Prof Yadati Narahari

IISc Bangalore

Synopsis of Research Activities:

Department of Computer Science and Automation
IISc Bangalore

I work in the following areas: Algorithmic Game Theory; Mechanism Design (Design of Auctions and Markets); Computational Social Choice: Artificial Intelligence for Social Good; AIML for Agriculture.

Prof Cristina Piazza

TU Munich

Synopsis of Research Activities:

Department of Computer Science
Technical University of Munich (TUM)

The research activity of Professor Piazza focuses on the areas of rehabilitation and assistive robotics. Her main research interests include the study of human movement and the mechatronic design of artificial devices based on soft robotics technologies. The aim is to develop simple and reliable technologies, based on neuroscientific theoretical principles, to assist people with limb loss or motor disabilities. An additional focus is to explore the development of advanced control techniques based on non-invasive methods, such as the use of surface electromyographic (sEMG) sensors. The ultimate goal is to build intelligent prostheses and promote a natural integration of bionic limbs. She has also experience in designing and conducting clinical trials with subjects with limb loss, in close collaboration with national and international clinical partners. Prof. Piazza is also interested in explore novel assessments for upper limb rehabilitation and provide innovative solutions to patients, based on emerging technologies, such as virtual reality.

Prof. Piazza received her PhD in Robotics at University of Pisa, Italy before moving to Chicago (USA) where she worked as a Postdoctoral Researcher at the Department of Physical Medicine and Rehabilitation, Northwestern University and the Regenstein Foundation Center for Bionic Medicine, Shirley Ryan AbilityLab (former Rehabilitation Institute of Chicago). Since November 2020, she is Professor for Healthcare and Rehabilitation Robotics at the Technical University of Munich (TUM).


Dr A P Prathosh

IIT Delhi

Synopsis of Research Activities:

Assistant Professor
Department of Electrical Engineering
IIT Delhi

Prathosh received his Ph. D from the Indian Institute of Science (IISc), Bangalore in 2015, in the area of temporal data analysis. He submitted his Ph. D thesis three years after his B.Tech in 2011, with many top-tier journal publications. Subsequently, he worked in corporate research labs including Xerox Research India, Philips research, and a start-up in CA, USA. His work in the industry, focussing on healthcare analytics, led to the generation of several IP, comprising 15 (US) patents of which 10 are granted and 6 are commercialized. He joined IIT Delhi in 2017 as an Assistant Professor in the computer technology group of Electrical Engineering where is currently engaged in research and teaching of the machine and deep learning courses. His current research includes guided deep-representational learning, cross-domain generalization, signal processing, and their applications in healthcare. He has co-founded a startup Cogniable.Tech which builds learning algorithms for behavioural healthcare (first-place winner of the recent AI startup challenge by Govt. of India) and also actively engaged with several corporate industries, start-ups, and medical centres (E.g., AIIMS) in solving interesting technical problems.

Mr Christian Leibig

Vara (MX Healthcare GmbH) Berlin

Synopsis of Research Activities:

Director of Machine Learning

Christian Leibig is Director of Machine Learning at Vara, working on medical applications of artificial intelligence, in particular deep learning. He obtained a Ph.D. in Neural Information Processing from the International Max Planck Research School in Tuebingen and a diploma in physics from the University of Konstanz. Before joining Vara, he worked as a Postdoctoral Researcher at the University Clinics in Tuebingen on the applicability of Bayesian Deep Learning and machine learning applications for the healthcare space for ZEISS and held research and internship positions with Max Planck, LMU Munich and the Natural and Medical Sciences Institute in Reutlingen. The method and software of his PhD work, an unsupervised solution for neural spike sorting from HDCMOS-MEA data is distributed by Multichannel Systems (Harvard Bioscience). His work on applying and assessing uncertainty methods to large scale medical imaging was among the first in the field and awarded with key note speaker invitations. His overarching interest lies in bridging the gap between theoretical and applied machine learning, in particular for applications that have a meaningful impact.

Prof Gautam Menon

Ashoka University

Synopsis of Research Activities:

Departments of Physics and Biology, Ashoka University, Sonipat & The Institute of Mathematical Sciences, Chennai

I am a biophysicist and mathematical modeller with a special interest in disease modelling. Trained as a statistical physicist, my interests switched to biophysics and to disease modelling and related public policy about a decade ago. I currently lead the development of one of India’s most detailed epidemiological models for COVID-19 spread, the INDSCI-SIM model, which provides input to policy across several Indian states and cities. Our work in network models of disease spread has led to a deeper understanding of how to construct testing regimes for COVID-19 in India that combine relatively inexpensive but less sensitive point-of-care tests using lateral flow assays with highly sensitive RT-PCR tests that require laboratory facilities. I was an author on one of the first papers to examine optimal vaccination strategies in India. I am currently funded by the BMGF to develop agent-based models for COVID-19 spread in India. Our model, BharatSim, which also includes a synthetic population developed using state-of-the-art machine learning methods, will be made publicly available shortly. In the past I have worked on connecting individual-level immune response to H1N1 influenza infection to population-level models for the spread of this disease. I also work on models for vaccination strategies that can lead to faster reopening of schools and to the relaxation of non-pharmaceutical interventions. My other work in biophysical models includes models for the shapes and behaviour of colonies of cyanobacteria, of axonal transport, and of nuclear architecture.

Dr Jürgen Dukart

Forschungszentrum Jülich

Synopsis of Research Activities:

Group Leader Biomarker Development
Institute of Neuroscience and Medicine - INM-7: Brain
and Behaviour, Research Center Jülich

The aim of the group Biomarker Development is to identify, validate and integrate novel technology-based biomarkers for early detection, follow-up, stratification and monitoring of treatment effects in neurological and psychiatric diseases. The main technologies developed and deployed by our group and integrated into clinical studies in collaboration with clinical partners include neuroimaging and smart technologies such as smartphones, wearables and video-based interaction tracking. The scientific focus of the group is on development and deployment of technological platforms for objective evaluation of symptoms in everyday life and in the clinic as well as implementation of data processing and analysis algorithms for improved evaluation of imaging and sensor data integrating machine learning and other AI-based methods.

Prof Ujjwal Maulik

Jadavpur University Kolkatta

Synopsis of Research Activities:

Professor and Former Chair Department of Computer Science and Engineering Jadavpur University, Kolkata

In the last two and half decades Prof. Maulik and his group is primarily doing research in the domain of Pattern Classification, Machine Learning, Multi Objective Optimization and Bioinformatics. He demonstrated how evolutionary clustering can be used for partitioning large data sets. For determining number of partitions automatically, he also developed a new cluster validity index and have shown the uniqueness and global optimality of the clusters obtained using it. Prof. Maulik’s group also developed multi-objective clustering techniques which evolve a set of Pareto-optimal solutions as alternative partitions. Moreover, an innovative strategy was developed for combining these alternative solutions to obtain a better partition using support vector machine (SVM) classifiers. He also designed an ensemble of semi-supervised SVM classifiers that recognizes the conceptual similarity between the component classifiers. The importance of the developed techniques by his group for solving real-life problems is revealed by its application in identification of co-expressed gene modules and cancer markers from gene expression data and in remote sensing imagery for effective land-cover classification which is important for forestation/deforestation studies and flooded-area estimation.

Prof. Maulik’s research in Bioinformatics demonstrate that innovative computational frameworks are important for new findings. His group developed multi-objective techniques for finding differentially co-expressed gene modules of human proteins across acute and chronic states of HIV-1 progression. Through mining quasi-bicliques from HIV-1−human protein-protein interaction networks several new human proteins are identified that could act as the gateways of viral entry. It is also shown that these proteins control a number of microRNAs that have oncogenic involvement. His group also developed a cancer-microRNA network which is important resource for both experimental and computational biologists. His current research on Covid demonstrate the fact that structural multiplicity of the viral proteins can trigger the host cell protein and result post Covid severity. All these research contributions are important for designing better healthcare system. The detail about Prof. Maulik’s research is available at .

Prof Lucie Flek

University of Marburg

Synopsis of Research Activities:

Associate Professor for Language Technologies
Department of Mathematics and Computer Science
University of Marburg

Lucie Flek is an Associate Professor at the Philipps-Universität Marburg, leading the newly formed research group on Language Technologies. Her interests lie in machine learning applications in the field of Natural Language Processing (NLP), including DNN-based synthetic data generation, robustness to adversarial attacks, privacy-preserving algorithms, and robustness to distributional shifts. The health application of the research groups’ work range from conversational AI, medical entity extraction and question answering, to mental health analysis in social media, including early suicide ideation detection using dynamic graph neural models.

Prior to her return to academia, Lucie Flek has contributed to digital strategies in Amazon Alexa and Google. In her earlier research work at TU Darmstadt, Positive Psychology Center at University of Pennsylvania, and University College London, she has been focusing on psychological and social NLP applications, serving as Area Chair for Computational Social Sciences at multiple ACL* conferences. Before her research path in natural language processing, she was involved in particle physics research in the area of dark matter searches at CERN.

Prof Vijay Chandru

IISc Bangalore

Short Bio:

Centre for Biosystems science and Engineering
IISc Bangalore

Professor Vijay Chandru has served on the faculty of engineering at Purdue University and is now with the Centre for Biosystems science and Engineering at the Indian Institute of Science (IISc). He is an executive advisor for healthcare to ART Park (DST innovation Hub for AI and Robotics at IISc), and a Commissioner with the Lancet Citizens Commission on reimagining India’s health system. He was an inventor of the Simputer and founder of Strand Life Sciences, India's leading precision medicine solutions company. A fellow of the academies of science and engineering, a technology pioneer of the World Economic Forum and recipient of the Hari Om Trust Award of University Grants Commission in 2001 for serving science and society, Professor Chandru identifies with "Historians of the Now" - a cadre that begins with a study of what is today, asking not how to avoid the perils of the past but how to maximize the advantages of the future.

Dr Rajiv Ratn Shah

Indraprastha Institute of Information Technology Delhi

Synopsis of Research Activities:

Head, Department of Human Centred Design Assistant Professor, Computer Science & Engineering Director, MIDAS Research Lab

Rajiv Ratn Shah currently works as an Assistant Professor in the Department of Computer Science and Engineering (joint appointment with the Department of Human-centered Design) at IIIT-Delhi. He is also the director of the MIDAS Lab at IIIT-Delhi and Signal Sciences & AI Labs Pvt. Ltd. He received his Ph.D. in computer science from the National University of Singapore (NUS), Singapore. Before joining IIIT-Delhi, he worked as a Research Fellow in Living Analytics Research Center (LARC) at the Singapore Management University (SMU), Singapore. Dr. Shah is the recipient of several awards, including the prestigious Heidelberg Laureate Forum (HLF), European Research Consortium for Informatics and Mathematics (ERCIM) fellowships, and best paper/poster awards at different international conferences. His research interests include multimedia content processing, natural language processing, image processing, speech processing, multimodal computing, data science, and social media computing. Specifically, his current research interests include: multimodal deep learning based healthcare solutions, multimodal deep learning based scoring systems, and deep learning based multimedia systems. Many research works from his lab has been published to top tier conferences and journals.