Jet New is a founder and AI practitioner with 8 years of experience building production ML systems and research-driven products from Singapore. Currently leading Atlas, an AI-native visual research workspace, he also directs AgentScale AI where he helps deliver end-to-end AI solutions for enterprise clients. His background spans data science at Indeed (experimenting on recommendation features for >300M users), reinforcement learning research at NUS (improving transformer generalization and representation learning), and probabilistic modelling at Grab. Jet combines hands-on engineering—Spark, Airflow, TensorFlow Probability, Bayesian optimization—with academic rigor, and has a track record of turning research insights into deployable systems and client-winning products. An under-the-radar strength is his ability to bridge multi-agent research insights into practical, verifiable tooling for exploratory workflows.
8 years of coding experience
2 years of employment as a software developer
Korea University Winter School, Korea University Winter School at Korea University
Academic Programme, Academic Programme at NUS University Scholars Programme
Bachelor of Computing, Computer Science, Bachelor of Computing, Computer Science at National University of Singapore
Code repository for the research project "You Play Ball, I Play Ball: Bayesian Multi-Agent Reinforcement Learning for Slime Volleyball", won 1st Prize at 17th STePS.
Contributions:6 commits, 4 pushes, 1 branch in 6 months
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