optimization

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Legend
Sarang Jagdale
Founder · Engineer · Executive

Sarang Jagdale

Sarang Jagdale is a PhD engineer turned supply chain AI co-founder who spent over two decades cracking some of the world's hardest logistics problems - from IBM's global consulting floors to the startup that eventually became Lyric. As Head of Decision Science at Lyric, he architects the algorithmic core of a platform now trusted by Coca-Cola, Google, and Mondelez to make their supply chains think for themselves. Lyric raised $43.5M in Series B funding in August 2025, bringing total funding to $67M.

supply-chain · aiRead →
Legend
BW
Executive · Operator · Engineer

Bill Wells

Bill Wells is the CEO of AMPL Optimization Inc., the Mountain View company behind AMPL, the algebraic modeling language born at Bell Labs that has long been a gold standard for large-scale mathematical optimization. A UC Berkeley-trained mathematician, Wells runs the small but globally influential team that turns business-critical decisions in energy, finance, supply chain, and transportation into solvable models, while steering the company from a classic modeling language toward a modern, API-driven optimization platform.

ampl · optimizationRead →
Legend
Penny Chen
Founder · Executive · Engineer

Penny Chen

Penny Chen is the co-founder and CEO of Pax, the Y Combinator (S24) startup rebuilding duty drawback - the U.S. program that refunds import tariffs - as an AI-native brokerage. An MIT PhD and former research scientist at Amazon and Flexport, she stumbled on duty drawback while building supply-chain algorithms and saw a math problem hiding inside a bureaucratic one: each year roughly $10-15 billion in eligible refunds go unclaimed because legacy brokers take 10-20% and won't touch claims under $100k. Pax turns the rulebook into algorithms and LLM data extraction, promising a TurboTax-style experience that cuts filing from 9-12 months to a few weeks. The company raised $4.5M in seed funding led by Initialized Capital in April 2025.

penny-chen · paxRead →
Legend
Carolyn Mooney
Founder · Executive · Engineer

Carolyn Mooney

Carolyn Mooney is the co-founder and CEO of Nextmv, a Philadelphia-based developer platform for building, testing, and deploying decision models - everything from vehicle routing to staff scheduling. A systems engineer by training, she ran missile simulations at Lockheed Martin, optimized pizza deliveries at Zoomer, and led Grubhub's systems engineering team before deciding the messy gap between data science and operations needed its own discipline. She calls it DecisionOps. In May 2026, FICO acquired Nextmv, vindicating the bet she and co-founder Ryan O'Neil made that optimization deserved the same engineering rigor as software.

carolyn-mooney · nextmvRead →
Legend
Jinlin Wang
Investor · Founder · Operator

Jinlin Wang

Jinlin Wang arrived in the United States in 1996 with $50 in his pocket and a borrowed one-way ticket to pursue a PhD in electrical engineering. Three decades later, he is General Partner at Foothill Ventures, an early-stage fund that has backed seven seed-stage unicorns - five of them founded by Chinese immigrant engineers. Wang's career spans big tech (PeopleSoft, Oracle, Yahoo, Microsoft), startup founding (Auryc, acquired by Heap in 2022), and venture investing through three successive funds totaling over $311M. He holds 7 patents and a cross-disciplinary worldview shaped by Tsinghua University, the University of Connecticut, and Stanford - a combination that informs his conviction that the most interesting startups sit at the edges between fields.

venture-capital · deep-techRead →
Legend
Cameron R. Wolfe
Scientist · Engineer · Creator

Cameron R. Wolfe

Cameron R. Wolfe, Ph.D. is a Senior Research Scientist at Netflix's Globalization team and the author of Deep (Learning) Focus, a twice-weekly Substack newsletter with 60,000+ subscribers that translates cutting-edge ML research into approachable long-form essays. A Rice University computer science PhD, he has built a reputation as one of the clearest explainers of large language models, RLHF, and AI agents in the field, bridging academia and industry with methodical depth and intellectual generosity.

machine-learning · deep-learningRead →