: AEM Society of Japan Best Paper Award, IEEE International Conference on Applied System Innovation, Best Conference Paper Awards, 51st SICE Chubu Branch Award for Research, Best Paper Award of International Conference on Vibration Engineering, Science and Technology (INVEST-22). He has delivered 20 invited lectures in countries such as Kenya, Indonesia, Bulgaria, China, Taiwan, Nigeria and India. Prof. Sasaki has served as the Executive Director of the Society of Instrument and Control Engineers (January 1, 2008-December 31, 2009), the Director of the AEM Society of Japan (January 1, 2008-2022), the Branch President of the SICE Chubu Branch and IEEE LIFE SENIOR MEMBER. Prof Sasaki has also successfully organized a large number of conferences and symposia on diverse technical subjects.
Title of Presentation:
Intelligent man-machine interface systems using EEG, EMG, and EOG
Abstract:
In modern East Asia (China, South Korea, Taiwan) and Japan, the aging of the population is progressing, and the number of functional disorders associated with aging is increasing. On the other hand, disabilities caused by traffic accidents or work-related accidents have the potential to change an individual’s life from being independent to dependent. The reality is that the number of people who require such constant care is increasing. To this end, essential issues include supporting individuals to regain control, restoring career independence, reducing the burden on caregivers, and promoting autonomy and automation. In recent years, research on human-machine interfaces that apply biological signals to disabled people has been attracting attention, to promote the independence of elderly and disabled people and reduce the burden on caregivers. As mentioned above, bio-signal technologies combined with assistive devices and communication methods can address or reduce the severity of the challenges experienced by older adults and people with disabilities. Man-machine interface systems via electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) signals offer endless opportunities for stakeholders. In recent years, research and development have been conducted on the technology necessary to estimate and identify bio-signals that can be used with sensors and signal processing technology and convert them into mechanical control methods. The need for bio-signal control is heightened by elderly and disabled people who have lost control of their environment due to various events. Biotechnology, which combines human-robot interfaces, is a promising initiative to promote quality of life and independence. This study utilizes EEG, EOG, EMG, and eye-related information to control a machine in a 3D environment. By mapping gaze movements to the corresponding robot’s inverse kinematics, operators can control the robot arm through eye movements and facial muscles. It is also possible to use EMG signals from facial muscles to control the force of the robot hand. These research results demonstrated the feasibility of the concept of leveraging a dynamic 3D bio-signal man-machine control system with further improvements. This tutorial will also introduce some of these application examples.

Thomhert Suprapto Siadari, Ph.D
Title of Presentation:
Data-centric AI: Perspectives and Techniques
Abstract:
In recent years, the spotlight in the field of Artificial Intelligence (AI) has shifted from model-centric to data-centric approaches, fundamentally transforming the way we design, develop, and deploy AI systems. This tutorial, “Data-centric AI: Perspectives and Techniques,” aims to explore this paradigm shift, focusing on the importance of high-quality data in building robust and effective AI solutions.
The session will begin by defining data-centric AI and contrasting it with traditional model-centric approaches. Participants will gain insights into how prioritizing data quality, rather than solely improving algorithms, can lead to significant advancements in AI performance. We will delve into key methodologies for data preprocessing, augmentation, and labeling, emphasizing the critical role of data engineering in the AI pipeline.
Through practical examples, attendees will learn best practices for curating datasets that enhance the generalization capabilities of AI models. We will also discuss emerging tools and frameworks that facilitate the implementation of data-centric strategies, highlighting their impact on improving AI performances.
By the end of this tutorial, participants will have a comprehensive understanding of the data-centric AI perspective and will be equipped with actionable techniques to elevate their AI projects.

Dessi Puji Lestari, Ph.D
Co-Founder of Prosa.ai and Chief Scientist of Speech og Prosa.ai
Dessi Puji Lestari started developing Indonesian-language Natural Language Processing (NLP) when she was an undergraduate in Bandung Institute Technology (ITB). After graduating in 2002, she worked for her alma mater as lecturer in the informatics study. She continues her research while pursuing master degree and doctoral degree in Japan.
Dessi Puji Lestari has more than sixty research publications that used as references by academics, industries and Public Sectors ( Dessi Puji Lestari – Institut Teknologi Bandung (itb.ac.id))
Keeping the spirit of Quad Helix, In 2018, she and two other co-founders solidified their steps and choices to establish Prosa.ai (Pemrosesan Bahasa) a startup company in the field of artificial intelligence with a specialization in NLP for Bahasa Indonesia, both for text processing and speech processing. She with other 2 co-founders believes Indonesia can develop AI technology to enhance business services and bring better value to their customers, and to make it happen requires collaboration between academia, industry, and all stakeholders.
Pendidikan
Bachelor : Institut Teknologi Bandung, Bandung – Indonesia, 2002
Master : Tokyo Institute of Technology, 2007
Doctoral : Tokyo Institute of Technology, 2011
Publikasi dan Projects
More than 60 publications (https://www.itb.ac.id/staf/profil/dessi-puji-lestari )
More than 15 in ITB (https://www.itb.ac.id/staf/profil/dessi-puji-lestari)
SaaS-Based AI Solutions for Speech and Text by Prosa.ai
In this tutorial, we will delve into the transformative capabilities of SaaS-based Text-to-Speech (TTS) and Speech-to-Text (STT) technologies developed by Prosa.ai. This session will provide an overview of TTS and STT systems, highlighting their various applications, technical architecture, and advanced integrated features. Because our TTS and STT systems are cloud-based Software-as-a-Service (SaaS) solutions, they offer unparalleled convenience, scalability, and cost-efficiency, making it easy for all users to access and utilize our web applications for their needs.