Professor Dr. Saifur Rahman
Professor Dr. Saifur Rahman

IEEE Life Fellow;
2022 IEEE President-Elect, 2023 IEEE president;
Past President, IEEE PES;
Joseph R. Loring Professor of Electrical And Computer Engineering, Virginia Tech, USA;
Founding Director, Virginia Tech Advanced Research Institute, USA.

Keynote Title: How Can a Smart Power Grid Help to Integrate Diverse Sources of Generation and Storage.

With the focus on environmental sustainability and energy security, power system planners are looking at renewable energy and storage as supplements and alternatives. But such generation sources have their own challenges – primarily intermittency.  It is expected that the smart grid – due to its inherent communication, sensing and control capabilities – will have the ability to manage the load, storage and generation assets (including renewables) in the power grid to enable a large-scale integration of distributed generation. In a smart grid, information about the state of the grid and its components can be exchanged quickly over long distances and complex networks. It will therefore be possible to have the integration of sustainable energy sources, such as wind, solar, off-shore electricity, etc. for smoother system operation. 

The future electric utility will become an intelligent provider of these services. This lecture introduces the operational characteristics of renewable energy sources, and various aspects of the smart grid – technology, standards and regulations. It also addresses the interplay among distributed generation, storage and conventional generation to provide an efficient operational strategy in the context of the smart grid.

ICCIT, Bangladesh

19 December 2022

Professor Saifur Rahman is the founding director of the Advanced Research Institute at Virginia Tech, USA where he is the Joseph R. Loring professor of electrical and computer engineering. He also directs the Center for Energy and the Global Environment. He is a Life Fellow of the IEEE and an IEEE Millennium Medal winner.  He is the 2022 IEEE President-elect and was the president of the IEEE Power and Energy Society (PES) for 2018 and 2019. He was the founding editor-in-chief of the IEEE Electrification Magazine and the IEEE Transactions on Sustainable Energy. He has published over 150 journal papers and has made over four hundred conference and invited presentations. He is the founder of BEM Controls, LLC, a Virginia (USA)-based software company providing building energy management solutions.  He has conducted several energy efficiency, blockchain and sensor integration projects for Duke Energy, Tokyo Electric Power Company, the US National Science Foundation, the US Department of Defense, the US Department of Energy and the State of Virginia. He has a PhD in electrical engineering from Virginia Tech. 

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Dr. Luis Kun
Dr. Luis Kun

2022 IEEE President Elect for the Society for Social Implications of Technology (SSIT)
Distinguished Professor Emeritus, National Security (CHDS/NDU).

Keynote Title: Climate Change Effects in Bangladesh’s Healthcare & Public Health 2022 Dynamics.

According to the World Health Organization, Climate change is the single biggest health threat currently facing humanity and the impacts are already harming health through air pollution, disease, extreme weather events, forced displacement, food insecurity and pressures on mental health. Every year, environmental factors alone, take the lives of around 13 million people.  Extreme weather events in addition are causing greater damage than ever before (i.e., stronger: winds, hurricanes, tornados, monsoons) which affects both physical and mental health.  In a world still coping with the effects of COVID-19, the war between Russia and Ukraine, and the daily increase in both world population and urbanization, the world faces many different risks from a large number of interconnected vulnerabilities that are generated simultaneously.  A third of Pakistan is under water for months now, affecting 33 million people and there is no dry land where to drain it.  Not only there is no possibility of agriculture production which can cause food insecurity in many other nations, but all type of potential diseases including: cholera, malaria and dengue from bacteria and the billions of mosquitos, are creating a public health nightmare for authorities.  Meanwhile in East Africa, 22 million people are at risk of famine due to drought and in the US farmers and ranchers have to make decision in respect to what to plant and or to get rid of their cattle because of droughts and no water available for those purposes.  In the west, Hoover Dam has very little water left which causes problems with availability of hydroelectric power, drinking water in Las Vegas, and water for agriculture in California. Increased water levels in our oceans are causing people to flee from coastal areas to more secure ones, mostly urban areas. These moves increases population density which in turn increases the possibilities of spreading infectious diseases.

Dr. Luis Kun is the 2022 IEEE President Elect for the Society for Social Implications of Technology and a Distinguished Professor Emeritus of National Security (CHDS/NDU). Born in Montevideo, he graduated from the Merchant Marine Academy in Uruguay and holds a BSEE, MSEE, and PhD degree in BME, all from UCLA.  He is an IEEE Life Fellow, a Fellow of the American Institute for Medical and Biological Engineering, the International Academy of Medical and Biological Engineering, and the International Union for Physical and Engineering Sciences in Medicine. He is the founding Editor in Chief of Springer’s Journal of Health and Technology 2010-2020. He spent 14 years at IBM and was the Director of Medical Systems Technology at Cedars Sinai Medical Center. As Senior IT Advisor to AHCPR, he formulated the IT vision and was the lead staff for High Performance Computers and Communications program and Telehealth. In July 1997, he was an invited speaker to the White House and was largely responsible for the first Telemedicine Homecare Legislation signed by President Clinton in August 1997. As a Distinguished Fellow at the CDC and an Acting Chief IT Officer for the National Immunization Program, he formulated their IT vision on 10/2000. Dr. Kun received many awards including: AIMBE’s first-ever Fellow Advocate Award in 2009; IEEE-USA Citation of Honor Award with a citation, “For exemplary contributions in the inception and implementation of a health care IT vision in the US.” In 2009, he was named “Professor Honoris Causa” by Favaloro University, (Argentina) and “Distinguished Visitor” by City of Puebla, Mexico in 2013.  He served as the IEEE Distinguished Visitor for the CS and as a Distinguished Lecturer (DL) for the Engineering in Medicine and Biology Society (EMBS) and SSIT where he chairs the DL Program since 2016. Since 2014, he serves as an Honorary Professor of the Electrical Engineering Department at the School of Engineering of the University (UDELAR) in Montevideo, Uruguay.  He received the Medal of Merit in October, 2016 in Mexico by the National Unit of Engineering Associations and was named Visiting Professor by the National Technological University of Buenos Aires, Argentina in October 2017.

Prof. Dr. Mohamed-Slim Alouini
Prof. Dr. Mohamed-Slim Alouini

Fellow, IEEE;
Distinguished Professor, Electrical and Computer Engineering & Associate Vice President for Research, Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology (KAUST), Saudi Arabia.

Keynote Title: A light in digital darkness: Free space optics to connect the unconnected.

Despite the ubiquitous digital connectivity that we experience all around us, it is a fact that almost third of the population of the world is still “offline” due to the lack of a robust Internet and communications infrastructure in many places on the globe. The reason why such digitally dark spots still exist in the world is mainly two-folds. For one, economically backward or thinly scattered populations are not viable for relatively larger investments in communications infrastructure. Secondly, a hostile geography/terrain raises the cost of installing optical fibers and other equipment. Thus, it’s no wonder that many big Internet giants such as Amazon, Facebook, and SpaceX, have attempted to reach the hitherto “digitally inaccessible” regions by providing connectivity through satellites or high-altitude platforms (HAPs). A constellation of satellites/HAPs provides a more cost-effective and reliable alternative to the deployment of optical fiber and related equipment in such locations of the world. Because of the large chunks of relatively unlicensed bandwidth available in the optical spectrum, there is a great opportunity to use lasers for ground gateway station-satellite/HAPs, and inter-satellite or inter-HAP communications, a communications model known as the free-space optics (FSO). Towards that end, this talk examines the FSO communications from the perspective of satellite and HAP communications. In this regard, some new pointing, acquisition and tracking aspects are presented. Furthermore, this talk goes also through the adaptive optics and relaying schemes that are needed to deal with atmospheric turbulence which affects such kind of networks.

Mohamed-Slim Alouini was born in Tunis, Tunisia. He received the Ph.D. degree in Electrical Engineering from the California Institute of Technology (Caltech) in 1998. He served as a faculty member at the University of Minnesota then in the Texas A&M University at Qatar before joining the King Abdullah University of Science and Technology (KAUST) in 2009. He is a Distinguished Professor of Electrical and Computer Engineering at KAUST. Prof. Alouini is a Fellow of the IEEE and OPTICA (Formerly the Optical Society of America (OSA)). He is currently particularly interested in addressing the technical challenges associated with the uneven distribution, access to, and use of information and communication technologies in rural, low-income, disaster, and/or hard-to-reach areas. 



Dr. Mohammad S. Alam
Dr. Mohammad S. Alam

Texas A&M University - Kingsville, Texas, USA

Keynote Title: Multimodal Imaging Based Recognition and Tracking.

In this keynote, we plan to cover the latest trends in multimodal imaging based techniques for efficient pattern recognition and tracking. Test results using real life imagery will be presented to verify the effectiveness of the proposed techniques.

Prof. Mohammad S. Alam received his BS and MS degrees in electrical and electronic engineering from the Bangladesh University of Engineering and Technology (BUET) in 1983 and 1985, his MS degree in computer engineering from the Wayne State University in 1989, and his Ph.D. degree in electrical engineering from the University of Dayton in 1992. He served as the Special Assistant to the Vice President for Research and Graduate Studies at Texas A&M University – Kingsville (TAMUK) and as the Dean of the Frank H. Dotterweich College of Engineering at TAMUK during 2016-2022. Prior to joining TAMUK, he served as the Chair of the Department of Electrical and Computer Engineering at the University of South Alabama during 2001-2015, and as the first Warren H. Nicholson Endowed Chair Professor of Electrical and Computer Engineering in 2016. He served on the faculty of BUET, Purdue University – Fort Wayne, and the University of Alabama. He also served as a Graduate Faculty member of Purdue University and Indiana University.

His research interests include image processing, pattern recognition, renewable energy, smart energy management and control, and ultrafast computing. He authored or co-authored 200+ refereed journal papers, 335+ conference publications, and 18 book chapters. He edited a reference book of selected papers on JTC (SPIE Press) and many conference proceedings. Over 8,400 citations of his work have been reported in the Google Scholar (h-index: 44, i10-index: 152) and 36,000+ reads in ResearchGate. He received numerous excellence in research/teaching/service awards including the 1998 Outstanding Engineer Award from Region 4 of IEEE, 2013 Outstanding Engineer Award from Region 3 of IEEE, and 2016 Joseph M. Biedenbach Outstanding Engineering Educator Award from Region 3 of IEEE. He is listed in the world’s top 2% scientists across all fields in 2021.

Prof. Alam served/serves as the PI or Co-PI of many research projects totaling over $17M, funded by NSF, NASA, FAA, DoE, ARO, AFOSR, AFRL, SMDC, Wright-Patt AFB, Alabama Department of Commerce, British Petroleum, nfina Technologies, Radiance Tech, and ITT industry. He presented over 125 keynote addresses, invited papers, seminars and tutorials at international conferences and research institutions in the US and abroad. He has organized and chaired many international conferences and served as a Guest Editor for several professional journals. He supervised the research work of 55+ Masters/Ph.D. students, 17 post-doctoral students, and 7 visiting scholars. Prof. Alam serves as an ABET evaluator for domestic and international institutions.

Prof. Alam is an elected Fellow of eleven professional societies: Institute of Electrical and Electronics Engineers (IEEE), Institution of Engineering and Technology (IET), Optical Society of America (OSA), SPIE – the International Society for Optical Engineering, Institute of Physics (IoP), Society for Imaging Science & Technology (IS&T), International Association for Pattern Recognition (IAPR), Asia-Pacific Association for Artificial Intelligence (AAIA), American Association for Advancement of Science (AAAS), Bangladesh Computer Society (BCS), and the Institution of Engineers Bangladesh (IEB). He serves as an OSA Fellows Travelling Lecturer. He served as the Chairman of the Fort Wayne Section of IEEE during 1995-1996 and as the President of the Mobile Section of IEEE during 2012-2016. He also served as the President of the Southeastern ECE Department Heads Association (SECEDHA) during 2005 – 2006.

Prof. Dr. Mohammad A. Karim
Prof. Dr. Mohammad A. Karim

Fellow - IEEE, IET, OSA, SPIE, IoP;
University of Massachusetts - Dartmouth, USA

Keynote Title: Peer-Reviewed Research and Ranking: A Bangladesh Context.

This keynote will focus on the specifics, trends, and drivers that are of consequence to the ranking of both public and private universities in Bangladesh. Comparative data for neighboring countries will be highlighted.

Mohammad Karim is a professor of electrical and computer engineering at the University of Massachusetts Dartmouth. Until recently, he served as the University’s Executive Vice Chancellor, Provost and Chief Operating Officer for 7+ years. Previously, he was Vice President for Research of Old Dominion University, Dean of Engineering at the City University of New York, Head of Electrical and Computer Engineering at the University of Tennessee Knoxville, Director of Electro-Optics and Chair of Electrical and Computer Engineering at the University of Dayton. Professor Karim is an author/co-author of 19 books, 13 book chapters, and over 360 peer-reviewed articles. He is an elected fellow of multiple professional societies including Institute of Electrical and Electronics Engineers (IEEE). The list of his research sponsors includes Office of Naval Research, National Science Foundation, US Air Force, Naval Research Laboratory, US Army, NASA, US Department of Education, Ohio Aerospace Institute, US Department of Defense, and Avionics Laboratory of Wright-Patterson Air Force Base.

He received BSc Honors in Physics from Dacca University in 1976 and MS in Physics, MS in Electrical Engineering, and PhD from the University of Alabama respectively in 1978, 1979, and 1982.

Professor Dr. Latifur Khan
Professor Dr. Latifur Khan

Fellow of IEEE, IET, BCS;
Department of Computer Science, University of Texas at Dallas (UT Dallas), USA.

Keynote Title: Semi-Supervised Learning, Life Long Learning and Scalable Spatio-Temporal Graph Neural Networks for Social Good.

In this presentation, I will focus on Semi-supervised learning, lifelong learning and spatio-temporal forecasting.  

With regard to semi-supervised learning, various efforts have been proposed for reducing the annotation cost when training Deep neural networks (DNN). Semi-Supervised Learning (SSL) is one of the solutions that has been provably handy in leveraging unlabeled instances to mitigate the efficacy of the DNN model’s performance and has been attracting an increasing amount of attention in recent times. In this work, our main insight is that semi-supervised learning can benefit from the recently proposed unsupervised contrastive learning approach, which aims to achieve the positive concentrated and negative separated representation in the unlabeled feature space. Herein, we introduce MultiCon, a semi-supervised learning paradigm that aims at learning data augmentation invariant based embedding. Experiments on multiple standard datasets including Covid19 Chest X-ray images, and CT Scans demonstrate that MultiCon achieves state-of-the-art performance across existing SSL benchmarks. In addition, we will demonstrate how semi-supervised learning can be used to identify Choroidal Tumors in Fundus Photographs and find vulnerable functions in application libraries. 

With regard to lifelong learning, we will monitor conflicts and political violence around the world by analyzing volumes of continuous or stream specialized text on a global scale. To help advance research in political science, we introduce ConfliBERT, a domain-specific pre-trained language model for conflict and political violence. We first gather a large domain-specific text corpus for language modeling from various sources. We then build ConfliBERT using two approaches: pre-training from scratch and continual pre-training to facilitate lifelong learning.  For incremental/continual learning, deep learning models should be able to learn new information while retaining previously learned skills or knowledge, but catastrophic forgetting does happen and we will address that in this talk.

Time series forecasting with additional spatial information has attracted a tremendous amount of attention in recent research, due to its importance in various real-world applications in social studies, such as conflict prediction and pandemic forecasting. Conventional machine learning methods either consider temporal dependencies only or treat spatial and temporal relations as two separate autoregressive models, namely, space-time autoregressive models. Such methods suffer when it comes to long-term forecasting or predictions for large-scale areas, due to the high nonlinearity and complexity of spatio-temporal data. In this talk, we describe how to address these challenges using spatio-temporal graph neural networks. 

*This work is funded by NSF, NIH, ARMY, ONR, and NSA. The work (ConflictBERT) is in collaboration with Dr. Patrick Brandt and Dr. Jennifer Holmes, School of Economic, Political and Policy Sciences, UT Dallas.

Dr. Latifur Khan is currently a full Professor (tenured) in the Computer Science department at the University of Texas at Dallas, USA where he has been teaching and conducting research since September 2000. He received his Ph.D. degree in Computer Science from the University of Southern California (USC) in August of 2000. In addition, he received his bachelor degree in Computer Science and Engineering (CSE) from Bangladesh University of Engineering and Technology (BUET) with first class honors (2nd position).

Dr. Khan is a fellow of IEEE, IET, BCS, and an ACM Distinguished Scientist. He has received prestigious awards including the IEEE Technical Achievement Award for Intelligence and Security Informatics, IEEE Big Data Security Award, and IBM Faculty Award (research) 2016. Dr. Khan has published over 300 papers in premier journals and prestigious conferences. Currently, Dr. Khan’s research focuses on big data management and analytics, data mining and its application to cyber security, and complex data management including geospatial data and multimedia data. His research has been supported by grants from NSF, NIH, the Air Force Office of Scientific Research (AFOSR), DOE, NSA, IBM, and HPE.  More details can be found at