IEEE UP Section CIS Chapter

Lectures/ Talks/ Seminars



Lecture on "Time Series Analysis"
Speaker: Prof. Vrijendra Singh
Affiliation: Dept. of Information Technology, IIIT Allahabad, India
December 17th, 2020
Time: 07:00 PM - 08:00 PM



Lecture on "Applications of Genetic Algorithms in Optimization Problems in Sensor Networks"
Speaker: Prof. R. K. Mishra
Affiliation: Dept. of Electrical Engineering, IIT (BHU) Varanasi, India
December 19th, 2020
Time: 07:00 PM - 08:00 PM



Lecture on "Introduction to Machine Learning"
Speaker: Dr. Rahul Kumar Sevakula
Affiliation: Dept. of Medicine, Harvard Medical School, Masachusetts General Hospital
December 21st, 2020
Time: 07:00 PM - 08:00 PM



Lecture on "Deep Learning and Artificial Intelligence"
Speaker: Prof. Nishchal K. Verma
Affiliation: Dept. of Electrical Engineering, IIT Kanpur, India
December 23rd, 2020
Time: 07:30 PM - 08:30 PM



Lecture on "System Design"
Speaker: Dr. Sujeet Mishra
Affiliation: Chief Design Engineer (Electric Locos), Diesel Locomotive Works, Varanasi, Ministry of Railways, Varanasi, U.P., India
December 24th, 2020
Time: 06:00 PM - 07:00 PM



Lecture on "Ambient intelligence: convergence of artificial intelligence, machine learning, biometrics, cloud-computing, and internet-of-things"
Speaker: Professor Vincenzo Piuri, Università degli Studi di Milano, Italy
September 26th, 2018
Venue: L-17, Lecture Hall Complex, Indian Institute of Technology Kanpur, India
Time: 05:00 PM - 06:00 PM


Abstract:

Adaptability and advanced services for ambient intelligence require an intelligent technological support for understanding the current needs and the desires of users in the interactions with the environment for their daily use, as well as for understanding the current status of the environment also in complex situations. This infrastructure constitutes an essential base for smart living. Various technologies are nowadays converging to support the creation of efficient and effective infrastructures for ambient intelligence.
Artificial intelligence can provide flexible techniques for designing and implementing monitoring and control systems, which can be configured from behavioral examples or by mimicking approximate reasoning processes to achieve adaptable systems. Machine learning can be effective in extracting knowledge from data and learn the actual and desired behaviors and needs of individuals as well as the environment to support informed decisions in managing the environment itself and its adaptation to the people’s needs. Biometrics can help in identifying individuals or groups: their profiles can be used for adjusting the behavior of the environment. Machine learning can be exploited for dynamically learning the preferences and needs of individuals and enrich/update the profile associated either to such individual or to the group. Biometrics can also be used to create advanced human-computer interaction frameworks.
Cloud computing environments will be instrumental in allowing for worldwide availability of knowledge about the preferences and needs of individuals as well as services for ambient intelligence to build applications easily.
This talk will analyze the opportunities offered by these technologies to support the realization of adaptable operations and intelligent services for smart living in an ambient intelligent infrastructure.


Bio:

Prof. 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 Università degli Studi 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 Computers and the IEEE Transactions on Cloud Computing, and has been Associate Editor of 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.




Distinguished Lecture Program Talk on "Evolutionary Multi-Criterion Optimization: Introduction to Theories and Applications"
Speaker: Professor Kalayanmoy Deb, Koenig Endowed Chair professor, Michigan State University, USA
December 13th, 2014
Venue: Outreach Auditorium, Indian Institute of Technology Kanpur, India
Time: 10:00 AM - 12:00 PM


Abstract:

The aim of this talk is comprehensive coverage of Evolutionary algorithms one of the growing area of research in field of Computational Intelligence. Many real world problems have multiple objectives, where instead of exact solution a set of optimal solutions is required. Evolutionary algorithm is a highly effective way of finding multiple effective solutions in a single simulation run.


Bio:

Prof. Deb is Koenig Endowed Chair Professor at Department of Electrical and Computer Engineering in Michigan State University (MSU), USA. He also holds joint appointments at Department of Mechanical Engineering and at Department of Computer Science and Engineering at MSU. Prior to his joining MSU, he was at Indian Institute of Technology (IIT) Kanpur. Prof. Deb's research interests are in Evolutionary Optimization and their application in optimization, Meta- modeling, Constraint Handling, Engineering Design, Neural Networks, Data- mining and Machine learning.
He is awarded Infosys Prize, TWAS Prize in Engineering Sciences, CajAstur Mamdani Prize, Distinguished Alumni Award from IIT Kharagpur, Edgeworth- Pareto award, Bhatnagar Prize in Engineering Sciences, and Bessel Research award from Germany. He is fellow of IEEE, ASME, and three science academies in India. He has published over 375 research papers with Google Scholar citation of 63,500 with h-index 84. He is in the editorial board on 20 major international journals.