Y Combinator

Datacast Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

Datacast Episode 100: Data-Centric Computer Vision, Productizing AI, and Scaling a Global Startup with Hyun Kim

Hyun Kim is the co-founder and CEO of Superb AI, an ML DataOps platform that helps computer vision teams automate and manage the entire data pipeline: from ingestion and labeling to data quality assessment and delivery. He initially studied Biomedical Engineering and Electrical Engineering at Duke but shifted from genetic engineering to robotics and deep learning. He then pursued a Ph.D. in computer science at Duke with a focus on Robotics and Deep Learning but ended up taking leave to further immerse himself in the world of AI R&D at a corporate research lab. During this time, he started to experience the bottlenecks and obstacles that many companies still face to this day: data labeling and management were very manual, and the available solutions were nowhere near sufficient.

Datacast Episode 90: Operational Analytics, Reverse ETL, and Finding Product-Market Fit with Kashish Gupta

Datacast Episode 90: Operational Analytics, Reverse ETL, and Finding Product-Market Fit with Kashish Gupta

Kashish Gupta is the founder and co-CEO of Hightouch, a data startup based out of San Francisco. He grew up in Atlanta, loves playing racket sports, and always wanted to be an inventor when he grew up. He studied Machine Learning in college and had a short stint at a VC firm called Bessemer Venture Partners, and ever since graduating has been working on Startups. He and his co-founders are on their 5th business idea and have finally found a product-market fit.

Datacast Episode 82: Enabling AI-Powered AR Navigation For Driving with Chen-Ping Yu

Datacast Episode 82: Enabling AI-Powered AR Navigation For Driving with Chen-Ping Yu

Dr. Chen-Ping Yu is the co-founder and CEO of Phiar, a company that is bringing human-like perception to every vehicle with its advanced lightweight spatial AI. Prior to founding Phiar, he was a postdoctoral fellow at Harvard University, researching neuro-inspired deep learning.

Chen-Ping received his Ph.D. from Stony Brook University in Computer Vision and Machine Learning and his MS from Penn State University. He was the recipient of numerous honors and awards, including from the NSF, and has published more than 15 scientific publications at top computer vision, AI, and cognitive science conferences and journals.

Datacast Episode 75: Commoditizing Data Integration Pipelines with Michel Tricot

Datacast Episode 75: Commoditizing Data Integration Pipelines with Michel Tricot

Michel Tricot has been working in data engineering for 15 years. Originally from France, Michel came to the US in 2011 to join a small startup named LiveRamp. As the company grew, he became the Head of Integrations and Director of Engineering, where his team built and scaled over 1,000 data ingestion and distribution connectors to replicate hundreds of TB worth of data every day. 

After LiveRamp’s acquisition and later IPO (NYSE:RAMP), he wanted to return to an early-stage startup. So he joined rideOS as Director of Engineering, again deep in data engineering. While there, he realized that companies were always trying to solve the same problem repeatedly, which should be solved once and for all. 

This was when he decided to start a new company, and Airbyte was born.

Datacast Episode 72: Folding Data with Gleb Mezhanskiy

Datacast Episode 72: Folding Data with Gleb Mezhanskiy

Gleb Mezhanskiy is the CEO & Co-founder of Datafold -  a data observability platform that helps companies unlock growth through more effective and reliable use of their analytical data. As a founding member of Data teams at Autodesk and Lyft and the Head of Product at Phantom Auto, Gleb has built some of the world's largest and most sophisticated data platforms and has developed tooling to improve productivity and data quality in organizations with hundreds of data users.

Datacast Episode 67: Model Observability, AI Ethics, and ML Infrastructure Ecosystem with Aparna Dhinakaran

Datacast Episode 67: Model Observability, AI Ethics, and ML Infrastructure Ecosystem with Aparna Dhinakaran

Aparna Dhinakaran is the Chief Product Officer at Arize AI, a startup focused on ML Observability. She was previously an ML engineer at Uber, Apple, and TubeMogul (acquired by Adobe). During her time at Uber, she built several core ML Infrastructure platforms, including Michelangelo. She has a bachelor’s from Berkeley's Electrical Engineering and Computer Science program, where she published research with Berkeley's AI Research group. She is on a leave of absence from the Computer Vision Ph.D. program at Cornell University.

Datacast Episode 55: Making Apache Spark Developer-Friendly and Cost-Effective with Jean-Yves Stephan

Datacast Episode 55: Making Apache Spark Developer-Friendly and Cost-Effective with Jean-Yves Stephan

Jean-Yves (or "J-Y") Stephan is the CEO & Co-Founder of Data Mechanics, a Y-Combinator-backed startup building a data engineering platform that makes Apache Spark more developer-friendly and more cost-effective. Before Data Mechanics, he was a software engineer at Databricks, the unified analytics platform created by Apache Spark's founders. JY did his undergraduate studies in Computer Science & Applied Math at Ecole Polytechnique (Paris, France) before pursuing a Masters at Stanford in Management Science & Engineering.