FDP on Machine Learning and Latest Optimization Techniques

A five day Faculty Development Program on Machine Learning and Latest Optimization Techniques, from 11th June 2018 to 15th June 2018 was organised by the Department of Electronics and Communication Engineering. The idea of the program, so organised, was to enrich the faculty members with the developing technological scenarios in the fields of Machine Learning and Optimization Techniques. The experts from various platforms and with a substantial experience in their area of expertise enlightened the participants with their knowledge and experience.

Day 1 of FDP (Evolutionary Algorithms and Swarm Algorithms)

Dr. T V Vijay Kumar delivered a talk on Evolutionary Algorithms and Swarm Algorithms. He described about various kinds of algorithms like ant colony, honey bee, annealing, cuckoo search etc. He talked about the situations in which the nature inspired algorithms should be put to use. Concepts of natural selection, tournament selection, exploration and exploitation were also widely discussed. He talked about the genetic algorithms and multi-objective optimization as well.

Dr. T V Vijay Kumar is a Professor in the School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi. He is also Concurrent Professor in Special Centre for Disaster Research, Jawaharlal Nehru University. Additionally he is also the International Students advisor at Jawaharlal Nehru University. He has completed his PhD in the area of Databases from Jawaharlal Nehru University after completing his MPhil and MSc in Operational Research and BSc(Hons) in Mathematics from University of Delhi.

His research interests are Databases, Data warehousing, Nature inspired computing and Big data analytics.

Day 2 of FDP (Fuzzy Logic: Theory and Practical Implementation)

Dr. Arun Sharma delivered a talk on Fuzzy Logic. He described about soft computing and how it is different from the hard computing. He discussed about different components of soft computing in general and fuzzy logic in specific. He talked about the membership functions and implementation of Fuzzy Logic. He stressed about by the different variations of Fuzzy Logic like Neuro-Fuzzy etc. being used now a days. He gave the practical demonstration on commonly used application software as well.

Dr. Arun Sharma works as Associate Professor and Head of the Department - IT at Indira Gandhi Delhi Technical University for Women (IGDTUW), Delhi. He is also having the additional responsibilities as Managing Director - IGDTUW Anveshan Foundation, an Incubation Centre at IGDTUW. He has handled the responsibility as Dy. Dean (Examination Affairs) successfully for three years from 2015 to 2018 at IGDTUW. Also he is the Convener of Board of Studies for Faculty of Engineering and Technology, IGDTUW. He has been the Chairman of CSI - Ghaziabad Chapter (2015-16) and Members of IEEE Delhi Section Standing Committee on Technical & Professional Activities (Conferences) for 2016-17 and 2017-18. He has organized six International Conferences and delivered Key Note Addresses in various Conferences and others in India and abroad. He has been nominated for World’s Who’s Who by Marquis, USA in 2013. He has also been awarded by Computer Society of India in 2017 for his significant contribution for it.

His areas of interests include Software Engineering, Soft Computing and Big Data. Under his guidance, 5 students have completed their PhD degree. He has published more than 60 papers in international SCI/SCIE/SCOPUS and other journals and conferences. He is a Senior Member-IEEE and Life Member- CSI.

Day 3 of FDP (Neural Networks and Deep Learning)

Dr. R. K. Aggarwal gave a lecture on Neural Networks and Deep Learning. He differentiated between supervised and unsupervised learning by giving pertinent examples. He drew parallels between human intelligence and machine intelligence and how the machines could be made to learn just like humans but in a much lesser time. He talked about nearest neighbor algorithm, decision boundary approach, error equation and gradient descent method for minimizing the error. He discussed in detail about the Single Layer Perceptron and Multi Layer Perceptron. With the help of examples he made the audience understand about the concepts of Confusion Matrix and Accuracy in the context of Neural Networks. He differentiated between deep learning and machine learning. Gradient diminishing effect and Auto encoder scheme were also discussed by him. Over all was very informative and useful talk for the people aspiring to work in these highly coveted areas.

Dr. R. K. Aggarwal is Dean & Professor, School of Engineering and Professor, School of Computer & Systems Sciences, Jawahar Lal Nehru University, Delhi. He has teaching experience of approximately twenty five years. He is the member of various boards and committees as follows-Advisor to Staff Selection Commission, New Delhi; Member, UGC Expert Committee; Coordinator, Expert Committee, CBSE; Member, Project Review and Steering Group (PRSG) for the project CDAC Mohali; Member, Expert Member, DST, Delhi; Expert Member, DRDO, Delhi; Expert Member, Selection Committee, Jammu University; Member, Advisory Committee, Department of Computer Science, University of Delhi; Jury member, INSPIRE AWARD- National Level Exhibition and Project Competition; Academic Committee Member, Central University of Rajasthan; Academic Committee Member, Central University of Himachal Pradesh, Member, BOS, NIT Uttrakhand, Member, BOS, Doon University, Member, BOS, Gautam Buddha University, Member, BOS, IGNOU.

His research areas include Data Mining, Machine Learning, Pattern Recognition and Medical Imaging. Under his guidance, 14 students have completed their PhD degree and 8 are currently doing their research work under his supervision. He has published 63 papers in international SCI/SCIE/SCOPUS and other refereed journals and 41 papers in the conferences. He is a Senior Member-IEEE and ACM. He has been reviewer of the journals of IEEE, Elseveir and Springer.

Day 4 of FDP (Identification of Human Activity using Machine Learned Models)

Dr. Dinesh K.Vishwakarma delivered his talk on the human activity identification by incorporating machine learning models. He described about the benefits of human activity identification which can promptly bring to notice any kind of aberration from the normal routine. This could be used in the surveillance and security, elderly people healthcare, Intrusion detection system and automated movie analysis etc. He also described about the various challenges coming in the way of automated human activity identification. He explained with example how the machine learning models could be used in the computer vision applications.

Dr. Dinesh K.Vishwakarma is an Associate Professor in Delhi Technological University, Delhi. He is Officer In-charge (Genral Administration) and I/C, Examination (Secrecy Delhi Technological University.He received the B.Tech. degree from Dr. RML Awadh University, Faizabad, Uttar Pradesh, India, in 2002, the M.Tech. degree from the Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India, in 2005, and the Ph.D. degree in Computer Vision from Delhi Technological University, New Delhi, India, in 2016.

His current research interests include human action and activity recognition, hand gesture recognition, gait analysis, and machine learning.

Day 5 of FDP (Use of LabView software in Communication Engineering and Signal Processing)

Mr. Kuldeep Sharma delivered a presentation on the usage of LabView in various electronics engineering disciplines especially in Communication Engineering, Signal & Systems and Digital Signal Processing. He compared LabView with MATLAB and Scilab and discussed about the pros and cons of working with these softwares. He demonstrated the usefulness of LabView by performing the lab curriculum experiments.

Mr. Kuldeep Sharma is Application Engineer with Trident Techlabs, Delhi. He has nine years of experience working with LabView and other softwares.