Indian Institute of Information Technology Vadodara
(Institute of National Importance under Act of Parliament)

Invited Talks

Date : January 09, 2021
Smart Living: The Next Frontier

Prof. Sajal K. Das
IEEE Fellow, Daniel St. Clair Endowed Chair, Department of Computer Science, Missouri University of Science and Technology, USA.

Date : December 18, 2020
Software verification: an overview

Prof. Agostino Cortesi
Department of Environmental Science, Informatics and Statistics, Università Ca' Foscari, Venezia, Italy.

Date : December 12, 2020
A few mathematical gems from vedic and sutra literature

Prof. Amartya K. Dutta
Affiliation: ISI Kolkata

Date : December 04, 2020
Bio-inspired Methods for Sensing & Instrumentation using AI

Prof. Amit K Mishra
Radar Remote Sensing Group (RRSG) Electrical Engineering Department University of Cape Town

In this talk, the speaker shall discuss a few bio-inspired methods that his group has been working on. He will also discuss a machine learning-centric sensing method called Application Specific INstrumentation (ASIN) where inexpensive sensors are used with AI to result in functional instruments.

Date : October 03, 2020
Electromagnetically Induced Transparency based Quantum Memory

Dr. Sumit Bhushan
Guest researcher, National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA and is associated with Quantum Communications and Networks group

Date : September 22, 2020
Life in an Era of Machine Intelligence: In Utopia or Dystopia?

Prof. L M Patnaik
Adjunct Professor and INSA Senior Scientist, Consciousness Studies Program, National Institute of Advanced Studies, IISc Campus Bangalore

Date : September 21, 2020
Machine learning with IBM Watson

Dr. Mani Madhukar
Dr. Mani is associated with IBM and has 16+ years of experience in IT with exposure to both industry and academia. He holds a doctorate in Computer Engineering and Executive program in Management from McIntire School of Commerce, University of Virginia

Date : August 22, 2020
How to stay motivated in difficult and uncertain times

Date : September 14, 2018
Solar-Blind Photo Detectors.

Prof. Susanta Sen
Institute of Radio Physics and Electronics University of Calcutta

Date : March 16, 2018
Technology-assisted Screening and Balance Training Systems for Stroke Patients

Mr. Deepesh Kumar

Date : February 02, 2018
Overview and Introduction to VLSI

Prof. Dipankar Nagchoudhuri

Date : January 09, 2018
Digital trends in IT, Agile framework & Devops, Industry expectations from engineering graduates & alternate modes of talent spotting

Mr. Gaurav Gandhi
Academic Relationship Manager - India West, TCS

Date : November 11, 2017
Future of Science

Mr. Cyan Subhra Mishra
Intel Corporation

Date : November 10, 2017
Multi-modal design of an Intelligent Transportation System

Dr. Manush Chaturvedi
Pandit Deendayal Petroleum University

An Intelligent Transportation System (ITS) plays a major role in generating fine grained vehicular traffic information for city wide or larger region. The real time traffic information is used to optimize traffic movement in a road network. However, due to the high cost of deployment and maintenance, limited ITS infrastructure is available in developing countries like India, and it is difficult to generate real time traffic information at large scale. Hence, there is a need for cost effective ITS solution.
The cellular network is widely deployed in India covering a major part of the road network. Due to the increasing penetration of GPS enabled vehicles and smart phone users, the GPS probe data is considered an attractive source for real time travel speed estimation. This work puts forward a novel mechanism of amalgamating widely available cellular network data, GPS probe data, and the data from limited ITS infrastructure for generating accurate traffic information.

Date : October 27, 2017
Decision Making under Uncertainty

Prof. Tathagata Bandyopadhyay
IIM Ahmedabad

In real-life situations most often we make decision under uncertainty. A decision problem under uncertainty is characterized by more than one consequences and the associated probabilities of different consequences. In this talk we will discuss with examples how the concept of probability could be fruitfully used to improve decision making uncertainty.

Date : October 13, 2017
50 years of Moore’s Law: Challenges and potential solutions going forward

Dr. Saurabh Sinha
Arm Inc., Austin, Texas

Digital computers have enjoyed unprecedented improvements in performance, power, area and cost due to miniaturization of transistors. As device dimensions reach atomic scales, continuing transistor scaling becomes increasingly complex and expensive. In this talk I'll discuss some of the key limitations of device scaling in the coming years and some potential solutions to get 'equivalent scaling'. The talk will give a basic primer on modern digital design methodology, design-technology co-optimization at advanced technology nodes and some disruptive technologies being explored in Arm Research, such as monolithic 3D-ICs, alternative materials for interconnects, etc.

Date : September 01, 2017
Useful skills in the age of AI

Dr. Parth Gupta
Amazon (India), Bangalore

The talk focuses on various methods required in Machine Learning (ML) domain. Talk also discuss expectation from freshers in the ML domain.

Date : March 03, 2017
4G Mobile Wireless Technology

Harshvadan J Jani,
Reliance JIO Infocomm Ltd

Mobile Technology evolution & comparision; Network Architecture, Mobile Backhaul evolution from TDM to ‘All IP Network’; 4G Mobile Call Flow & Future ahead

Date : July 21, 2016
Linear Mixed Models With Incomplete Cluster Size: A Pattern Mixture Model Approach With Application in Consecutive Pregnancy Study.

Dr. Ashok Chaurasia, University of Waterloo

It is a common issue in analyzing clustered data that the outcome is associated with cluster size. This talk addresses the informative cluster size problem in linear and generalized linear mixed models when the cluster size is incomplete on all subjects. This problem is motivated by the NICHD Consecutive Pregnancies Study, where the objective is to study the relationship between pregnancy outcomes (continuous or discrete) and parity. It is hypothesized that these pregnancy outcome profiles are associated with the number of births over a woman's lifetime, resulting in an informative cluster size. However, in this study, a woman's lifetime number of births is not observed (censored at the end of the study window). In this paper we develop a pattern mixture model to account for informative cluster size by treating the incomplete cluster size (lifetime number of births) as a latent variable. We compare this approach with the simple alternative where we use the observed number of births at the end of the study as the cluster size. For estimating the population mean trajectory, we show theoretically, with simulations, and in the real data application that the latent variable approach possesses good statistical properties.

Date : April 19, 2016
Randomized Algorithms

Prof. Subramanian, IMSc Chennai

Date : March 4, 2016
Introduction to Computational Intelligence

Prof. Sushmita Mitra
Date : February 2, 2016
From Vision-Realistic Rendering to Vision Correcting Displays

Prof. Brian Barsky, Professor of Computer Science and Affiliate Professor of Optometry, at the University of California Berkeley, USA

Present research on simulating human vision and on vision correcting displays that compensate for the optical aberrations in the viewer's eyes will be discussed. The simulation is not an abstract model but incorporates real measurements of a particular individual's entire optical system.In its simplest form, these measurements can be the individual's eyeglasses prescription; beyond that, more detailed measurements can be obtained using an instrument that captures the individual's wavefront aberrations. Using these measurements, synthetics images are generated. This process modifies input images to simulate the appearance of the scene for the individual. Examples will be shown of simulations using data measured from individuals with high myopia (near-sightedness), astigmatism, and keratoconus, as well as simulations based on measurements obtained before and after corneal refractive (LASIK) surgery.

Recent work on vision-correcting displays will also be discussed. Given the measurements of the optical aberrations of a user's eye, a vision correcting display will present a transformed image that when viewed by this individual will appear in sharp focus. This could impact computer monitors, laptops, tablets, and mobile phones. Vision correction could be provided in some cases where spectacles are ineffective. One of the potential applications of possible interest is a heads-up display that would enable a driver or pilot to read the instruments and gauges with his or her lens still focused for the far distance.

Date : January 8, 2016
Digital Five Forces and their impact on IT industry

Gaurav Gandhi, Academic Relationship Manager, TCS

Date : November 4, 2015
Delegation games: Choosing strategy over Tactics

Dr. Ratnik Gandhi, Ahmedabad University

Market games between firms - producing similar goods - are (typically) played with production levels or market prices as firms' strategies.

In this talk, I will first introduce basics of game theory: games, equilibrium and related computational problems. Subsequently, I will talk about equilibria in market delegation games and show how firms benefit by delegating their games.

This talk will not assume any background in Mathematical Economics and will be self contained.

Date : October 28, 2015
A Card Trick - Protocol, Graph model, and extensions

Prof. Shailesh Tipnis, Professor Emeritus (Department of Mathematics), Illinois State University

We will perform a card trick and reveal its protocol for you to impress your friends. We will see how a Graph Theory model of the trick enhances understanding of the trick and helps in generalizations. The talk is meant to be accessible to all students on campus.

Date : September 28, 2015
Property-Driven Fence Insertion using Reorder Bounded Model Checking

Dr. Saurabh Joshi, IITG

Modern processor architectures employ optimizations such as store buffers. Such an optimization, however, may result in program executions that violate Sequential Consistency. In other words, program statements may appear to have been reordered violating the program order. Some of these executions may result in safety property (assertion) violation. Architectures provide fence instructions(memory barriers) that can be inserted to avoid any unwanted reordering. Too many fences may degrade performance drastically whereas too few fences may result in a buggy behaviour. Due to non-determinism in scheduling and reordering, it may be very difficult for even an expert programmer to insert fences in an optimal manner.

Automated techniques have been proposed for property-driven fence insertion that repairs a concurrent program through fence insertion by suggesting optimalfence placement for a given architecture.In this talk, I will introduce a technique we call "Reorder Bounded Model-Checking" (ROBMC). ROBMC introduces a new parameter in the world of bounded model checking. We show that ROBMC based approach outperforms traditional property-driven fence insertion techniques. This work has been presented and published in FM 2015.

Date : September 18, 2015
Zero Knowledge Proof

Dr. Bireswar Das, IITGn

Wizard Merlin wants to convince king Arthur that a mathematical statement is true, but Merlin does not want reveal anything other than the validity of the statement. Can he do that? In 1989, Goldwasser, Micali and Racoff introduced the notion of Zero Knowledge Proofs. These are proofs that are convincing and yet does not reveal anything other than the validity of the statement. In this talk we discuss zero knowledge proofs and its importance in computer science. Zero Knowledge Proof is one of the concepts for which Goldwasser and Micali received Turing Award in 2012. If time permits we will discuss a recent connection between zero knowledge proofs and minimum circuit size problem This part is based on a joint work with Eric Allender.

Date : August 21, 2015
No-where Differentiable Functions

Prof. Samaresh Chatterji, IIIT Delhi