• Practical AI/ML for Biosignals: From Statistical Features to Multi-Task Learning

    Tutorial

    Biosignals are rich, messy, and highly variable. In this tutorial, we offer a practical entry point into AI/ML for biosensing by starting from what makes signals like electroencephalography (EEG) and photoplethysmography (PPG) different from typical datasets: their frequency–magnitude structure, noise and artifacts, and strong variability across people and hardware (often experienced as domain shift). We show how this domain knowledge should shape the way you represent signals and choose models.

    We then use statistical analysis as the bridge from raw waveforms to meaningful features, connecting intuitive signal properties to time-domain statistics and frequency-domain summaries that often carry the most useful information. From there, we explain how classical machine learning uses these engineered features, how deep learning can learn representations directly from raw inputs, and how hybrid pipelines can combine both worlds. We also discuss practical, lightweight approaches to interpretability and explainability that help researchers and practitioners trust and debug biosignal models.

    Finally, we focus on multi-task learning as an extension for many biosensing problems. We cover how to define tasks that help rather than fight each other, why multi-loss training can become unstable, and how adaptive loss weighting can reduce manual tuning and keep training balanced. Participants will leave with concrete pitfalls to avoid and practical takeaways they can apply immediately.

    • Theerawit Wilaiprasitporn

      Vidyasirimedhi Institute of Science & Technology (VISTEC), Thailand

      Theerawit Wilaiprasitporn received his Ph.D. in Engineering from the Graduate School of Information Science and Engineering at the Tokyo Institute of Technology, Japan, in 2017. He specializes in AI applications for health and medical purposes. He founded Interfaces, an AI-driven health research team at the Vidyasirimedhi Institute of Science and Technology (VISTEC) in Thailand.

      Since establishing Interfaces at VISTEC in 2019, Theerawit’s contributions have been instrumental in developing remote health monitoring systems, which supported over 30,000 individuals during the COVID-19 pandemic. This achievement led to his nomination for the 2022 IEEE R10 Humanitarian Technology Activities Outstanding Volunteer Award. Most recently, he was honored with the prestigious Young Scientist Award 2024 by the Foundation for the Promotion of Science and Technology under the Patronage of His Majesty the King, recognizing him as one of Thailand’s leading young professionals. He was subsequently awarded the Outstanding Research Award 2025 from the National Research Council of Thailand (NRCT) for his long-term work (2019–2025) on advancing multi-task and multi-objective AI architectures for EEG and PPG signal processing.

      Theerawit served as an Associate Editor for the IEEE Internet of Things Journal and the IEEE Sensors Journal for four years before his resignation. Since 2025, he has been involved in Thailand’s first digital therapeutic service, FitSloth Company Limited.

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  • Fiber optic biosensing strategies for attomolar analyte detection

    Tutorial

    Rapid decentralized disease diagnosis by non- or minimally- invasive means such as microlitre blood sample or urine/saliva or detection of the newer variety of disease biomarkers such as circulating cell-free DNA demand diagnostic technologies with an attomolar analyte detection capability. The past two decades have seen a tremendous growth in the biosensor strategies that offer such ultra-high sensitivities. A variety of optical and electrochemical transduction techniques aided by nanomaterials (e.g. plasmonic nanoparticles and graphene) and AI/ML have been demonstrated.

     

    This tutorial briefly reviews some of the reports on attomolar labelled and label-free biosensing strategies highlighting the working principles and limitations on the scale-up and high-throughput applications. Subsequently, a detailed discussion will be devoted to the plasmonic fiber optic biosensing solutions in particular. Gratings and modified-geometry based fiber optic sensors and their advantages and limitations will be covered.

    • Sai.

      V V Raghavendra

      Indian Institute of Technology Madras, Chennai, India

      Dr. V.V. Raghavendra Sai is a Professor of Biomedical Engineering in the Department of Applied Mechanics and Biomedical Engineering. He is the group leader of the Biosensors Research Laboratory at IIT Madras. Prior to joining IIT Madras in 2011, he was a postdoctoral fellow at University of Idaho, USA for two years. He received the Ph.D. in Biomedical Engineering from Indian Institute of Technology Bombay in 2009 for the work done on development of two novel fiber optic biosensing technologies for detection of biomolecules and pathogens. The biosensors laboratory focuses on development of affordable and indigenous technologies for clinical diagnostics, water, food and environmental monitoring. He has authored more than 45 peer reviewed research articles, more than 25 conference presentations/proceedings and filed 10 patents. He is also a recipient of prestigious Young Engineer Award from Indian National Academy of Engineering (INAE) and International travel award from Epson Research Foundation in 2015 and 2016 respectively. He has been part of several international research projects with US, UK, Germany and Norway. Some of the technologies developed by his group has been licensed and transferred to US and Indian startups. He has guided more than 15 PhD and MS scholars and mentored 10 Postdocs. Currently 10 research scholars (MS & PhD) and 6 Postdocs are working with him.

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  • Superchiral Light-based Bio-Chemical Sensing

    Monitoring biological systems is crucial in healthcare, driving the need for reliable and non-invasive solutions. The proliferation of unverified drugs in the market necessitates reliable methods for their detection and identification, especially amidst advancements in pharmaceuticals. Plasmonic biosensors emerge as a great platform for ultra-sensitive detection, identification, and manipulation of biomolecular systems. This tutorial will present the critical need for precise detection and monitoring of biomolecules and drugs, presenting innovative solutions through the design of a plasmonic biosensor to tackle challenges in sensitivity, selectivity, and label-free detection and identification. The tutorial will elaborate a robust and tunable, cavity-integrated plasmonic nanopatterned sensor that exhibits superchiral light in the infrared domain for ultrasensitive detection of chiral molecular concentrations and enantiomeric excesses. The multispectral capability of this system is further harnessed to generate unique chiral fingerprint-based barcodes for the identification of diverse chiral drugs and biomolecules. The tutorial will further discuss and demonstrate results for a surface-modified plasmonic biosensor operating in the visible-near-infrared realm in detecting viral biomarkers and neurotransmitters directly from complex physiological environments. The system, on coupling with a microfluidic flow setup allows sensitive, selective and rapid detection without requiring complex pre-processing or sample preparation steps. We will discuss additional applications of the unique plasmonic sensor, utilizing the property of tunable superchirality to create a dynamic chirality tracking system operating in the near infrared for real-time monitoring of protein dynamics. These techniques aim to revolutionize bio-detection, chiral differentiation, and sorting processes, having extensive applications in medical research and pharmaceutical industries.

    • Dr. Debashis Chanda

      University of Central Florida, Florida, USA

      Prof. Debashis Chanda is a Professor, jointly appointed with NanoScience Technology Center, Dept. of Physics and College of Optics and Photonics (CREOL), University of Central Florida (UCF).  Dr. Chanda received his PhD from University of Toronto. His PhD work was recognized in the form of several awards, including prestigious National Sciences and Engineering Research Council (NSERC) fellowship. Dr. Chanda completed his post-doctoral research with Prof. John A. Rogers at Beckman Institute, University of Illinois at Urbana-Champaign. Most of his research works were extensively covered by National Science Foundation news, BBC, Daily Mail, NBC, Fox, Science Radio and other national/international media outlets. His research has appeared on American Scientist magazine as focused article where it was outlined how companies like Intel, Toshiba etc are trying to adopt some of the printing techniques which were developed in his group. Dr. Chanda is a recipient of the 2012 DOE Energy Frontier Research Center (EFRC) Solar Energy Future Direction Innovation Proposal Award, International Displaying Future Award-2016 by Merck Germany, UCF Research Incentive Award (2017), UCF Reach of the Stars Award (2018), UCF Luminary Award (2020), Samsung Global Research Outreach (GRO) Award (2022), Sony Research Award (2022), UCF Research Incentive Award (2025), UCF College of Science Oscar Award (2026), UCF Trustee Chair Award (2026). Dr. Chanda’s research has been supported by NSF, DoD, DARPA, Florida Space Institute/NASA, Northrop Grumman, Lockheed Martin etc. Apart from that Dr. Chanda is the founder of start-up, E-Skin Displays Inc., out of his research in California.

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