Emerging Research Topics in Engineering (ERTE) -2021
About ERTE 2021
“Emerging Research Topics in Engineering (ERTE)” is the flagship event of IEEE Gujarat Section. This year event is scheduled on October 1-3, 2021 in virtual mode with the theme of “Explainable AI (XAI)”. The event is aimed to encourage young researchers, PhD scholars, Master students, early career professionals and faculty members to learn the state-of-the-art of emerging and challenging research areas from eminent speakers around the globe. This may help participants to discover their career path and direct them to identify their own research topics and problem statements.
What is Explainable AI?
The prediction made using machine learning looks like a black box. It becomes impossible for human that why specific value is predicted by ML algorithm? The lack of explainability and trust hampers our ability to fully trust AI systems. The solution of this problem is to have explainable system. Thus, transforming the black box type of hidden functionalities of AI into transparent and understandable system is all about Explainable AI.
Following are distinguished speakers of the event:
- Dr. Soma Dhavala, Principal Researcher, Wadhwani AI, Bangalore, India
- Dr. Vijayan K. Asari, Professor, University of Dayton, Ohio, USA
- Dr. Vineeth N Balasubramanian, Professor, IIT Hyderabad, India
- Dr.Rajul Jain, Director, Predictive Analytics, Global Strategic Insights at Johnson & Johnson Vision, Washington, USA
- Dr. Arash Shaban-Nejad, Director of Population Health Intelligence (PopHI) Lab, Center for Biomedical Informatics, Department of Pediatrics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, USA
- Dr.Vijay Arya, Senior Researcher, IBM India Research Lab (IRL), Bangalore
- Mr.Jay Shah, Research Scholar, Arizona State University
Event Website Link: https://ieeegujaratsection.org/erte-2021
Registration Link: https://forms.gle/rDugsA6CQeGaxrcXA
We invite you to participate in the event and interact with speakers. Further also requested to share this mail in your network and among eligible audiences.
For any query, kindly contact:
Harshul Yagnik, ieeegujaratsec@gmail.com, Mobile Number: +91-9737642757
Date and Time
Location
Hosts
Registration
- Start time: 01 Oct 2021 03:00 PM
- End time: 03 Oct 2021 08:00 PM
- All times are (UTC+05:30) Chennai
-
Add Event to Calendar
- Gandhinagar, Gujarat
- India
- Contact Event Host
-
For any query, kindly contact:
Harshul Yagnik, ieeegujaratsec@gmail.com, Mobile Number: +91-9737642757
Speakers
Dr. Arash Shaban-Nejad of University of Tennessee Health Science Center, Memphis, TN, USA
Explainable AI-powered Clinical and Population Health Decision Making
Biography:
Arash Shaban-Nejad is the Director of Population Health Intelligence (PopHI) lab and an Associate Professor in the UTHSC-OAK-Ridge National Lab (ORNL) Center for Biomedical Informatics, and the Department of Pediatrics at the University of Tennessee Health Science Center (UTHSC). Before coming to UTHSC, he was a Postdoctoral Fellow of the McGill Clinical and Health Informatics Group at McGill University. Dr. Shaban-Nejad received his Ph.D. and MSc in Computer Science from Concordia University (AI and Bioinformatics), Montreal, and Master of Public Health (MPH) from the University of California, Berkeley. Additional training was received at the Harvard School of Public Health. His primary research interest is Population Health Intelligence, Precision Health and Medicine, Epidemiologic Surveillance, Semantic Analytics and Explainable Medicine using tools and techniques from Artificial Intelligence, Knowledge Representation, Semantic Web, and Data Science. His research has been supported by several research grants from Canada Institute for Health Research (CIHR), National Institute of Health (NIH)/National Cancer Institute (NCI), the Gates Foundation, Microsoft Research, and Memphis Research Consortium (MRC).
Address:United States
Dr. Vijay Arya of IBM India Research Lab (IRL), Bangalore
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Biography:
Vijay Arya is a Senior Researcher at IBM Research India and part of IBM Research AI group where he works on problems related to Trusted AI. Vijay has 15 years of combined experience in research and software development. His research work spans Machine learning, Energy & smart grids, network measurements & modeling, wireless networks, algorithms, and optimization. His work has received Outstanding Technical Achievement Awards, Research Division awards, & Invention Plateau Awards at IBM, and has been deployed by power utilities in the USA. Before joining IBM, Vijay worked as a researcher at National ICT Australia (NICTA) and received his PhD in Computer Science from INRIA, France, and a Masters from Indian Institute of Technology (IIT) Delhi. He has served on the program committees of IEEE, ACM, and IFIP conferences, he is a senior member of IEEE & ACM, and has more than 60 conference & journal publications and patents.