Plenary Talks




KEYNOTE SPEAKERS

Not found Prof. Sheldon Williamson
Fellow, IEEE
Professor, Ontario Tech University, Canada
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Title: Enhancing the life of Lithium-ion (Li-ion) battery packs

Abstract:

Enhancing the life of Lithium-ion (Li-ion) battery packs has been the topic of much interest. In this framework, the role of on-board cell voltage balancing of Li-ion batteries will be highlighted in this talk. This is a very important topic in the context of battery energy storage cost and life/state-of-charge/state-of-health (SOC/SOH) monitoring. This talk will also introduce a first-of-its-kind closed-loop cell charge (voltage) balancing and extreme fast charging technique. The technique uses instantaneous cell voltage and/or temperature rise (ΔT) as a control parameter. Existing charging techniques for Li-ion batteries use a largely open-loop approach, where the charge profile is pre-decided, based on apriori knowledge of cell parameters. There is a need for closed-loop charging techniques that use instantaneous cell voltage and/or temperature to modulate the charging current magnitude. This talk addresses this gap by proposing for the first time ever a constant-temperature constant-voltage (CT-CV) charging technique, considering cell temperature as a key degradation metric.Furthermore, continuous monitoring of SOC/SOH of a Li-ion battery is essential to avoid over-charging, over-discharging, and ensure smart battery management. It also ensures overall safe operation, increase in calendar life, and reduction of average life-cycle cost. However, accurate SOC/SOH estimation has become a major challenge, since these studies need large amounts of experimental data, and adopt standard charge/discharge patterns that do not reflect real world driving loads.

In this talk, advanced machine learning (ML) techniques will be introduced to estimate battery SOC/SOH based on measured critical battery parameters. The effectiveness of the proposed ML techniques are verified using experimental data of the Li-ion battery operating under varied driving schedules and temperatures. Experimental test results show that the proposed ML approaches outperform other conventional approaches with much greater accuracy. This presentation will also highlight the current status and future opportunities within Ontario Tech University’s research program on transportation electrification and electric energy storage systems. The above-mentioned research initiatives will be described in the presentation and industry-specific projects within the STEER group will be highlighted. The NSERC Canada Research Chair (CRC) program includes several novel initiatives in the areas of transportation electrification and is built upon the expertise and knowledge of the STEER group in a number of promising interdisciplinary areas related to power electronics and motor drives.
Not found Prof.V John Mathews
Fellow, IEEE
Professor, Oregon State University, USA
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V John Mathews is a professor in the School of Electrical Engineering and Computer Science (EECS) at Oregon State University. He received his PhD and MS degrees in electrical and computer engineering from the University of Iowa, Iowa City, Iowa in 1984 and 1981, respectively, and the BE (Hons.) degree in electronics and communication engineering from the Regional Engineering College (now National Institute of Technology), Tiruchirappalli, India in 1980. He was with the Department of Electrical and Computer Engineering at the University of Utah from 1985 until 2015. He served as the chairman of the ECE department at Utah from 1999 to 2003, and as the head of the School of EECS from 2015 to 2017. Mathews’ research interests are in the theory and applications of signal processing and machine learning techniques in neural engineering, biomedicine, and structural health management. He is the author of the book Polynomial Signal Processing, published by Wiley, and co-authored with Professor G. L. Sicuranza, University of Trieste, Italy. He has published more than 175 technical papers, and is the inventor on ten patents. Mathews is a Fellow of IEEE. He was the Vice President - Finance of the IEEE Signal Processing Society during 2003-2005, and the Vice President - Conferences of the Society during 2009-2011. He was a distinguished lecturer of the IEEE Signal Processing Society for 2013 and 2014, and is the recipient of the 2014 IEEE Signal Processing Society Meritorious Service Award.

Title: Intelligent Signal Processing in Neural Engineering and Biomedicine

Abstract:

Data-driven signal processing and machine learning techniques have the potential to greatly enhance our ability to diagnose and treat diseases and other health problems. This talk will discuss a number of examples of applying signal processing and machine learning approaches for improving human healthcare. These examples will include one or more of
(1) reanimating paralyzed limbs for restoring motor skills;
(2) predicting movement intent using peripheral nerve signals and electromyograms;
(3) early detection of maternal-fetal diseases such as preeclampsia; and
(4) detecting and predicting seizures in epileptic patients.
Not found Prof. Nawab Muhammad Faseeh Qureshi
Senior Member IEEE, ACM
Assistant Professor, Sungkyunkwan University, Korea
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Dr. Nawab Muhammad Faseeh Qureshi is an assistant professor in the department of Computer Education, Sungkyunkwan University, Seoul, South Korea. He received 1st Superior Research award from his college for outstanding research performance. He has graduated several masters student and Ph.D. student so far. His area of research is convergence of big data with machine learning, deep learning, natural language processing, context-aware processing in IoT devices and their communication protocols for 5G and onwards. He has published several papers in TOP tier journals such as IEEE Internet of Things, IEEE Transactions on Industrial Informatics, Sustainable Cities and Society, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Fuzzy Systems and Flagship conferences such as IEEE global communications conference (GLOBECOM), IEEE International Conference on Communications (IEEE ICC) and IEEE International Conference on Distributed Computing Systems (ICDCS) and others. He is a Senior Member IEEE and actively participates in online Webinars and has given several keynotes in the conferences and Seminars.

Title : AI-Enabled Security through NLP in the Metaverse Environment

Abstract:

Abstract: Metaverse is a broad technology name that includes virtual reality and augmented reality visualizations. These days this term is broadly used in research to cope a variety of problems with respect to big data, ML, Deep Learning especially Natural Language Processing (NLP) that understands the language specifications and helps to establish the meaning for variety of languages and visual text data. In the talk, we will discuss NLP and the way it will play an important role in the future platform metaverse. Also, we will discuss an aspect of AI-enabled security related to NLP in the metaverse where we will discuss how the meaning is extracted from a text regarding a possible attack in the NLP-based metaverse environment.
Not found Prof. Paolo Viotti
Associate Professor
Sapienza University of Rome, Italy
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Title: THE USE OF A INNOVATIVE REMOTE CONTROL SYSTEM FOR THE HYDRAULIC INFRASTRUCTURE

P. Viotti, A. Chiavola, C. Di Marcantonio, P. Sigismondi, F. Tatti, G. Sappa

Abstract:

The objectives of the project have resulted in the design and testing of a multi-component system for the implementation of the control and management of the Integrated Water Service (IIS) even in the event of natural or anthropogenic disasters (seismic events, drought conditions, malicious pollution with illegal discharges into the sewers). With IIS is intended the complete cycle of waters ranging from the sources to the final disposal to the nature after use and treatment. The timely detection of the aforementioned anomaly conditions is vital since the Integrated Water Service (SII), providing a service of primary importance to the population, must be able to respond quickly to critical situations that could compromise its functionality. The innovation consisted in the synergistic use of:
• MEMS-type acquisition sensors and piezo-electric sensors • traditional sensors to detect hydraulic and chemical-physical parameters
• Low consumption RTU (Remote Terminal Unit) for acquisition and processing
• wireless networks for data transmission, conventional (2G / 3G / 4G) and advanced (LoRaWAN)
• SCADA systems for the visualization and historical consultation of data.
The data acquired and processed by the implemented system are those relating to hydraulic processes (flow rates, pressures, water levels), purification processes (pH, dissolved oxygen, suspended solids, residual chlorine) and seismic shaking data (accelerations on hydraulic works ).
Not found Dr. Sugeeth Gopinathan
Head of Robotics Applications
Neura Robotics, Germany
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He is currently the head of Robotics Applications at Neura Robotics Germany. He has taken Post Doc from TU Braunschweig, Germany, and Ph.D. from the University of Bielefeld, Germany. Dr. Sugeeth received Kazuo Tanie Award, IEEE, Lisbon, Portugal. His areas of interest are automation and robotics.

Title: Future Trends in Robotics

Abstract:

Robotics had been a topic of interest since the late 90s. The whole field has gone through a massive evolution since the start of 2010. The introduction of collaborative robots has opened up many possibilities and use cases for robots in both traditional industries and SMEs. Currently, the growth of robotics is more inclined towards AI and related cognitive capabilities. The talk is intended to provide an overview of the changes we should expect in the coming ten years and how to mold a career in this field.
Not found Dr. Asokan Thondiyath
Professor and Head, Department of Engineering Design
IIT Madras.
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Currently Professor and Head of the Department of Engineering Design, IIT Madras. He was awarded the Stanford-India Biodesign fellowship by Stanford University, USA in 2009 and has completed a post-doctoral fellowship in medical device development at Stanford University. He received Ph.D. in Mechanical Engineering from IIT Madras in the year 2000. Dr. Asokan is a visiting Fellow of the University of New South Wales, Australia. Dr. Asokan has published more than 120 papers in International Journals and conferences and has filed 20 patents in India, USA, and Singapore

Title: Autonomy for Robots- Design Challenges

Abstract:

Autonomous robots are finding wide applications in many areas. Providing autonomous capabilities is a challenging task in the case of field robots as the environment is usually unstructured and unpredictable. This talk will focus on some of the major challenges in autonomous navigation and control of robots and present some case studies on developing autonomous robots for field applications.

Tutorial Speakers

Not found Dr. Prasanth Venugopal
Assistant Professor, University of Twente, Netherlands
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Prasanth Venugopal received the B.Tech. degree in electrical and electronics engineering from Amrita Vishwa Vidyapeetham University, Coimbatore, India, in 2010, and the M.Sc. degree in electrical engineering and the Ph.D. degree from the Delft University of Technology, Delft, The Netherlands, in 2012 and 2018, respectively. His MSc. and Ph.D. theses were related to wireless charging of EVs. He worked in the semiconductor and passive components industry from 2016-2020 in Munich, Germany. From November 2016 to December 2018, he was with Qualcomm Halo, Munich, Germany, as a Senior Electrical Engineer in the field of power electronic systems and applications related to wireless charging of Electric Vehicles. He then went on to work at TDK Europe as a Technical Specialist/Manager for xEV applications until May 2020. From June 2020, he is appointed as a Tenured Assistant Professor in the Power Electronics and EMC group at U Twente.
He has so far published 29 papers with 6 journals and has filed 6 patents which are in various stages of acceptance. His current areas of interest are Electric Vehicles, Wireless Charging, Power Electronics Integration - Semiconductors and Passive Component Technologies.

Title: SaRe Battery Electronics of the Future : Safe and Reliable

Abstract:

Li-ion battery (LiB) has disrupted the world of energy storage thereby creating a pathway for a sustainable future relying on intermittent renewable energy sources. It is expected that the market for LiB will exceed 400 GWh per year from 2025 onwards. The talk will summarize an overview of the R&D program at University of Twente in advanced battery power electronics and battery evaluation. This includes the development of a new generation of advanced BMS concepts based on advanced power electronics. In addition, an overview will be presented of performance and ageing including implications on safety and second-life batteries.
Not found Prof. Anurag K. Srivastava
Fellow IEEE
Chairperson, Professor - Lane, Department of Computer Science and Electrical Engineering, West Virginia University
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Title: AI and Power Grid: Limits, Applications and Path Forward

Abstract:

Availability of data from massive sensors deployment in the cyber-physical electric grid enables new monitoring and control applications. Advancement in artificial intelligence provides an opportunity to develop data-driven technique utilizing these datasets. Some possible applications include, early alarm and diagnosis, predicative analysis, distributed and decentralized control. New applications need to consider physics-induced limits and high- performance requirement in a dynamic environment. Availability of additional sensor data brings its own challenges including data anomalies, real time processing, data fusion, data management and cyber-security management. Differentiating between data anomalies, cyber events and physical system events can be very challenging due to the similar signatures. This talk will focus on AI basics, limits of AI for power grid applications, example of possible applications including real time cyber-power data analytics to enhance situational awareness, and associated challenges and opportunities. Path forward for AI applications for future grid will be also discussed.

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