MMLSpark: Lessons from Building a SparkML Compatible Machine Learning Library

Watch Next

• 

  Expanding Flows for Fast and Flexible Generation Beyond the Fixed Canvas

  July 21, 2026

  • Sophia Tang
• 

  Microsoft AI for Good Lab - Introduction to HASTE

  July 17, 2026

  • Juan M. Lavista Ferres,
  • Caleb Robinson,
  • Cameron Birge

  , et. al.
• 

  Learning Genetic Perturbation Effects at Single-Cell Resolution for Virtual Cells

  July 14, 2026

  • Jiaqi Zhang
• 

  Convergence Analysis for Fast High-Order ODE Solvers in Diffusion Probabilistic Models

  July 7, 2026

  • Zhengjiang Lin
• 

  Reinforce Adjoint Matching: Scaling Diffusion RL

  June 30, 2026

  • Andreas Bergmeister
• 

  Plenary Talk 2: Reimagining Education and Skilling for the Age of AI: Challenges & Opportunities

  June 9, 2026

  • Manohar Swaminathan
• 

  Session on Retrieval

  June 9, 2026

  • Lokesh Nagalapatti,
  • Soumen Chakrabarti
• 

  Session on Inclusive AI: Data, Models, Evaluation

  June 9, 2026

  • Niloy Ganguly,
  • Danish Pruthi,
  • Sunayana Sitaram

  , et. al.
• 

  Plenary Talk 1: Navigating the AI Horizon: Promises, Perils, and the Power of Collaboration

  June 9, 2026

  • Ece Kamar,
  • Srinivasan Iyengar
• 

  Welcome Session - Microsoft Research India Academic Summit 2026

  June 9, 2026

  • Venkat Padmanabhan,
  • Srinivasan Iyengar