Prof. Abhijit Sen
Kwantlen Polytechnic University, Canada
Speech Title: Role of Generative AI in Computer Security and Privacy
Abstract:Tailored for both cybersecurity enthusiasts and professionals across diverse backgrounds, thesession aims to explore the transformative influence of Generative AI in safeguarding digitalecosystems. From its innovative applications in threat intelligence, anomaly detection, andauthentication systems to ethical considerations surrounding its use, we will navigate throughthe pivotal role Generative AI plays in shaping the future of cybersecurity. Whether you're aseasoned professional or new to the field, join us as we demystify the intricate intersections ofGenerative AI, computer security, and privacy. The presentation will conclude with a Q&Asession, providing an opportunity to delve deeper into the emerging opportunities andchallenges lying ahead.
Biography: Dr. Abhijit Sen is a Professor of Computing Science and Information Technology at KwantlenPolytechnic University in BC, Canada, holding a Ph.D. from McMaster University, an M.S. degreefrom the University of California, Berkeley, and a B.Tech in Electrical Engineering from the IndianInstitute of Technology, Kharagpur. With over 30 years of experience, Dr. Sen has played pivotalroles in organizations like Canadian Aviation Electronics and Microtel Pacific Research.
His international impact includes positions as a visiting professor at institutions in New Zealand,Germany, India, and China. Dr. Sen is a renowned keynote speaker at international conferences,showcasing thought leadership. He actively contributes to academia, serving as a reviewer andtechnical committee member for various conferences, along with editorial board roles forconference proceedings publications. As an external examiner, he evaluates Ph.D. theses atmultiple universities.
Dr. Sen's research interests encompass Wireless Networking, Security, RFID, ComputingEducation, Distributed Systems, DevOps, and Artificial Intelligence. Recognized for hisdedication, he received the Distinguished Teaching Award from Kwantlen Polytechnic University.A Life Member of IEEE, he has served in the Executive Committee of IEEE, Vancouver Chapter.His contributions have been recognized by the IEEE, Vancouver Chapter, highlighting hisunwavering commitment and individual contributions to the organization.
Prof. Cyrus F Nourani
Akdmkrd-DAI-TU Berlin, Germany
Biography: Cyrus F. Nourani, PhD, has a national and international reputation in computer science, artificial intelligence, mathematics, virtual haptic computation, enterprise modeling, decision theory, data sciences, predictive analytics economic games, information technology, and management science. In recent years he has been engaged as a research professor at Simon Frasier University in Burnaby, British Columbia, Canada, and at the Technical University of Berlin, Germany, and has been working on research projects in Germany, Sweden, and France. He has many years of experience in the design and implementation of computing systems. Dr. Nourani’s academic experience includes faculty positions at the University of Michigan-Ann Arbor, the University of Pennsylvania, the University of Southern California, UCLA, MIT, and the University of California, Santa Barbara. He was a visiting professor at Edith Cowan University, Perth, Australia, and a lecturer of Management Science and IT at the University of Auckland, New Zealand. Dr. Nourani has taught AI to the Los Angeles aerospace industry and has worked in many R&D and commercial ventures. He has written and coauthored several books. He has over 400 publications in computing science, mathematics, and management science, and he has written several books and has edited several volumes on additional topics, such as pure mathematics; AI, EC, and IT management science; decision trees; and predictive economics game modeling. In 1987, he founded Ventures for computing R&D and was a consultant for such clients such as System Development Corporation (SDC), the US Air Force Space Division, and GE Aerospace. Dr. Nourani has designed and developed AI robot planning and reasoning systems at Northrop Research and Technology Center, Palos Verdes, California. He also has comparable AI, software, and computing foundations and R&D experience at GTE Research Labs. Dr. Nourani commenced his university degrees at MIT, where he became interested in algebraic semantics. That was pursued with a world-renowned category theorist at the University of California and Oxford University. Dr. Nourani’s dissertation on computing models and categories proved to have pure mathematics foundations developments that were published from his postdoctoral times in US and Europe publications.
Prof. Loc Nguyen
Sunflower Soft Company, Vietnam
Speech Title: Adversarial Variational Autoencoders to extend and improve generative model
Abstract:Generative artificial intelligence (GenAI) has been developing with many incredible achievements like ChatGPT and Bard. Deep generative model (DGM) is a branch of GenAI, which is preeminent in generating raster data such as image and sound due to strong points of deep neural network (DNN) in inference and recognition. The built-in inference mechanism of DNN, which simulates and aims to synaptic plasticity of human neuron network, fosters generation ability of DGM which produces surprised results with support of statistical flexibility. Two popular approaches in DGM are Variational Autoencoders (VAE) and Generative Adversarial Network (GAN). Both VAE and GAN have their own strong points although they share and imply underline theory of statistics as well as incredible complex via hidden layers of DNN when DNN becomes effective encoding/decoding functions without concrete specifications. In this research, I try to unify VAE and GAN into a consistent and consolidated model called Adversarial Variational Autoencoders (AVA) in which VAE and GAN complement each other, for instance, VAE is good at generator by encoding data via excellent ideology of Kullback-Leibler divergence and GAN is a significantly important method to assess reliability of data which is realistic or fake. In other words, AVA aims to improve accuracy of generative models, besides AVA extends function of simple generative models. In methodology this research focuses on combination of applied mathematical concepts and skillful techniques of computer programming in order to implement and solve complicated problems as simply as possible.
Biography: Loc Nguyen is an independent scholar from 2017. He holds Master degree in Computer Science from University of Science, Vietnam in 2005. He holds PhD degree in Computer Science and Education at Ho Chi Minh University of Science in 2009. His PhD dissertation was honored by World Engineering Education Forum (WEEF) and awarded by Standard Scientific Research and Essays as excellent PhD dissertation in 2014. He holds Postdoctoral degree in Computer Science from 2013, certified by Institute for Systems and Technologies of Information, Control and Communication (INSTICC) by 2015. Now he is interested in poetry, computer science, statistics, mathematics, education, and medicine. He serves as reviewer, editor, speaker, and lecturer in a wide range of international journals and conferences from 2014. He is volunteer of Statistics Without Borders from 2015. He was granted as Mathematician by London Mathematical Society for Postdoctoral research in Mathematics from 2016. He is awarded as Professor by Scientific Advances and Science Publishing Group from 2016. He was awarded Doctorate of Statistical Medicine by Ho Chi Minh City Society for Reproductive Medicine (HOSREM) from 2016. He was awarded and glorified as contributive scientist by International Cross-cultural Exchange and Professional Development-Thailand (ICEPD-Thailand) from 2021 and by Eudoxia Research University USA (ERU) and Eudoxia Research Centre India (ERC) from 2022. He has published 92 papers and preprints in journals, books, conference proceedings, and preprint services. He is author of 5 scientific books. He is author and creator of 9 scientific and technological products.
Prof. Umesh C. Pati
National Institute of Technology, India
Biography:Dr. Umesh C. Pati is a Full Professor at the Department of Electronics and CommunicationEngineering, National Institute of Technology (NIT), Rourkela. He has obtained his B.Tech.Degree in Electrical Engineering from National Institute of Technology (NIT), Rourkela,Odisha. He received both M.Tech. and Ph.D. degrees in Electrical Engineering withspecialization in Instrumentation and Image Processing, respectively, from the Indian Instituteof Technology (IIT), Kharagpur.
His current areas of interest are Internet of Things (IoT), Industrial Automation,Instrumentation Systems, Artificial Intelligence, Image/Video Processing, Computer Vision,and Medical Imaging. He has authored/edited two books and published more than 100 articlesin the peer-reviewed international journals as well as conference proceedings. Dr. Pati has filed2 Indian patents. He has served as a reviewer in a wide range of reputed international journalsand conferences. He also has guest-edited special issues of Cognitive Neurodynamics and theInternational Journal of Signal and Imaging System Engineering. He has delivered manyKeynote/Invited talks in India as well as abroad. Besides other sponsored projects, he iscurrently associated with a high-value IMPRINT project, “Intelligent Surveillance DataRetriever (ISDR) for Smart City Applications,” which is an initiative of the Ministry ofEducation (formerly the Ministry of Human Resource Development) and Ministry of Housingand Urban Affairs, Govt. of India.
He has visited countries like the USA, Australia, Italy, Austria, Singapore, Mauritius,etc., in connection with research collaboration and paper presentation. He was also an academicvisitor to the Department of Electrical and Computer Engineering, San Diego State University,USA, and the Institute for Automation, University of Leoben, Austria. He is a Senior memberof IEEE, Fellow of The Institution of Engineers (India), Fellow of The Institution of Electronicsand Telecommunication Engineers (IETE), and life member of various professional bodies likeMIR Labs (USA), The Indian Society for Technical Education, Instrument Society of India,Computer Society of India, and Odisha Bigyan Academy. His biography has been included inthe 32nd edition of MARQUIS Who’s Who in the World 2015.
Assoc. Prof. Pavel Loskot
ZJU-UIUC Institute, China
Speech Title: Key Ideas in Conformal Predictions
Abstract:Uncertainty quantification plays an important role in obtaining robust models of stochastic systems. When combined with predictive machine learning models, they improve the confidence in predictions by identifying potential problems. Among different techniques for uncertainty quantification involving both parametric and non-parametric methods, the conformal predictions have many advantages such as providing the guaranteed bounds for the true values, and being model and distribution agnostic. Moreover, conformal predictions are relatively easy to use in a wide range of statistical forecasting applications while offering solid theoretical foundations. In this talk, I will outline the key ideas in conformal predictions focusing especially on their use in statistical signal processing and machine learning, and explain how they are used in classification and regression learning tasks.
Biography: Pavel Loskot joined the ZJU-UIUC Institute, Haining, China, in January 2021 as Associate Professor after 14 years being the Senior Lecturer at Swansea University in the UK. He obtained his PhD degree in Wireless Communications from the University of Alberta in Canada, and the MSc and BSc degrees in Radioelectronics and Biomedical Electronics, respectively, from the Czech Technical University of Prague in the Czech Republic. In the past 25 years, he was involved in numerous collaborative research and development projects, and also held a number of consultancy contracts with industry. Pavel Loskot is a Senior Member of the IEEE, a Fellow of the Higher Education Academy in the UK, and the Recognized Research Supervisor of the UK Council for Graduate Education. His current research interests focus on mathematical and probabilistic modeling, statistical signal processing and classical machine learning for multi-sensor data in biomedicine, computational molecular biology, and wireless communications.
Assoc. Prof. Syed Mushhad M. Gilani
University of Agriculture, Pakistan
Biography: Dr. Syed Mushhad Mustuzhar Gilani is an Associate Professor of the Department of Computer Science, an Associate Senior Tutor, a Postgraduate Research Advisor, and convener of the QEC committee and various other committees at the University of Agriculture Faisalabad. He was an Assistant Professor (Computer Sciences) / Research Advisor for Postgraduate Students at PMAS-Arid Agriculture University Rawalpindi from 2012 to 2022. He received his Ph.D. from the School of Computer Science at Chongqing University of Posts and Telecommunication, China. He has published more than 60 papers in peer-reviewed international journals and conferences. He has successfully supervised postgraduate students. He has served as session chair of reputed conferences. He has reviewed many research papers for reputable journals and conferences. He received an excellent Speaker Award at (Ted Talk) Youth Festival 2017 of Chongqing University of Posts and Telecommunication, China. His research interests include Future Internet Architecture, Software Defined Wireless Networks, IoT, and Smart Environments.
Assoc. Prof. Moirangthem Marjit Singh
North Eastern Regional Institute of Science & Technology (NERIST),India
Speech Title: Deep Learning Techniques for Image Classification
Abstract: This invited talk will cover highlights on various Deep Learning (DL) techniques useful for application in Image classification task. The talk will explore some DL based techniques developed for image classification in recent times indicating issues and challenges. The talk will delve into elucidating the research landscape where DL techniques are applied for the purpose of image classification. At the end of the talk, appropriate problem and solution domains will also be deliberated briefly.
Biography: Dr. Moirangthem Marjit Singh is currently an Associate Professor in Computer Science & Engineering Department at North Eastern Regional Institute of Science & Technology (NERIST), Arunachal Pradesh,India. He received B.Tech. and M.Tech. in Computer Science & Engineering degrees from NERIST and was awarded Gold Medal for securing top position in M.Tech. He received his PhD (Engineering) degree in computer Science and Engineering from University of Kalyani, West Bengal,India. He was the Head of the Department of Computer Science and Engineering, NERIST during 2018 to 2022. He was also the founder Honorary Joint Secretary of the Institution of Engineers, Arunachal Pradesh State Centre, India during 2019-2021. Dr. Marjit is a Fellow of IETE New Delhi, India and Fellow of the Institutions of Engineers (India) and the senior member IEEE, USA. Dr. Marjit was honoured with “Academic Excellence Award” by Taylor’s University, Malaysia in recognition of his outstanding academic performance on 13 September 2023 at Taylor’s University in association International Conference on Evolutionary Artificial Intelligence (ICEAI 2023). He was awarded the IE(I) Young Engineers Award 2014–2015 from the Computer Engineering Division, Institution of Engineers, India. He received the Best Paper Awards at international conferences namely the ICEAI 2023(held at Taylors’ University, Malaysia) and the ICACCT 2016, (held at APIIT, India) published by springer.
Dr. Marjit secured First Position in X and Second Position in XII Examinations conducted by CBSE, New Delhi, India, amongst the candidates sent up from Jawahar Navodaya Vidyalayas (JNVs) of North Eastern region states of India, in 1995 and 1997, respectively. He was awarded the Gold Medal for getting top position in the M.Tech.(CSE) at NERIST in 2010 He has more than 20 years of teaching and research experience. He has published several research papers in journals and conferences of repute. He has organized/associated with several technical conferences held in India and abroad. His research interests include mobile adhoc networks, wireless sensor networks, network security, AI, machine learning, and deep learning.
Asst. Prof. Jiaqing Liu
Ritsumeikan University, Japan
Biography: Jiaqing Liu received the B.E. degree from Northeastern University, Shenyang, China, in 2016, and the M.E. and D.E. degrees from Ritsumeikan University, Kyoto, Japan, in 2018 and 2021, respectively. From 2020 to 2021, he was a JSPS Research Fellowship for Young Science. From October 2021 to March 2022, he was a Specially Appointed Assistant Professor with the Department of Intelligent Media, ISIR, Osaka University, Osaka, Japan. He is currently an Assistant Professor with the College of Information Science and Engineering, Ritsumeikan University. His research interests include pattern recognition, image processing, and machine learning.
Dr. Abhimanyu Mukerji
Amazon.com, Inc., United States
Biography: Abhimanyu is a Senior Economist at Amazon working on dynamic causal models and causal machine learning. His prior research has used methods from machine learning, deep learning and natural language processing combined with econometric approaches to study problems in applied microeconomics and empirical corporate finance. He holds a PhD in financial economics from Stanford University.