Dec 20, 2025
10:30 am - 11:30 am
From Data to Intelligence - Emerging Paradigms in Data, AI, and Human–Machine Collaboration
Bio: Dr. Varsha Jain is a seasoned technology leader who leads the AI innovation charter at Persistent Systems. She plays a pivotal role in shaping the organization’s technology vision and driving the development of transformative AI solutions. With a strong focus on strategic alignment, she ensures that AI initiatives are closely tied to business objectives, delivering measurable impact and sustainable competitive advantage for the company and its clients.
AI Innovations for Cancer Management and Research
Bio: Dr. Santosh Dixit is the Chief Domain Expert ( Healthcare and Life Sciences) at Persistent Systems. In this capacity, Dr. Dixit works with multi-disciplinary teams of clinicians, healthcare professionals, data scientists and technologists for developing AI/GenAI-powered digital innovations for biomedical ecosystems with a special focus on Oncology. Dr. Dixit has 20+ years of experience in Preclinical and Clinical Pharmacology, Translational R&D, Drugs/Diagnostics/Medical device development, Regulatory Affairs, Public health and Policy initiatives. Dr. Dixit has received his Ph.D. in Pharmaceutical Sciences from University of Cincinnati, USA and post-doctoral fellowships from Vanderbilt University, USA and University of Western Ontario, Canada.
Building scalable decision support systems for omni-channel fulfilment
Bio: Sharad is a Sr. Director Data Sciences, at Target in India, the fully integrated global capability center and strategic partner for Target Corporation. Sharad is responsible for building and delivering data science solutions for Target’s Global supply chain and Logistics (GSCL) across inventory management, digital fulfilment, warehousing, and transportation for Target’s replenishment and allocation business. His team focuses on developing highly scalable, low latency solutions for Target’s omnichannel business using optimization, simulation, and ML models.
Sharad joined Target in 2013 and has been instrumental in expanding data science across multiple areas of supply chain and logistics. These capabilities help deliver best in class experiences for Target guests by ensuring that the right products, are present at the right place, at the right time and in right quantity.
Sharad has a master's degree in industrial engineering and operations research from the University of Florida. Outside of work, he enjoys traveling, hiking and photography.
Algorithmic decision making in Ad Tech through targeting and smart bidding
Bio: Jayanta studied in ISI Kolkata before acquiring PhD in Statistics from University of Michigan. After a brief stint in US as a faculty in Duke University, he moved to India and joined the nascent Data Science field in 2008. He has worked as scientist and analytics leader in multiple organisations like HP, GM, GE before building the Telematics (mobile based Auto Insurance) product in Zendrive as a start-up. He joined InMobi as the Data Science leader in 2024 and shaped the future of DSP using cutting-edge ML techniques in conjunction with fundamental Statistical methods.
Inventing What’s Next at IBM Research India
Bio: Prateeti Mohapatra is a Senior Technical Staff Member and Manager at IBM Research Lab India, working with a team of researchers in IT Automation, Observability and Cognitive Support. Her current focus is on bringing AI solutions to IT operations, providing more insights with reactive, predictive, and proactive capabilities across the application life cycle. She currently heads the AI for Automation and Interaction sub-theme globally at IBM Research. She has received numerous awards, including Research Division awards and Outstanding Technical Achievement awards in Cognitive Support and IT Automation.
Bio: Shiv Tavker is an applied scientist on the World Wide Pricing Team and has a background in optimization, machine learning, natural language processing, deep learning and bandits. He currently focuses on large language model adaptation, multilingual modeling, and vision models. Prior to joining Amazon, he was a dual degree data science student at the Indian Institute Of Technology–Madras (IIT–Madras).
Empathetic 3D Avatars: Humanizing AI Through Multimodal Systems
Bio: Ajai Devanathan is Vice President and Lead Computer Vision at Openstream.AI, specializing in GenAI, multimodal LLMs, deep learning, and 3D vision. He leads R&D on empathetic conversational avatars and context-aware dialogue systems that fuse language, vision, and structured knowledge to deliver truly cognitive digital agents.
His work spans agentic multimodal frameworks, vector databases, neuro-symbolic reasoning, and explainable AI, with applications from healthcare and enterprise knowledge extraction to security. Ajai is currently a Ph.D. scholar in Multimodal AI and XAI at Amrita University, building on an M.Tech in AI and ML (with distinction) from PES University and a B.Tech in Computer Science from BMS College of Engineering. He has authored work on explainability of neural networks, medical information dialogue systems, and threat-intent detection for the Indian Army. Passionate about building the next AI horizon, Ajai combines academic rigor with hands-on leadership in real-world AI products across healthcare, defense, education, and enterprise.
Research at Adobe
Bio: Tejas is a Senior Research Scientist with nearly a decade of experience in industry research and applied science. At Adobe, Tejas works on document transformations, driving innovations that enhance customer experiences through AI-powered solutions.
Previously, Tejas was Principal Data and Applied Scientist and manager at Microsoft’s Turing team in Bengaluru, where he led efforts to generate “follow-up” questions and suggestions for Microsoft Copilot. Earlier, at IBM Research Lab, Tejas managed teams building NLP solutions for Indic languages and education technology, earning three Outstanding Technical Achievement Awards.
Tejas holds a Ph.D. in Computer Science from IIIT-Delhi, specializing in Machine Learning and Biometrics for face recognition. His research has received 1,700 citations, with an h-index of 18 and i10-index of 23, and one of his works earned the Highest Impact Award at the CVPR Biometrics Workshop. He has co-authored multiple patents in education technology and served as guest faculty at IIT-Jodhpur, teaching MLOps for three years.
Outside work, Tejas enjoys cycling, walking, and spending time with family.
Reimagining Talent Lifecycle using AI
Bio: Kuldeep is an AI leader with a decade of experience in developing AI products serving millions of users. Currently, he is the SVP of AI and head of R&D Labs at SHL, where he leads a global team to create innovative AI-powered HRTech software and platforms. He has previously worked as a Research Scientist at Xerox Research and was a founding member and CTO of VideoKen. Kuldeep holds a PhD in Computer Science and has published several research papers in leading AI conferences.
Navigating the Frontiers of Trust with AI at IDfy
Bio: Gurudatt Bhobe is a seasoned data science leader with over 16 years of experience building high-performing machine learning teams and products across industries. He currently works at IDfy, where he focuses on designing and scaling ML-driven systems for fraud detection, risk identification, and secure onboarding. His expertise spans machine learning, computer vision, MLOps, API products, and secure ML, with a growing focus on LLMs, AI agents, AIOps, and resilient cloud-native systems.
Previously, Gurudatt has held leadership roles at organizations such as Servify, where he built a world-class data platform and team, and SupplyAI, where he was Co-Founder and COO, working on the world’s first AI-powered platform for detecting and preventing retail returns fraud. He holds a PGDM from MDI Gurgaon and a B.E. in Electrical Engineering from VJTI Mumbai.
At IDfy, Gurudatt is actively hiring experienced computer vision engineers and scientists to build the future of fraud detection using cutting-edge applied AI at scale.