Invited Speakers
Asst. Prof. Trang Nakamoto,
Ritsumeikan University, Japan
Trang Nakamoto, born in Vietnam in 1986, is an assistant professor at Ritsumeikan University. He earned his B.Eng. from Hanoi University of Science and Technology in Vietnam (2009), followed by a Master’s degree from Dongguk University in South Korea (2011) and a Ph.D. from Ritsumeikan University in Japan (2014). After two years working in industry, he returned to academia in 2017 as a senior researcher at R-GIRO. His research focuses on the development of innovative biosensors powered by microbial fuel cell (MFC) technology. He is recognized for pioneering practical, low-cost MFC-based biosensors for critical applications in environmental monitoring and smart agriculture. With over 40 peer-reviewed publications and more than 50 international conference presentations, contributing significantly to the advancement of bio-electrochemical sensing technologies.
Title:Harnessing Microbial Fuel Cells for Biosensing Applications and Green Energy
Abstract:Microbial Fuel Cells (MFCs) offer a unique platform for both green energy generation and, more powerfully, self-powered biosensing. This presentation introduces advanced MFC-based biosensing technologies and highlights our research advancements in transforming microbial bio-electrochemistry into real-time, actionable data for environmental and agricultural monitoring, overcoming the cost and power limitations of traditional sensors.
Our research focuses on developing practical, MFC-based biosensors that leverage microbial metabolism to detect environmental changes. We will present case studies including floating sensors for tracking organic pollution in wastewater and portable devices for sensing soil water content in smart agriculture. A cornerstone of our work is sustainability; we have pioneered novel, low-cost electrodes derived from waste biomass like rice husks and loofah sponges. While these devices are powered by the green energy they generate from waste, their primary value lies in their function as autonomous sensors. Our work demonstrates a clear pathway toward developing intelligent, sustainable sensor networks for a smarter, greener future.
Dr. Shitikantha Dash,
National University of Singapore, Singapore
I am a post-doctoral research fellow at the National University of Singapore (NUS), Singapore. Here, I am working with Prof. Dipti Srinivasan's research group towards developing Singapore's largest V2G testbed. Prior to this, I worked as a research associate at the Indian Institute of Technology (IIT) Ropar, Rupnagar, India, under a CRG project sponsored by the Science and Engineering Research Board (SERB), New Delhi.
I completed my bachelor's at the Biju Patnaik University of Technology (BPUT), Odisha, India, in Electrical and Electronics Engineering, and my master's at the Center for Advanced Post Graduate Studies, BPUT, Rourkela, India, in Power System Engineering. Then I moved to the Indian Institute of Technology Ropar, Rupnagar, India, for my PhD program in the Department of Electrical Engineering under the supervision of Prof. Ranjana Sodhi from the EE department and Prof. Balwinder Sodhi from the CS department.
My primary research interest includes demand response, energy market, energy storage systems, distributed energy resources management, and residential load monitoring. When I am not doing research, you may find me at the pool table in staff launge. I also enjoy post-independence Odia literature and editing Odia Wikipedia.
Title: Profit-Aware EV Utilisation Model for Sustainable Smart Cities: Joint Optimisation over EV System, Power Grid System, and City Road Grid System
Abstract: A sustainable city requires a sustainable means of transportation. This ambition is leading towards higher penetration of electric vehicles (EVs) in our cities, in both the private and commercial sectors, putting an ever greater burden on the existing power grid. Modern deregulated power grids vary electricity tariffs from location to location and from time to time to compensate for any additional burden. In this paper, we propose a profit-aware solution to strategically manage the movements of EVs in the city to support the grid while exploiting these locational, time-varying prices. This work is divided into three parts: (M1) profit-aware charging location and optimal route selection, (M2) profit-aware charging and discharging location and optimal route selection, and (M2b) profit-aware charging and discharging location and optimal route selection considering demand-side flexibility. This work is tested on the MATLAB programming platform using the Gurobi optimisation solver. From the extensive case studies, it is found that M1 can yield profits up to 2 times greater than those of its competitors, whereas M2 can achieve profits up to 2.5 times higher and simultaneously provide substantial grid support. Additionally, the M2b extension makes M2 more efficient in terms of grid support.