Joydeep Mitra (Ph.D., FIEEE) is Associate Professor of Electrical Engineering at Michigan State University, East Lansing, Director of the Energy Reliability & Security (ERiSe) Laboratory, and Senior Faculty Associate at the Institute of Public Utilities. He received a Ph.D. in Electrical Engineering from Texas A&M University, College Station, and a B.Tech.(Hons.) in Electrical Engineering from Indian Institute of Technology, Kharagpur. Prof. Mitra has conducted research in power system modeling, analysis, stability, control, planning and simulation, and is known for his contributions to power system reliability analysis and reliability-based planning. He has over 200 publications and patents in the power systems area; he is co-author of the book, "Electric Power Grid Reliability Evaluation: Models and Methods," and of IEEE Standard 762, a standard on reliability reporting. He is recipient of the 2019 IEEE-PES Roy Billinton Power System Reliability Award. Prof. Mitra's research has been funded by the U.S. National Science Foundation, the U.S. Department of Energy, U.S. National Laboratories, and several electric utilities. Prof. Mitra is a Fellow of the IEEE. He serves as an Associate Editor for the IEEE Transactions on Power Systems and Power Engineering Letters, and for the IEEE Transactions on Industry Applications. In the past he has served as Chair of the IEEE-PES Analytic Methods for Power Systems Committee, Chair of several IEEE-PES Subcommittees, and as an Editor for the IEEE Transactions on Smart Grid. Prof. Mitra engages actively in several IEEE activities such as organizing conference tracks and contributing to the development of IEEE standards.
"Energy Assurance with Renewable Generation"
Since the beginning of this century we have witnessed an acceleration in the adoption of renewable energy resources and technologies. Various forces – social, political, economic, regulatory and technological – have conspired to create a climate that fosters the development and proliferation of numerous technologies that enable the conversion, control and integration of renewable energy resources.Although the mix of renewable resources is diverse, ranging from wind and solar to tidal and biomass, the bulk of today’s investments are going into wind and solar, both of which are considered variable resources because they are available not upon demand, but upon the whims of nature. This creates several challenges and opportunities in exploiting their benefits, both when operating them in isolation and when operating them in coordination withother resources. Numerous solutions have been proposed for mitigating the challenges, ranging from storage and transmission expansion to demand response and “smart grid” control technologies. This talk will discuss the most significant factors affecting energy assurance in the presenceof renewable generation. It will investigate the use of energy storage to mitigate some of the challenges. It will discuss reliability metrics and targets, and a method for quantifying the notion of "firming" up an intermittent resource. Effects of resource availability and network constraints will be considered. The presentation will conclude with a discussion of another characteristic of renewable resources – low inertia – and how it impacts system reliability, and of ongoing research toward developing solutions for mitigating these impacts.
Nikhil R. Pal is a Professor in the Electronics and Communication Sciences Unit of the Indian Statistical Institute. His current research interest includes brain science, computational intelligence, machine learning and data mining. He was the Editor-in-Chief of the IEEE Transactions on Fuzzy Systems for the period January 2005-December 2010. He has served/been serving on the editorial /advisory board/ steering committee of several journals including the International Journal of Approximate Reasoning, Applied Soft Computing, International Journal of Neural Systems, Fuzzy Sets and Systems, IEEE Transactions on Fuzzy Systems and the IEEE Transactions on Cybernetics. He is a recipient of the 2015 IEEE Computational Intelligence Society (CIS) Fuzzy Systems Pioneer Award, He has given many plenary/keynote speeches in different premier international conferences in the area of computational intelligence. He has served as the General Chair, Program Chair, and co-Program chair of several conferences. He was a Distinguished Lecturer of the IEEE CIS (2010-2012, 2016-2018.) and was a member of the Administrative Committee of the IEEE CIS (2010-2012). He has served as the Vice-President for Publications of the IEEE CIS (2013-2016). He is serving as the President of the IEEE CIS (2018-2019). He is a Fellow of the National Academy of Sciences, India, Indian National Academy of Engineering, Indian National Science Academy, International Fuzzy Systems Association (IFSA), The World Academy of Sciences, and a Fellow of the IEEE, USA.
"Can we make Neural Networks a bit more understandable and biologically plausible?"
In the recent past there have been several success stories of AI systems, often beating human performance. In many cases, neural networks, in particular deep neural networks, are the main pillars of such systems. But are these systems comprehensible and/or biologically plausible? In most cases, they are not! In my view, comprehensibility of a system depends, at least, on the following: simplicity, transparency, explainability, trustworthiness, and the biological plausibility of such systems. Ideally, we should strive for realizing all these attributes in any intelligent system, but this is very difficult. So I shall follow an easier path to describe how these attributes may be realized separately. I shall illustrate each case with examples.
Vincenzo Piuri has received his Ph.D. in computer engineering at Politecnico di Milano, Italy (1989). He is Full Professor in computer engineering at the UniversitàdegliStudi di Milano, Italy (since 2000). He has been Associate Professor at Politecnico di Milano, Italy and Visiting Professor at the University of Texas at Austin and at George Mason University, USA. His main research interests are:artificial intelligence, computational intelligence, intelligent systems, machine learning, pattern analysis and recognition, signal and image processing, biometrics, intelligent measurement systems, industrial applications, digital processing architectures, fault tolerance, dependability, and cloud computing infrastructures. Original results have been published in more than 400 papers in international journals, proceedings of international conferences, books, and book chapters. He is Fellow of the IEEE, Distinguished Scientist of ACM, and Senior Member of INNS. He has been IEEE Vice President for Technical Activities (2015), IEEE Director, President of the IEEE Computational Intelligence Society, Vice President for Education of the IEEE Biometrics Council, Vice President for Publications of the IEEE Instrumentation and Measurement Society and the IEEE Systems Council, and Vice President for Membership of the IEEE Computational Intelligence Society. He is Editor-in-Chief of the IEEE Systems Journal (2013-19), and Associate Editor of the IEEE Transactions on Cloud Computing and IEEE Access, and has been Associate Editor of the IEEE Transactions on Computers, the IEEE Transactions on Neural Networks and the IEEE Transactions on Instrumentation and Measurement. He received the IEEE Instrumentation and Measurement Society Technical Award (2002). He is Honorary Professor at:Obuda University, Hungary; Guangdong University of Petrochemical Technology, China;Northeastern University, China; Muroran Institute of Technology, Japan; and the Amity University, India.
“Artificial Intelligence for Cloud and IoT Infrastructures”
Recent years have seen a growing interest among users in the migration of their applications to the Cloud computing and Internet-of-Things environments. However, due to high complexity, Cloud-based and Internet-of-Things infrastructures need advanced components for supporting applications and advanced management techniques for increasing the efficiency. Adaptivity and autonomous learning abilities become extremely useful to support configuration and dynamic adaptation of these infrastructures to the changing needs of the users as well as to create adaptable applications. This self-adaptation ability is increasingly essential especially for non expert managers as well as for application designers and developers with limited competences in tools for achieving this ability. Artificial intelligence is a set of techniques which greatly can improve both the creation of applications and the management of these infrastructures. This talk will discuss the use of artificial intelligence in supporting the creation of applications in cloud and IoT infrastructures as well as their use in the various aspects of infrastructure management.
Prof Dharmendra Sharma is a career academic and researcher. His PhD is in Artificial Intelligence from the Australian National University. He obtained his undergraduate and postgraduate qualifications from the University of the South Pacific, where he was an academic for over 20 years prior to moving to take up an academic appointment at University of Canberra in 2001. He then completed his postgraduate qualifications in computer science from the University of New South Wales prior to completing his PhD at ANU. He has held several leadership positions including deanship. Currently, he is Chair of University Academic Board, and concurrently holds a distinguished professor position. He is also a member of FNU, University of Canberra Council and has been an external advisor to USP for several years. He has published over 310 research papers and has won several competitive research grants, and has produced over 35 higher degrees by research students. He has been a respected leader in academia and in university administration for over 26 years. He received the Australian Order in the recent Queen's Birthday Honours for his services to computer science and to higher education
“AI Futures: Hope or Hype”
The modern world seems to have concerns about the hype AI is generating that it will take over the world. Is it a myth or reality? Is it the 4th industrial revolution? How is it impacting on our social, political and other structures that define our way of life? Will it indeed improve the quality of life? Is there improved hope through this digital revolution? Are we on our way to technical singularity? Will it render us, the human kind, irrelevant? These are some of the questions this keynote will attempt to address. There will an opportunity to discuss the future that AI offers and how we imagine it could, through digital creativity and disruption, create a culture of sharing a global knowledge base through cyberspace to lead to creation of a borderless, harmonious and singular, ‘flat’ modern world that would be intellectually challenging and that would improve the quality of life.
Valentina Emilia Balas is currently full Professor in the Department of Automatics and Applied Software at the Faculty of Engineering, “Aurel Vlaicu” University of Arad, Romania. She holds a Ph.D. in Applied Electronics and Telecommunications from Polytechnic University of Timisoara. Dr. Balas is author of more than 250 research papers in refereed journals and International Conferences. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. She is the Editor-in Chief to International Journal of Advanced Intelligence Paradigms (IJAIP) and to International Journal of Computational Systems Engineering (IJCSysE), member in Editorial Board member of several national and international journals and is the director of Intelligent Systems Research Centre in Aurel Vlaicu University of Arad. She is a member of EUSFLAT, SIAM and a Senior Member IEEE, member in TC –Fuzzy Systems (IEEE CIS), member in TC – Emergent Technologies (IEEE CIS),member in TC – Soft Computing (IEEE SMCS).
“Trends and Challenges in Bio-Inspired Architectures for Nanotechnology”
The lecture presents new research directions of our team in the realm of Brain-Inspired Nano Architecture for integrated circuits in order to achieve low power consumption and high reliability computing for the devices of the future. Computers and brains differ significantly at all scales. Brains are organized of neurons filled with salt water and different organic compounds, whereas computer consists of metals and semiconductors. Neurons can communicate based on electrochemical activity, whereas computers use electrical information “0” and “1”. Neurons are organized in highly interconnected complex circuits, much more than any electronic circuit used in computing. Our approach is dealing with the gated ion channels which can be considered the nano-switches of the brain. This will allow us to analyze the statistical behavior of arrays of such brain-inspired devices. Moore and Shannon introduced a particular class of two-terminal networks, known as hammock networks. These kinds of networks are potentially important to applications in nanoelectronics as well as in biology. Taking inspiration from axon communication, which relies on ion channels distributed on cylindrical structures, we introduce a generalization of the classical hammock networks. We focus on evaluating reliability in the case of two terminal networks.
Prof. Marcin Paprzycki is an Associate Professor at the Systems Research Institute, Polish Academy of Sciences. He is also a member of the Advisory Board of the G1ANT. He has an MS from Adam Mickiewicz University in Poznań, Poland, a Ph.D from Southern Methodist University in Dallas, Texas, and a Doctor of Science from the Bulgarian Academy of Sciences. He is a senior member of IEEE, a senior member of ACM, a Senior Fulbright Lecturer, and an IEEE CS Distinguished Visitor. He has contributed to more than 450 publications and was invited to the program committees of over 500 international conferences. He is on the editorial boards of 15 journals.
“Introduction to Robotic Process Automation”
Recently, trend to ``robotize'' various types of repetitive operations is accelerating. As a typical example, we learn about robot-controlled warehouses, or production lines. Here, while Tesla’s problems with ``too many robots'' bring some interesting questions, the trend is clear and irreversible. However, robots appear also in different contexts. Consider, for instance, an ``invoice processing center'', in which workers (1) select a file folder (located on their computer or in the company server/cloud); (2) open a file located in this folder; (3) copy selected number(s), from this file, to a spreadsheet; (4) close the file; (5) repeat steps (2) and (3) until all files form the selected folder have been opened/processed; (6) a formula in the spreadsheet produces some number(s); workers (7) copy resulting number(s) into predefined field(s) in the database (interfaced from an interface opened in another window); (8) go to step (1) and repeat the process for another folder. There exists large number of business centers, where hundreds of workers do this every day. Obviously, it is easy to envision that such repetitive business processes, could be software-completed. Until recently, system integration was the answer. However, completing ``full-scale system integration'' was very complex and very costly. Moreover, it took a lot of time to complete. This was particularly the case when large number of artifacts had to be integrated. There are well-known cases, when integration was a ``never ending story'', as each time the integration process was in its final stages, business process had to change, and integration had to be restarted. In response to this, Robotic Process Automation (RPA) was proposed. Here, instead of performing integration of system modules (e.g. using Enterprise Service Bus), lightweight scripts are introduced, which work exactly as the human would. In other words, software robot clicks the same window as the worker does, copies the same data from one window to another, sends (the same) mail by clicking within the mail application window, mimicking the way human workers use keyboard and mouse. Of course, such ``scripts'' can be introduced also at other levels of the system that is being integrated (not necessarily repeating the keyboard and mouse processes), but the main ``algorithm'' remains the same: find repeatable processes, use some lightweight approach to capture their nature and replace actions undertaken by a human by those undertaken by a computer. The aim of the talk will be to introduce audience to the Robotic Process Automation. Presented material will be grounded in experiences of G1ANT, a robotic process automation company.