The Speakers

Ramakrishnan A. G. is an adjunct faculty at the Dept. of Heritage Science and Technology at IIT Hyderabad. Earlier, he retired as a professor of Electrical Engineering and Centre for Neuroscience, Indian Institute of Science, Bangalore. He obtained his M.Tech. and Ph.D. from IIT Madras. He graduated 22 Ph.D.s, 16 M.Tech.s by research, and guided over 100 M.Tech. projects at IISc. He is a Fellow of the Indian National Academy of Engineering. As the leader of a research consortium, he was instrumental in creating handwriting recognition technologies for eight Indian languages. He received Manthan award (South East Asia and Asia Pacific) twice for creating Braille & audio books for blind students through his OCR and TTS in Tamil and Kannada. His areas of research are speech recognition in Indic languages, decoding of imagined words from EEG, brain functional connectivity analysis in modified states of consciousness, and the study of the physiological mechanisms behind the health and therapeutic effects of deep breathing. For his work on evoked potentials from leprosy patients, he received Sir Watt Kay Young Researcher’s Prize from the Royal College of Physicians and Surgeons, Glasgow. 

He was a Senior Research Scientist at Hewlett Packard  Research Labs, Bangalore India from May 2002 to August 2003. He is an invited member of the Senate of IIIT-Allahabad, Prayagraj and the Federation of Indian Chambers of Commerce and Industry - Indian Language Internet Alliance. He was a member of the Knowledge Commission, Government of Karnataka during 2017-2020. He is also one of the founder directors of RaGaVeRa Indic Technologies private limited recognized by Karnataka Government as one of the Elevate 2019 Startup winners. The Kannada TTS developed by RaGaVeRa was evaluated to be better in quality than Google’s Wavenet TTS and Nuance’s Kannada TTS. He is also the Advisor-Neuroscience of Feedfront Technologies Pvt Ltd, Bengaluru, and Principal Advisor of Bhashini AI Solutions Pvt. Ltd.

His YouTube videos have 33000+ views so far and have 400+ subscribers.

Webpage: http://mile.ee.iisc.ac.in/AGR/index.htm

I am a MD-PhD student at the University of California San Francisco working in the laboratory of Dr. Edward Chang in the department of neurological surgery. I am broadly interested in neurosurgery and neural engineering research. My specific interest is in studying speech motor control and speech-based brain computer interfaces to restore communication to patients with paralysis. I enjoy developing methodology for both neural decoding and interpretating the specific features encoded by neural populations.

Lab Website: https://changlab.ucsf.edu/

Arpan Banerjee's primary interests are theoretical and computational neuroscience, and functional brain imaging. Understanding where (spatial) and when (temporal) task-related differences in information processing occur in the brain is fundamentally important for formulating basic scientific theories and investigating the mechanisms of brain dysfunctions. The key research question that he wants to address is how large networks of neurons coordinate amongst each other to form organized assemblies at only specific instants of time to orchestrate ongoing behavior. Demystifying the tunes that govern this neural orchestra will shed light on subtle differences in human brain function across normal individuals, across patients and eventually lead to developing neuro-markers for spectrum disorders such as autism.

Arpan is a Principal investigator of Cognitive Brain Dynamics Lab housed in National Brain Research Centre, Manesar, Gurgaon. Built a research team of more than 25 people adept in performing cutting edge research on brain dynamics using EEG/ MRI/ MEG technologies in last 8 years which have resulted in several publications in top tier international journals and conference presentations. Received prestigious grants and achieved deliverables committed to the respective government agencies. Mentored PhD and MSc students, post-doctoral fellows and research assistants some of whom has taken up prominent positions in industry and academia and have obtained prestigious fellowships like NPDF, CSRI (from Dept of Science & Technology, Govt of India).

Lab Website: https://cbdlnbrc.weebly.com/

Dr Arun Sasidharan is a Neuroscientist, trained initially in Modern Medicine (MBBS) and later in Neurophysiology (PhD). He does interdisciplinary research, exploring how brain's predictive processes shape mental illness & wellness, crossing conventional boundaries for a holistic and simplistic understanding. He has around 13 years of advanced expertise in using EEG, ERP, PSG, and fMRI - conducting workshops and talks across the country. His research focuses on various aspects of consciousness that include sleep cognition, dreaming, emotional construction, neurobiology of mental illness, and developing novel EEG-based tools to assess them. Last 4 years he worked with a group of brilliant engineers to translate Neuroscience research ideas using EEG-based health-care and research-level solutions. Currently, he is a Scientist at the new Center for Consciousness Studies, under Dept of Neurophysiology, NIMHANS.

LinkedIn Profile: https://in.linkedin.com/in/dr-arun-sasidharan-352a1518

Bhuvana Ramabhadran (IEEE Fellow, 2017, ISCA Fellow 2017) currently leads a team of researchers at Google, focusing on semi-supervised learning for speech recognition and multilingual speech recognition. Previously, she was a Distinguished Research Staff Member and Manager in IBM Research AI, at the IBM T. J. Watson Research Center, Yorktown Heights, NY, USA, where she led a team of researchers in the Speech Technologies Group and coordinated activities across IBM’s world wide laboratories in the areas of speech recognition, synthesis, and spoken term detection. She has served as an elected member of the IEEE SPS Speech and Language Technical Committee (SLTC), for two terms since 2010 and as its elected Vice Chair and Chair (2014–2016) and currently serves as an Advisory Member. She has served as the Area Chair for ICASSP (2011–2018), on the editorial board of the IEEE Transactions on Audio, Speech, and Language Processing (2011–2015), and on the IEEE SPS conference board (2017-2018) during which she also served as the conference board’s liaison with the ICASSP organizing committees , and as Regional Director-At-Large (2018-2020), where she coordinated work across all US IEEE chapters . She currently serves as the Chair of the IEEE Flanagan Speech & Audio Award Committee and currently serves as a Member-at-Large of the IEEE SPS Board of Governors. She serves on the International Speech Communication Association (ISCA) board and has served as the area chair for Interspeech conferences since 2012. In addition to organizing several workshops at ICML, HLT-NAACL, NeurIPS and ICML, she has also served as an adjunct professor at Columbia University, where she co-taught a graduate course on speech recognition. She has served as the (Co/-)Principal Investigator on several projects funded by the National Science Foundation, EU and iARPA, spanning speech recognition, information retrieval from spoken archives, keyword spotting in many languages. She has published over 150 papers and been granted over 40 U.S. patents. Her research interests include speech recognition and synthesis algorithms, statistical modeling, signal processing, and machine learning. Some of her recent work has focused on the use of speech synthesis to improve core speech recognition performance and self-supervised learning.

Webpage: https://research.google/people/bhuvana-ramabhadran/

Hema A Murthy received the bachelor’s degree from Osmania University, Hyderabad, India, in 1980, the master’s degree from McMaster University, Hamilton, ON, Canada, in 1986, and the Ph.D. degree from IIT Madras, Chennai, India, in 1992. From 1980 to 1983, she worked as a Scientific Officer (SO/SC) with the Speech and Digital Systems Group, TIFR, Mumbai. She is currently a Professor with the Department of Computer Science and Engineering, IIT Madras. She has over 39 journal publications, three book publications, and over 220 articles.

Her research interests include speech processing, computer networks, music information retrieval, computational brain research, and other areas of machine learning and signal processing. Dr. Murthy was a recipient of the Manthan Award, in 2012, and the IBM Faculty Award, in 2006. Her awards include being elected as a Fellow of the Indian National Academy of Engineering, in November 2017, and to the board of the International Speech Communication Association for the duration of 2017–2021.

Webpage: http://www.cse.iitm.ac.in/~hema/

Mari Ganesh Kumar received his Doctoral degree from the Department of Computer Science and Engineering, Indian Institute of Technology Madras. His research interests include applied machine learning and signal processing to bio-signals. He has worked with Speech, EEG, and Neuronal signals and has published multiple articles. In 2021, he was awarded the Institute Research Award, recognising his doctoral research work. He was awarded the medal for the best outgoing student for his undergraduate degree from the Thiagarajar College of Engineering, Anna University. Currently he is working with the Amazon Alexa team as an Applied Scientist.

Webpage: https://mariganeshkumar.github.io/

Dr. Mriganka Sur is the Newton Professor of Neuroscience and Director of the Simons Center for the Social Brain at MIT, which he founded after 15 years as head of the MIT Department of Brain and Cognitive Sciences.

Dr. Sur studies the organization, plasticity and dynamics of the cerebral cortex of the brain using experimental and theoretical approaches. He has discovered fundamental principles by which networks of the cerebral cortex are wired during development and change dynamically during learning. His laboratory has identified gene networks underlying cortical plasticity, and pioneered high resolution imaging methods to study cells, synapses and circuits of the intact brain. His group has demonstrated novel mechanisms underlying disorders of brain development, and proposed innovative strategies for treating such disorders. His laboratory has discovered core functional rules of inhibitory-excitatory neuronal circuits in the cerebral cortex, and revealed dynamics of information processing across widespread cortical areas. The impact of these discoveries, which answer long-standing questions about computations underlying learning, decision-making and perception-action transformations, ranges from understanding dysregulation in brain disorders to brain architectures for next-generation AI.

Dr. Sur received the B. Tech. degree in Electrical Engineering from the Indian Institute of Technology, Kanpur, and the PhD degree in Electrical Engineering from Vanderbilt University, Nashville. He has received numerous awards and honors, most recently the Krieg Cortical Discoverer Prize, and delivered distinguished lectures world-wide. He has trained over 80 doctoral students and postdoctoral fellows, and received awards for outstanding teaching and mentoring. At MIT, he has been recognized with the Sherman Fairchild and Newton Chairs. He is an elected Fellow of the Royal Society of the UK, the National Academy of Medicine, the American Academy of Arts and Sciences, the American Association for the Advancement of Science, the World Academy of Sciences, the Indian National Science Academy, and the American Institute of Medical and Biological Engineering.

Lab Website: https://www.surlab.org/mriganka/

Dr. Rajeswari Aghoram is a faculty member in the Department of Neurology at Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry.

Academically, Dr. Aghoram holds the degrees of MD and DM, reflecting her specialization in Neurology. Her special area of interest encompasses Cognitive Neurosciences and EEG Electrophysiology. With a notable publication record, Dr. Aghoram has contributed to research in various aspects of neurology.

In addition to her academic pursuits, Dr. Aghoram actively participates in clinical work, conducting special clinics for Neurodegenerative diseases and General Neurology, Neuromuscular clinic, and for Epilepsy. This reflects her commitment to addressing a range of neurological conditions and providing specialized care.

Based in India, Dr. Rajeswari Aghoram continues to make valuable contributions to the field of Neurology through her clinical practice, research endeavors, and commitment to advancing patient care.

Webpage: https://jipmer.edu.in/users/drrajeswari

Richard Leahy is chair of the Ming Hsieh Department of Electrical and Computer Engineering at USC. He holds the Leonard Silverman Chair in Electrical and Computer Engineering with joint appointments in Biomedical Engineering and Radiology. His research interests lie in the application of signal and image processing to the formation and analysis of biomedical images, with applications in neuroimaging and molecular imaging using PET, MRI and EEG/MEG. His currently work is focused on the study and treatment of epilepsy, other neurological disorders, and mental health. Dr. Leahy is a Fellow of the IEEE and recipient of the 2010 Hoffman Medical Imaging Scientist Award from the IEEE Nuclear and Plasma Sciences Society.  He was general conference chair for IPMI2001, IEEE ISBI 2004 and Fully3D 2013 and has held editorial positions with IEEE Trans Med Imaging, Phys Med Bio and Neuroimage. 

Webpage: https://viterbi.usc.edu/directory/faculty/Leahy/Richard

Rini A. Sharon (Student Member, IEEE) received the bachelor’s degree in electronics and communication engineering from the Vellore Institute of Technology, Vellore, India, in 2015. She completed her Ph.D. in the Electrical Department at IIT Madras, Chennai, India. From 2015 to 2016, she worked as an Associate Engineer at Caterpillar Pvt., Ltd., Chennai. During her time at IIT Madras, she served as a Teaching Assistant. Rini has published eight articles to date and is also an Active Science Communicator. Her research interests include speech processing, computational brain research, and other areas of machine learning and signal processing. She is currently with Amazon.

Prof. S. Umesh is a Professor in the Department of Electrical Engineering at the Indian Institute of Technology — Madras. He holds a Ph.D. from the University of Rhode Island, USA (1993), M.E. (Hons.) from the Madras Institute of Technology, Chennai (1989), and B.E. (Hons.) from Birla Institute of Technology & Science, Pilani (1987).

His research interests cover Automatic Speech Recognition, Speaker Normalization & Adaptation, Self Supervised Learning, Deep Learning, Machine Learning, and Speaker Recognition & Diarisation. Prof. Umesh has a history of international collaborations, having worked as a Visiting Researcher at RWTH-Aachen, Germany, Cambridge University Engg. Dept., UK, and AT&T Laboratories-Research, USA. He also served as faculty at IIT-Kanpur from June 1996 to July 2009, progressing from Assistant Professor to Professor.

Prof. Umesh's contributions to academia have been acknowledged with awards such as the AICTE Career Award for Young Teachers (1997) and the Alexander von Humboldt Research Fellowship (2004). With diverse research interests, Prof. S. Umesh continues to make notable contributions to Electrical Engineering, particularly in the domains of speech and machine learning.

Webpage: https://www.ee.iitm.ac.in/~umeshs/

Shrikanth (Shri) Narayanan is University Professor and Niki & C. L. Max Nikias Chair in Engineering at the University of Southern California (USC), where he is Professor of Electrical & Computer Engineering, Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, and Otolaryngology—Head & Neck Surgery, Director of the Ming Hsieh Institute and Research Director of the Information Sciences Institute. Prior to USC, he was with AT&T Bell Labs and AT&T Research. His interdisciplinary research focuses on human-centered sensing/imaging, signal processing, and machine intelligence centered on human communication, interaction, emotions, and behavior.  He is a Fellow the Acoustical Society of America, IEEE, International Speech Communication Association (ISCA), the American Association for the Advancement of Science, the Association for Psychological Science, the Association for the Advancement of Affective Computing, the American Institute for Medical and Biological Engineering, and the National Academy of Inventors. He is a Guggenheim Fellow and member of the European Academy of Sciences and Arts, and a recipient of many awards for research and education including the 2023 ISCA Medal for Scientific Achievement, the IEEE SPS Claude Shannon-Harry Nyquist Technical Achievement Award,  and the 2023 Richard Deswarte Prize in Digital History. He has published widely and his inventions have led to technology commercialization including through startups he co-founded: Behavioral Signals Technologies focused on AI based conversational assistance and Lyssn focused on mental health care and quality assurance.

Webpage: https://viterbi.usc.edu/directory/faculty/Narayanan/Shrikanth

Sridharan Devarajan received his Bachelor's and Master's (dual) engineering degrees from the Indian Institute of Technology (IIT), Madras. He completed his Ph.D. in Neuroscience as a Stanford Graduate Fellow and subsequent postdoctoral training as a Dean’s Fellow at the Stanford University School of Medicine. At Stanford, he investigated the neural basis of attention and executive control with functional neuroimaging (fMRI), electrophysiology, and neuromorphic computational modeling. He set up his lab in 2015 at IISc, Bangalore, where he is now an Associate Professor at the Centre for Neuroscience and an associate faculty of Computer Science and Automation. His group studies how attention works in the human brain, combining experimental and computational approaches, including functional neuroimaging, non-invasive neurostimulation, and real-time neurofeedback. He also collaborates with Google Research, developing deep-learning and artificial intelligence (AI)-based models for healthcare applications. Awards include a Wellcome Trust-DBT India Alliance Fellowship, a SERB Early Career Award, a Pratiksha Trust Young Investigator Award, and a DST Swarna Jayanti Fellowship.

Webpage: https://cns.iisc.ac.in/sridhar/

Sriram Ganapathy is a faculty member at the Department of Electrical Engineering, Indian Institute of Science, Bangalore. Previously, he was a research staff member at the IBM Watson Research Center. He received his PhD from the Center of Language and Speech Processing, Johns Hopkins University. His research interests include signal processing and machine learning applied to speech recognition, speaker recognition and auditory neuroscience. He is a member of the ISCA and a senior member of the IEEE.

Webpage: https://ee.iisc.ac.in/sriram-ganapathy/

I am the Chief Scientist at Modality.AI, which offers clinically-validated and HIPAA-compliant solutions for remote patient monitoring and assessment of neurological and mental health. Modality.AI uses a conversational AI system to monitor patients' speech and facial responses through browser-based video calls.

I am also an Adjunct Assistant Professor in the Department of Otolaryngology - Head and Neck Surgery at the University of California, San Francisco (UCSF), where I collaborate with Dr. John Houde and Dr. Srikantan Nagarajan on speech motor control modeling research.

I was previously a Managing Senior Research Scientist in the R&D division at Educational Testing Services (ETS), where I managed the San Francisco Office and directed dialog and multimodal systems research with applications to language learning and behavioral assessment. Our team was awarded the prestigious ETS Presidential Award for our work on multimodal dialog systems. I earned my M.S and Ph.D degrees at the University of Southern California where I worked with an amazing and interdisciplinary group of researchers to explore the cognitive and technological aspects of speech science. My principal advisor was Dr. Shrikanth Narayanan.

Webpage: https://www.vikramr.com/