The Speakers

Subba Reddy Oota

Subba Reddy Oota is a final-year PhD Student at Inria-Research at Bordeaux, France and a visiting scholar at Max Planck Institute for Software Systems. He received his Mas-ters from IIIT Hyderabad in 2016. His research interests are in the areas of language analysis in the brain, brain encoding, and decoding, grounded language acquisition, robot grounding, geometric deep learning, and brain imaging analysis. He has also presented several research papers in refereed conferences like ACL, NAACL, COLING, INTERSPEECH, ICASSP, CogSci, WACV, IJCNN, ICDAR, ICONIP, and workshop papers at NeurIPS conferences. He served as a reviewer for all the leading conferences like NeurIPS, ICML, ICLR, INTERSPEECH, ACL, ICASSP, AISTATS, ECML-PKDD, WACV, IJCNN, Cognitive Science Society Annual Conference, and ACM CHIL. He has a good experience in offering tutorials at top conferences like IJCAI, IJCNN and Cogsci. Following is a list of recent tutorials he has offered

Manish Gupta

Manish Gupta ( Homepage Link ) is a Principal Applied Researcher at Microsoft AI and Research at Hyderabad, India. He is also an Adjunct Faculty at a premier engineering school in India - International Institute of Information Technology, Hyderabad (IIIT-H) and a visiting faculty at the Indian School of Business (ISB). He received his Masters in Computer Science from IIT Bombay in 2007 and his Ph.D. from the University of Illinois at Urbana-Champaign in 2013. With research interests in the areas of deep learning, web mining and information retrieval, he has published more than 150 research papers in referred journals and conferences, including NAACL, EMNLP, COLING, WWW, SIGIR, ECIR, ICDE,

KDD, WSDM. He has also co-authored two books: one on Outlier Detection for Temporal Data and another one on Information Retrieval with Verbose Queries.

Manish has a strong track record of teaching. He taught a full credit course on Web Mining at IIIT-H, India in 2013 and in 2014. He currently teaches a course on Information Retrieval and Extraction (with Prof. Vasudeva Varma) at IIIT-H and on Deep Learning at ISB. He has an extensive experience in offering tutorials at top conferences. Following is a list of recent tutorials he has offered.

Raju S. Bapi

Raju S. Bapi is a professor and head of the Cognitive Science Lab, IIIT Hyderabad, India. Earlier he was a professor, School of Computer and Information Sciences, University of Hyderabad, Hyderabad, India for 20 years where he was also the Coordinator of Centre for Neural and Cognitive Sciences. He worked as an EPSRC Research Fellow at University of Plymouth, UK and as a Researcher at ATR Research Labs, Kyoto, Japan. He has over 20 years of teaching and research experience in AI, Machine Learning, Neural Networks and Cognitive Science. He has extensive experience in applying neuroimaging methods to study the brain function and conducted training courses in India to introduce clinicians to this fascinating area. He has worked on a variety of inter-governmental collaborative projects such as Indo-French, Indo-Trento, in the areas of computational and cognitive neuroscience with multidisciplinary teams comprising computer scientists, linguists, neuroscientists, psychologists and clinicians. He has a PhD (Computer Science) from University of Texas, Arlington, USA. He is a senior member of IEEE, a member of ACM, Society for Neuroscience, and Cognitive Science Society. He reviews regularly for IJCNN, WCCI, Cognitive Science Society Annual Conference. He has published several articles in leading conferences including IJCAI, journals such as Experimental Brain Research, Neuroimage, Trends in Cognitive Science, Nature Scientific Reports, Frontiers Psychology, Frontiers Human Neuroscience, etc. Following is a list of recent tutorials he has offered

Mariya Toneva

Mariya Toneva is a tenure-track faculty at the Max Planck Institute for Software Systems. She obtained her postdoctoral fellow at the Neuroscience Institute at Princeton University, and PhD from Carnegie Mellon University in a joint program between Machine Learning and Neural Computation in 2021. Her research focuses on building computational models of language processing in the brain that can also improve natural language processing systems. Her work has appeared at CogSci, ICLR, NeurIPS, and SNL, and she has organized tutorials, workshops and symposia at Cogsci, NeurIPS, ICLR and SNL

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