IIIT Hyderabad, India.
Big Data in Cognitive Neuroscience: Opportunities and Challenges
Cognitive brain mapping is enjoying its growth with the availability of large open data sharing efforts as well as the application of modern machine learning and deep learning methods. In this talk, about the current practices in cognitive neuroscience predominantly focusing on functional imaging and highlight the tremendous opportunities fostered by the unprecedented scale of datasets in cognitive neuroscience. I also discuss challenges and limitations to keep in mind while working with these datasets.
Dr. S. Bapi Raju is a professor and head of the Cognitive Science Lab, IIIT Hyderabad. He was a former professor of School of Computer and Information Sciences, University of Hyderabad, Hyderabad, India during 1999-2019. He worked as a Researcher at ATR Research Labs, Kyoto, Japan and as an EPSRC Research Fellow at University of Plymouth, UK before returning to India. He has over 20 years of teaching and research experience in AI, Machine Learning, Neural Networks and Cognitive Science. 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 is also currently heading the Healthcare vertical in the DST-funded National Mission for Cyberphysical Systems (NM-CPS) Technology Innovation Hub under at IIIT Hyderabad called IHub-Data.
He has degrees in BE (Electrical Engineering) from Osmania University, MS (Biomedical Engineering) and 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.
Advances in NLP Research for Automated Business Intelligence
Automated business intelligence derives insights from data to help businesses make right decisions for their business processes. These business processes can range from back end IT operations, to designing and executing a marketing campaign, to creating a business strategy, among many others. Automated business intelligence attempts to automate these processes by removing dependency on human, by providing them new ways to interact with data. Some of these interactions, which not so long ago seemed almost impossible, have now become possible due to the recent advances in NLP, and particularly, in deep learning and large language models. Specifying a SQL query in natural language, let the data speak for itself in human understandable text, being able to converse with data and get insights are few examples of such interactions. In this talk, we will cover some of these recent advances in NLP research, and how they are influencing the area of automated business intelligence. The talk shall cover both, an industrial view of the automated business intelligence in the form of available tools; and an academic view in the form of technical problems. We will cover a range of technical problems including data search and exploration through semantic technologies, data insights via natural language querying and free form interaction, and use of NLP for exploratory data analysis including for data insights and data stories. We will conclude the talk with some food for thought by discussing open research problems in this space.
Arvind Agarwal is a Senior Technical Staff Member and Manager at IBM Research, India (Gurgaon) where he leads a team of research scientists and software developers to develop solutions in the space of AI-driven data processing and data analytics. Prior to joining IBM, he was a research scientist at Palo Alto Research Centre (PARC), Webster, New York. His research interests are in the areas of machine learning, natural language processing, deep learning, and text analytics . He is especially interested in conversational data analytics, and in machine learning sub-areas that deal with the problem of limited supervised data, such as self-learning, semi(un)-supervised learning, zero shot learning, domain adaptation, multitask learning etc. Arvind completed his PhD in Computer Science from University of Maryland, his M.S. in Computer Science from University of Utah and Bachelor’s from Birla Institute of Technology & Science, Pilani. He has about 20 patents, and more than 35 publications in top ML and NLP conference such as EMNLP, AAAI, KDD, NIPS, IJCAI, ATSTATS. He is also a recipient of Heidelberg Laureate Forum Young Researchers award, and ECML 2010 best student paper award.
Bank of America,
The role and use of big data in banking , in driving towards customer centric insights and the challenges in implementing effective and scalable solutions
Big data is bringing a drastic shift in the operations of modern banking by allowing them to access vast data volumes and extract valuable insights. Bank uses this data to make decisions daily and improve Consumer Banking clients through reporting, analytics and insights about the bank's financial relationship with them. Big Data is helping the bank to shift from a product centralized view to a client centralized view by obtaining data in batch and near real time format, analyze the data through different channels and prepare/present the data in graphical format. With more and more Banking products getting merged with the Big Data Platform, I will discuss about the Big data infrastructure that we are currently managing, the complex use cases that we solve day in and day out and the key challenges in handling large volume of data securely and enhancements that are being brought about in the Big data infrastructure.
Sridhar Viswanathan, working as architect at BA Continuum India Pvt Ltd, Hyderabad India. I have over 17 years of experience in Big Data, Statistical and business analytics. Skilled in Java, Big Data systems, Hadoop, Spark, Kafka, Tableau and HBase. I have been with Bank for close to 11 years and involved in flagship projects by leading teams to achieve high performance and deliver complex technical solutions. I have also trained professionals on Data visualization. I have interests on engineering problems related to real time streaming and enjoy solving then and learn lessons from failures. I have completed executive masters in data science from IIT Hyderabad in 2017. Prior to that i have worked in Deloitte and Accenture in healthcare, health insurance and banking domains. I have bachelor degree from Coimbatore institute of technology in information technology.
I have filed a patent (Patent Reference Number: P12952US01) on "Generating and providing enhanced user interfaces by implementing data, ai , intents and personalization (DAIP) technology."