Yubin Kim

Biography:

 Dr. Yubin Kim is the Co-Founder and Chief Science Officer at Vody, a generative AI startup focused on transforming e-commerce discovery using multimodal large language models. At Vody, she leads scientific strategy and product development, building systems that enhance product search, recommendations, and catalog understanding by combining structured data with visual and textual signals.

Yubin holds a Ph.D. in Language Technologies from Carnegie Mellon University, where her research focused on information retrieval, distributed selective search, and retrieval system evaluation.  Before founding Vody, Dr. Kim held key applied machine learning roles in industry, including leading search and recommendation teams at Etsy, where she worked on improving buyer experience through personalized discovery systems. She has a track record of translating rigorous research into impactful, user-facing products.

In addition to her industry work, Yubin is active in the research community. She has served as a program committee member, organizer, and reviewer for top conferences such as SIGIR, CIKM, and ICTIR, and is a frequent speaker at workshops and forums bridging academia and industry.

Gautam Solaimalai

Biography:

Gautam Solaimalai is a Vice President and Senior Software Engineering Manager at U.S. Bancorp, specializing in cloud-native enterprise architecture, AI-driven automation, and financial technology innovation. With over 15 years of experience across industry leaders like Honeywell, OneTrust, and U.S. Bank, Gautam has led strategic product development and digital transformation initiatives that power secure, scalable financial platforms. He is a published author in IEEE journals, a peer reviewer for global tech conferences, and a recipient of multiple innovation and excellence awards. Gautam is also an active contributor to the technology community through mentoring, technical leadership, and applied research in AI, IoT, and DevOps.

Shaleen Kumar Gupta

Biography:

Shaleen works on Google Search's AI Mode, focusing on post-training its multi-step, thinking and advanced reasoning LLM agent to enhance response quality and factuality. Previously, he made contributions to AI Overviews for search verticals. His past work involved training Multitasking Unified Model (MUM) based ranking models for search verticals and developing multimodal ranking for short videos and shopping. Throughout his time at Google, his efforts have centered on improving retrieval, ranking, and response generation for various search applications.

Vishal Jain

Biography:

Vishal Jain is a Staff software engineer at Meta and works on building scalable digital solutions. With extensive experience in quantitative finance and technology leadership roles at Meta, Two Sigma, and Bloomberg, he brings expertise in developing innovative solutions across industries. Vishal’s strong foundation in engineering and data-driven problem-solving, supported by his education at IIT Kanpur and Columbia University, positions him as a forward-thinking leader in the tech space.

Abhay Khosla

Biography:

Abhay Khosla is a Software Engineer at Google, specializing in large-scale distributed systems and applied machine learning. He has previously worked as a Machine Learning Engineer at Ocrolus, where he developed state-of-the-art computer vision models and benchmarking platforms, and as a Research Software Engineer at IBM Research, where he focused on natural language processing and knowledge graph population for AI-driven applications. Abhay holds an M.S. in Computer Science (Machine Learning Track) from Columbia University and a B.Tech. (Hons.) in Electronics and Electrical Communication Engineering with a Minor in Computer Science from IIT Kharagpur. His experience spans building scalable AI systems, deep learning research, and deploying production-grade ML services

Rahul Raja

Biography:

Rahul is a Staff Engineer at LinkedIn, where he is a part of the AI Infrastructure team. With over a decade of experience in designing and building large-scale distributed systems, Rahul has led several critical projects that support LinkedIn's machine learning and AI workloads at scale. He is a graduate from Carnegie Mellon University, and his work focuses on creating robust, high-performance infrastructure that powers intelligent applications.

Harsh Varshney

Biography:

Harsh Varshney is a Software Engineer at Google, working in the Chrome organization on privacy-preserving web infrastructure and intellectual property (IP) protection systems. He contributed to the Privacy Sandbox initiative, including the Third-Party Cookies Deprecation (3PCD) and User Cookie Choice (UCC) projects, focusing on building secure, large-scale distributed systems that protect user privacy and safeguard proprietary data while enabling a thriving open web ecosystem.

Previously, Harsh has architected and scaled data-intensive systems at Google, Splunk (now Cisco), AWS Redshift, Amazon, and Walmart, enabling real-time analytics at massive scale. He has led initiatives in observability, developed in-memory databases handling billions of metric time series per day, and designed token-based authentication and privacy-preserving infrastructure across cloud environments.

Harsh holds a Master’s degree in Software Engineering from Carnegie Mellon University’s School of Computer Science, where he studied under pioneers in software architecture, and a B.Tech. in Electrical & Electronics Engineering and Physics from BITS Pilani. He has delivered guest lectures at CMU and San Jose State University on distributed systems and software architecture and was featured in the CMU School of Computer Science Alumni Spotlight.