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Associate Professor, IIIT Delhi
Ph.D. degree in Electrical Engineering from IIT Delhi in 2006.
Bachelor's and master's in ECE from Delhi University in 1991 and 1997, respectively.
Assistant Director at ALL India Radio (through Indian Engineering Services) in 1993 and worked there until Feb. 1999.
Joined as Assistant Professor in the Computer Engineering Department, Netaji Subhas Institute of Technology (NSIT), Dwarka, Delhi in 1999.
Did her second master's as a full-time student from University of Maryland College Park, USA from 2008 to 2010.
Director of Assessment at the Bowie State University, Maryland USA from Oct. 2010 to April 2011.
Associate Professor at IIIT Hyderabad from July 2011 to Dec. 2013.
Associate Professor at IIIT Delhi from Dec. 2013.
Abstract:
Neurodevelopmental disorders impact humans in different ways affecting their life quality. Among the brain scanning technologies, EEG is the most economical, easy-to- acquire methodology yielding good temporal resolution. In this talk, we will discuss EEG data capture and the required preprocessing. We will also discussone of our recent works of extracting functional brain connectivity networks under music and rest states in individuals with intellectual disorder and comparison of the same with those of the healthy population.
Research Interests:
Applications of Wavelet Transforms, Machine (Deep) Learning, and Compressed Sensing, Sparse Reconstruction, fMRI/EEG/MRI/DTI Signal and Image Processing, Genomics Signal Processing, Signal Processing for Communication Engineering, and RF Energy Harvesting.
Professor,
Ecole polytechnique Federale de Lausanne (EPFL)
M.S. degree in Computer Sciences and the Ph.D. degree in Computer Science Engineering from Ghent University, Belgium, in 1998, and 2002, respectively.
PDF (2002-2005) at the lab of Prof. Michael Unser at the Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland.
Group leader for the Signal Processing Unit at the University Hospital of Geneva, Switzerland, as part of the Centre d’Imagerie Biomédicale (CIBM) 2005-2009).
In 2009, he received a Swiss National Science Foundation professorship.
In 2015 became Professor of Bioengineering at the École polytechnique Federale de Lausanne (EPFL) (Institute of Bioengineering), jointly affiliated with the University of Geneva (Department of Radiology and Medical Informatics), Switzerland.
Senior Editor, IEEE Transactions on Signal Processing (2019-present); Editor, SIAM Journal on Imaging Science (2018-present); Associate Editor, IEEE Transactions on Image Processing (2006 to 2009); Associate Editor, IEEE Signal Processing Letters (2004 to 2006); Chair, Bio Imaging and Signal Processing (BISP) Technical Committee (2012-2013); Founding Chair, EURASIP Biomedical Image & Signal Analytics SAT (2016-2018); Co-Chair, Biennial Wavelets & Sparsity series conferences, together with Y. Lu and M. Papadakis.
Recipient of the Pfizer Research Award (2012); NARSAD Independent Investigator Award (2014); and the Leenaards Foundation Award (2016).
Research interests include wavelets, sparsity, graph signal processing, and their applications in computational neuroimaging.
Abstract:
Over the past decade, approaches from signal processing, machine learning, and network science, have had a profound impact on the analysis and the interpretation of brain activity measured by functional magnetic resonance imaging (fMRI). Functional connectivity studies have given not only insights into how the brain supports coordinated cognition, learning, or stability in a changing environment, but also to what extent networks are altered in neurological disease and disorder. Recently, the quest for better understanding of brain dynamics has triggered new ways to approach functional connectivity; i.e., using time-resolved rather that summarizing correlational measures that miss essential details of network interaction dynamics. In this talk, I will highlight a promising recent advances where fMRI data is analyzed in terms of transient activity. This new framework can deal with spatial and temporal overlap of functional networks, and thus unravels their interdigitated and parallel organization. I will put these developments in perspective for building better, more mechanistic, models of brain function and their potential for disease diagnosis and prognosis.
Co-founder, Nanosniff Technologies
M. Tech from VNIT Nagpur in 1999.
Ph. D. from the Electrical Engineering Department at IIT Bombay in 2007.
Principal Engineer at Taiwan Semiconductor Manufacturing Company, for 32-nm High-K Metal Gate project 2007-2009.
Manager at IIT Bombay Nano-manufacturing Facility 2009.
Co-founded Nanosniff Technologies in June 2011, he is working as its Chief Technology Officer. In this role he is responsible for the R&D in the area of fabricating microcantilever sensors, microheaters; and developing instruments for detecting proteins, cardiac-markers and antibodies.
He has developed several MEMS Products (Devices & Instrumentation), which include:
1. Instruments: (i) Omnicant; (ii) Omnicant Bio.
2. MEMS Devices: (i) Piezoresistive Microcantilevers; (ii) Microheaters; (iii) Microheaters with IDE’s.
He has demonstrated the Proof of Concept of detecting Cardiac Proteins (hFAbP, Myoglobin etc) using Piezoresistive Microcantilevers, Ultrasensitive electronics, & a Custom-made Liquid-Cell.
Abstract:
Since the late 1980s there have been spectacular developments in microelectro-mechanical (MEMS) systems, which have enabled the exploration of transduction modes that involve mechanical energy; and are based primarily on mechanical phenomena. As a result an innovative family of chemical and biological sensors has emerged. In this talk, we discuss sensors in the form of microcantilevers & microheaters. While MEMS represents a diverse family of designs; devices with simple cantilever configurations & microheater configurations are especially attractive as transducers for chemical and biological sensors. The first part of the talk deals with several important aspects of these transducers, namely: (i) operation principles; (ii) fabrication; and (iii) applications. In the second part of the talk we discuss about our work in healthcare applications to make a MEMS based instrument that can help physicians in diagnosing a heart attack event. We will also present our work to develop a MEMS based explosives detector. Finally, we discuss about the instruments (Omnicant & Sensimer) that we have developed, to help researchers to experiment with microcantilevers & microheaters.
Professor, VNIT, Nagpur
Professor at VNIT Nagpur at Center of VLSI and Nano technology.
M.Tech. in Electrical Engineering from IIT Bombay.
Research engineer in the Microelectronics Project at in Department of Electrical Engineering at IIT Bombay.
Ph. D. (1992) from the Department of Electrical Engineering IIT Bombay.
Faculty at IIT Bombay after working for a year at Computer vision R&D Pune.
TECH Semiconductor (Now Micron), Singapore, in Advance Device Technology Department (1998-2000).
Institute of High Performance Computing, Singapore (2001).
Team Leader of Nanotechnology group at Computational Research Laboratory Pune (Supercomputing center by TATAs), 2004
Published about 45 papers in International Journals and 80 papers in international refereed conferences and 20 papers in national conferences.
Filed four patents in last two years and earlier he had obtained one patent in USA.
Many projects funded by agencies like MCIT, ADA, BRNS, RGSTC.
Heading a project on Incubation center a VNIT, Nagpur.
Recently edited a book MEMS Resonator Filters published by IET.
Abstract:
Analog signal processing is essential in almost all electronic systems. Traditionally, analog signal processing has been done with transistors and passive components such as resistors, inductors and capacitors. With nanoelectronics and MEMS, signal processing is done by using nanostructure devices that operate on principles different from scaled conventional transistors, including devices operating on mechanical transduction. In this talk, filter design in RF communication systems is reviewed since it is one of the most required signal processing blocks.The use of MEMS resonators for signal processing is relatively new and has the potential to change the topology of newer generation circuits. New materials, design and fabrication processes, and integration with conventional circuitry will need to be considered. This talk explores the challenges and opportunities of developing circuits with MEMS resonator filters. The replacement of classical electrical components with electromechanical components is explored in this talk, and the specific properties of MEMS resonators required in various frequency ranges are discussed.
Distinguished Lecturer, IEEE-EMBS, IEEE Nano Technology Council and INSA-YSA
Ph.D. (Electrical Engg), IIT-Delhi
Life Fellow- IEEE and LF-IETE, LF-IEI, LF-ASI/USI and LF-IFUMB/WFUMB.
Over 38 years of research-cum-teaching experience in India and abroad.
He has been at National Physical Laboratory (NPL), New Delhi, as a Director-grade-Scientist/ Head of Instrumentation, Sensors & Biomedical Measurements and Standards, as well as Distinguished Professor (AICTE/INAE) jointly with Thapar University.
Over 600 papers and books, 250 talks, 14 patents, 30 consultancies, 35 PhD scholars to his credit.
Recipient of awards by INSA (Ind Natnl Sci Academy)1974, NPL 1973, Thapar Trust
1983, ICMR (Ind Council of Med Res) 1984; Japan Soc. Ultr in Medicine 1985, Asian Federation of Societies of Ultrasound in Medicine & Biology 1987, IE-I(Institution of Engineers- India) 1988/ 1991, IEEEEMBS 1999 and IEEE-2010/2011/2014, Sir CV Raman Award by Acoustical Society of India / 2018, for his outstanding contributions, and Best Associate Editor Award-2920 of IEEE TIM.
Presently, he is IEEE-EMBS-DL (Distinguished Lecturer), IEEE Nano Technology Council-DL and INSA-YSA-DL. He has been the Best AE of IEEE-TIM, 2020.
His main areas of interest are: nano-electronic devices, sensors and transducers, biomedical instrumentation, biomedical standards, computer modelling and simulation, biomedical ultrasonics/medical acoustics, POCT devices, neuro-sensors/implants, nano-cancer-technology, cancer hyperthermia, tissue characterisation, lithotripsy, IOT, WSN and u-health care engineering.
Abstract:
With the rapid progress in science, newer and newer sensors and systems are being developed, day by day, for various industrial, scientific, engineering and biomedical applications. However, more advanced sophisticated sensors and systems are still required to be developed for better health care, with reliable quick diagnosis of a particular disease/abnormality in an intelligent manner as well as for therapeutic treatment of say cancer disease, well in time. Perspectives in nano-sensors and nano-systems are discussed here for the measurements in better healthcare applications, particularly for old age patients living in isolated areas. The design and fabrication aspects of new nano-sensors and smart systems based on different sensing mechanisms are given. Nano-chip based sensing systems like ultrasound on a chip, are described in detail. Main emphasis is placed on the development of IOT based and cloud-based nano-sensors and smart systems for new clinical measurements, in the ubiquitous manner. As the case studies, cancer nanotechnology and therapeutic treatment of deep seated brain tumors, with high intensity focused ultrasound, are described. U-health care program is presented with wireless sensor networking (WSN) in different environments, in an effective manner for better health cares. The present study would open a new area of research in the medical field.
Associate Professor, Electrical Engineering, IIT, Gandhinagar
Faculty at Electrical Engineering, IIT, Gandhinagar
PhD from Vanderbilt University, USA
MTech from IIT Kharagpur
Works on application-oriented projects and solutions for children with autism and stroke-rehabilitation platforms for the elderly.
Has established an Intelligent Rehabilitation and Affective Computing Systems Laboratory on campus.
Abstract:
Physiological Signal processing based solutions have invaded the domain of healthcare starting from diagnostics to rehabilitation. In my talk, I will address both of these aspects while focusing on patients suffering from neurological disorders. From the perspective of diagnostics, I will be focusing on use of oculomotor signatures to indicate neurological disorders. With regard to rehabilitation, I will be focusing on use of physiological signal processing for addressing gait deficits of post-stroke patients in my talk.
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