International Conference On Big Data, Machine Learning and Applications
NATIONAL INSTITUTE OF TECHNOLOGY SILCHAR
December 19-20, 2021
The Best Paper Award goes to paper ID 131, Paper Title: AI visualization in Nanoscale Microscopy; Authors: A. Rajagopal, V. Nirmala , Andrew.J , Arun Muthuraj Vedamanickam. Congratulations!
International Conference on Big Data, Machine Learning, and Applications (BigDML 2021) focuses on both theory and applications in the broad areas of Big Data and Machine Learning. This conference aims to bring together the academia, researchers, developers and practitioners from scientific organizations and industry to share and disseminate recent research findings in the fields of Big Data, Machine Learning and its applications. BigDML is an outstanding platform to discuss the key findings, exchanging novel ideas, listening to the world class leaders and sharing experiences with peer groups. The conference will provide the opportunities of collaboration with national and international organization of repute to the research community. BigDML expects a large number of participants and submissions from worldwide.
All the accepted and presented papers will proposed to be published in Lecture Notes in Networks and Systems - Springer, Proceedings Series. The papers will be indexed in SCOPUS, INSPEC, WTI Frankfurt eG, zbMATH, SCImago.
Prof. Dimitris I. Fotiadis (Fellow, IEEE) was born in Ioannina, Greece in 1961. He received the Diploma degree from the National Technical University of Athens, Athens, Greece, in 1985, and the Ph.D. degree from the University of Minnesota, Minneapolis, MN, USA, in 1990, respectively, all in chemical engineering. He is currently a Professor of Biomedical Engineering in the Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece, where he is also the Director of the Unit of Medical Technology and Intelligent Information Systems, and is also an Affiliated Member of the Foundation for Research and Technology Hellas, Institute of Molecular Biology and Biotechnology, Department of Biomedical Research. He was a Visiting Researcher at the RWTH, Aachen, Germany, and the Massachusetts Institute of Technology, Cambridge, MA, USA. He has coordinated and participated in more than 200 R&D funded projects (in FP6, FP7, H2020, and national projects), being the coordinator and technical coordinator in several of them. Prof. Fotiadis is an IEEE EMBS Fellow, EAMBES Fellow, Fellow of IAMBE, member of the IEEE Technical Committee of Information Technology in Healthcare, Editor-in-Chief of IEEE Journal of Biomedical and Health Informatics, Associate Editor of IEEE Reviews in Biomedical Engineering, IEEE Open Journal in Engineering in Medicine and Biology, and Computers in Biology and Medicine. His current research interests include multiscale modeling of human tissues and organs, intelligent wearable/implantable devices for automated diagnosis, processing of big medical data, machine learning, sensor informatics, image informatics, and bioinformatics. He is the recipient of many scientific awards including the one by the Academy of Athens.(Based on document published on 15 June 2020).
Talk title: AI in the fight against epidemic crisis and unmet needs in healthcare through the curation, augmentation, and federated analysis of heterogeneous medical data.
Prof. Ruslan Salakhutdinov received his PhD in machine learning (computer science) from the University of Toronto in 2009. After spending two post-doctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an Assistant Professor in the Department of Computer Science and Department of Statistics. In February of 2016, he joined the Machine Learning Department at Carnegie Mellon University. Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research and served on the senior programme committee of several learning conferences including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, Microsoft Research Faculty Fellow, Canada Research Chair in Statistical Machine Learning, a recipient of the Early Researcher Award, Connaught New Researcher Award, Google Faculty Award, Nvidia's Pioneers of AI award, and is a Senior Fellow of the Canadian Institute for Advanced Research.
Prof. Willy Susilo Willy Susilo is a Distinguished Professor, an IEEE Fellow, an IET (Institution of Engineering and Technology) Fellow, and an ACS (Australian Computer Society) Fellow at the School of Computing and Information Technology, Faculty of Engineering and Information Sciences in University of Wollongong, Australia.
He is the director of Institute of Cybersecurity and Cryptology (iC2), School of Computing and Information Technology, University of Wollongong. Prof. Willy is an innovative educator and researcher.
Currently, he is the Head of School of Computing and Information Technology at UOW (2015 - now). Prior to this role, he was awarded the prestigious Australian Research Council Future Fellowship in 2009. He was the former Head of School of Computer Science and Software Engineering (2009 - 2010) and the Deputy Director of ICT Research Institute at UOW (2006 - 2008).
He is the Editor in Chief of the Computers Standards and Interface (Elsevier) and Information (MDPI) journal. He has served as an Associate Editor in IEEE Transactions in Information Forensics and Computing and he is currently serving as an Associate Editor in IEEE Transactions in Dependable and Secure Computing.
Prof. Willy obtained his PhD from the University of Wollongong in 2001. He has published more than 500 research papers in journals and conference proceedings in cryptography and network security.
He has served as the program committee member in dozens of international conferences.
In 2016, he was awarded the ”Researcher of the Year” award at UOW, due to his research excellence and contributions. His work on the creation of short signature schemes has been well cited and it is part of the IETF draft.
In 2019, he was awarded the "Supervisor of the Year" award at UOW, due to his excellent supervision and mentoring experience.
In 2020, he was awarded the "Vice Chancellor’s Award for Global Strategy" for his contribution to the University's internationalisation and global strategy.
Prof. Ponnuthurai Nagaratnam Suganthan finished schooling at Union College (Tellippalai, Jaffna) and subsequently received the B.A degree, Postgraduate Certificate and M.A degree in Electrical and Information Engineering from the University of Cambridge, UK in 1990, 1992 and 1994, respectively. He received an honorary doctorate (i.e. Doctor Honoris Causa) in 2020 from University of Maribor, Slovenia. After completing his PhD research in 1995, he served as a pre-doctoral Research Assistant in the Dept. of Electrical Engineering, University of Sydney in 1995–96 and a lecturer in the Dept. of Computer Science and Electrical Engineering, University of Queensland in 1996–99. He moved to Singapore in 1999. He was an Editorial Board Member of the Evolutionary Computation Journal, MIT Press (2013-2018) and an associate editor of the IEEE Trans on Cybernetics (2012 - 2018). He is an associate editor of Applied Soft Computing (Elsevier, 2018- ), Neurocomputing (Elsevier, 2018- ), IEEE Trans on Evolutionary Computation (2005 - ), Information Sciences (Elsevier, 2009 - ), Pattern Recognition (Elsevier, 2001 - ) and IEEE Trans. on SMC: Systems (2020 - ). He is a founding co-editor-in-chief of Swarm and Evolutionary Computation (2010 - ), an SCI Indexed Elsevier Journal. His co-authored SaDE paper (published in April 2009) won the "IEEE Trans. on Evolutionary Computation outstanding paper award" in 2012. His former PhD student, Dr Jane Jing Liang, won the IEEE CIS Outstanding PhD dissertation award, in 2014. IEEE CIS Singapore Chapter won the best chapter award in Singapore in 2014 for its achievements in 2013 under his leadership. His research interests include swarm and evolutionary algorithms, pattern recognition, forecasting, randomized neural networks, deep learning and applications of swarm, evolutionary & machine learning algorithms. His publications have been well cited (Googlescholar Citations: ~50k). He was selected as one of the highly cited researchers by Thomson Reuters every year from 2015 to 2020 in computer science. He is ranked worldwide 300-400 among all Computer Science and Electronics researchers (also include some Control and Communication Engineering researchers) with public Google Scholar profiles. He served as the General Chair of the IEEE SSCI 2013. He is an IEEE CIS distinguished lecturer (DLP) in 2018-2021. He has been a member of the IEEE (S'91, M'92, SM'00, Fellow’15) since 1991 and an elected AdCom member of the IEEE Computational Intelligence Society (CIS) in 2014-2016.
Dr. Nitin Auluck working as Associate Professor in Computer Science & Engineering at IIT Ropar. He obtained PhD in Computer Science and Engineering from the University of Cincinnati USA in 2005. His research interests are scheduling & resource management in Distributed systems, IoT and Fog Computing. He is also the Head of IT services at Ropar. He is having 13+ years of experience in teaching, research and management positions. To his credit he got research funding from vairous agencies like Department of Science and Technology (DST), Government of India, Global Challenges Research Fund (GCRF), National Supercomputing Mission (NSM), British Council India etc.,. Currently he is serving as an Editor for Wiley's journal Concurrency and Computation: Practice and Experience (CCPE). He is a co-chair of CloudAM workshop for 2021. He has been on the program committee of many conferences such as CCGriD, CCNC, IEEE Cloud.
Talk title: Scheduling and Resource allocation in Fog computing.