Day -1 (March 29th 8:00AM-6:00PM (PST)) 

8:00 AM - 8:30 AM Registration
8:30 AM - 8:55AM Technical:  Decoding ChatGPT – Understanding the Algorithm & Its Application in Finance (Debasmita Das, Manager, MasterCard)
9.00 AM - 9.30 AM Technical: Are LLMs all you need? (Ted Way, Principal PM Lead, Microsoft
9.35AM - 10.05AM Technical: Building and evaluating Generative AI applications for NLP (Divyansh Agarwal, Sr. Research Engineer, Salesforce)
10.10AM  - 10.40AM  Keynote:  Responsible use of Generative AI in the Enterprise (Ali Arsanjani, Director-Cloud Partner Engineering, Google)
10.40AM - 10.50AM Break
10.50AM - 11.20AM Technical: Trends in Personalized Video Recommendations (Amey Porobo Dharwadker, AI Technology Leader, Meta)
11.25AM - 11.55AM

Technical: The Technology behind ChatGPT (Junling Hu, CEO,

12.00PM - 12.30PM Business: Risks and Opportunities in Generative AI (Eric Riz, CEO, VERIFIED)
12-35PM - 1.05PM Business: ChatGPT is 20 years behind! (Paul Edelblut, VP of Products, Vantage Labs)
1.05PM - 1.35PM Lunch Break
1.35PM - 2.05PM Business:  ChatGPT: More Than Just A Machine (West McDonald, Founder, West McDonald Co.
2.10PM - 2.40PM Technical: How to build a question/answer engine with python and NLP (Swagata Ashwani, Data Scientist, Boomi)
2.45PM - 3.15PM Business:  Enterprise AI apps (Venkata Duvvuri, Senior Scientist Tech Lead, Nvidia)
3.15PM - 3.25PM Break
3.25PM - 3.55PM Business: AI - The jack of all trades? (Sumeet Ahuja, VP of Product,​ Former Circle)
4.00PM - 4.30PM Technical: Detecting Deepfakes Using Machine Learning on Audio (Sneha Muppalla, Student, Cupertino High School)
4.35PM - 5.05PM Technical: Product Led Growth: A new and upcoming concept in consumer tech products (Kunal Khadilkar, Data Scientist, Adobe)
5.10 PM - 5.40PM Technical: Content Moderation via AIML and mechanical Turk (Rakhee Singhal, CEO, Actionable Analytics Group)

Day -2 (March 30th 7:45AM-5:30PM (PST))

7:45 AM - 8:00 AM Registration
8:00 AM - 8:25 AM
Techincal: Will AI Steal My Job? — Experiments with an AI Recruiter Chatbot in the Age of GPT/LLM ​(Keisuke Inoue, Data Scientist, Pandologic)
8.30 AM - 8.55 AM Business: Trusted AI - when data cannot be trusted (Sandhya Gopalan, AI & MLOps Practice Head, EY Global Delivery 
9.00AM - 9.30AM Business: Future of AI (Massimo Buonomo, Senior Advisor, Global Expert)
9.35AM - 10.05AM Business: AI 2025 - Four gAMe-changing AI trends of the intelligent business fabric (Soumen Chatterjee, AVP (Data &  AI), HCL Technologies
10.10AM  - 10.40AM Keynote: Metaverse Equality and Tech: If we do what we have always done, we will get what we have gotten (Michelle Pruitt, Director, Microsoft)
10:40 AM - 10:50AM Break
10.50AM - 11.20AM Business: Observability and AIOPs  (Shailesh Basani, ex-Director, Adobe)
11.25AM - 11.55AM Technical: LakeHouse: Smart Iceberg Table Optimizer (Rajasekhar Konda, Senior Engineering Leader, Apple & Hongyue Zhang, Software Engineer, Apple)
12.00PM - 12.30PM TechnicalCloud Cost Optimization (Raju Shreewastava, CEO, Big Data Trunk)
12-35PM - 1.05PM Technical: Low code and AI (Praveen K Tomar, Technology Lead, Office for National Statistics
1.05PM - 1.35PM Lunch Break
1.35PM - 2.05PM Business:  Challenges in financial monitoring for blockchain transactions (Leah McFarland, Product Management, State Street)
2.10PM - 2.40PM Technical: Operationalizing data-centric AI: Practical methods to quickly improve ML datasets
2.45PM - 3.15PM

Technical: Responsible AI (Ricardo Baeza-Yates, Institute for Experiential AI, Northeastern University)

3.20PM - 5.20PM Workshop:  Adaptive ML Algorithms with Python (Chanchal Chatterjee, Senior Deep Learning Software Leader, NVIDIA)

Day -3 (March 31st 7:45AM-5:30PM (PST))

7:45 AM - 8:00 AM Registration
8.00AM - 8.25AM Business:  Building an AI Job search companion: Approach and Learnings (Somnath Biswas, Product Management, TotalJobs Group)
8.30AM - 8.55AM Business: Commercializing AI: Focus on Better Customer Experience, NOT Better Algorithms (Anish Agarwal, Global Head of Analyticsl, Dr. Reddy's Laboratories)
9.00AM - 9.30AM Business: AI/Machine Learning use cases in the telecommunication industry (Dan Mo, Director, Ericsson)
9.35AM - 10.05AM Business: AI in Healthcare (Kerrie Holley, Directorl, Google)
10.10AM  - 10.40AM  Keynote : Delivering Fair, Safe and Effective NLP Models with Open-Source Tools (David Talby, CTOl, John Snow Labs)
10.40AM - 10.50AM Break
10.50AM - 11.20AM Business: Accelerating Machine Learning in Healthcare and Life Sciences on Amazon Web Services (Joshua Broyde, Solution Architectl, Amazon Web Services)
11.25AM - 11.55AM Technical: Digital products' global regulations and the impact (Wenjing Wang, Director, Merck)
12.00PM - 12.30PM Technical: Explainability and interpretability in Medical AI (Shubham - Patil, Data Scientistl, Stryker)
12:30 PM - 1:00PM Lunch Break
1.00PM - 1.30PM Business: Modeling Imaging Phenotypes to predict Omic profiles in Cancer (Shrey Sukhadial, Asisstant Director, Dartmouth-Hitchcock)
1.35PM - 2.05PM Technical: AI biologic design (Stefan Lukianovl, CEOl, Salve Therapeutics)
2.10PM - 2.40PM

BusinessSentient Search (Marianne Sweenyl, Principall, Daedalus Information Systems)

2.40PM - 2.50PM Break
2.50PM - 3.20PM Technical: Journey from rapid Experimentation to distributed training: Develop your deep learning model for cancer diagnosis (Sarita Joshi, AI Specialist, Google & Ayo Adedeji, AI Specialist, Google)
3.25PM - 4.05PM

Keynote Panel: AI in Healthcare

Rohan Singh Rajput (Sr. Data Scientist, Headspace)
Venkatraghavan Sundaram (Manager, PCCI)
Rathnakumar Udayakumar (Product Management, Netradyne) - Moderator
4.10 PM - 4.40 PM Data Mesh in Action - the business perspective (Marian Siwiak, Chief Data Officer, Cognition Shared Solutions)
4:45PM -  5: 15 PM Insurance(Subrogation) and AI (Abhishek Rai, Senior Data Scientist, Gigaforce)

NOTE: Agenda and speakers subject to change without notice