Charles Elkan
Also known as Charles Peter Elkan, Charles P. Elkan
Charles Elkan is a computer scientist whose AI work spans automated reasoning, machine learning, computational biology and finance. He earned a mathematics degree at Cambridge and a computer science PhD at Cornell, then joined UC San Diego in 1990 and co-founded its Artificial Intelligence Laboratory. His career included the 1996 ParaMEME motif-discovery interface, a 2001 paper on cost-sensitive classification, and machine-learning leadership at Amazon and Goldman Sachs. As of October 2026, he is chief scientist at Poesis, an affiliate professor at UC San Diego and an investing partner at Rohati Capital.
Timeline
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1990
Cornell PhD and UCSD faculty
He earns a mathematics degree at Cambridge and a computer science PhD at Cornell in 1990. While at Cornell, he studies as a visiting PhD student at Stanford advised by John McCarthy and works as a postdoctoral fellow at the University of Toronto before joining UC San Diego's computer science faculty in 1990. At UCSD, he co-founds the Artificial Intelligence Laboratory and develops algorithms for reasoning about database queries and updates, as well as a web engine for comparing protein and DNA sequences.
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1996–1999
ParaMEME and a Harvard visit
In 1996, he coauthors ParaMEME, a parallel implementation and web interface for DNA and protein motif discovery. In 1998–1999, he is a visiting associate professor of computer science at Harvard.
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2000
First place at CoIL Challenge
In 2000, he takes first place in the CoIL Challenge data-mining competition.
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2001
Cost-sensitive classification
In 2001, he publishes The Foundations of Cost-Sensitive Learning, which examines classification decisions when different misclassification errors carry different penalties.
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2014–2018
Amazon machine-learning team
From 2014 to 2018, he is Amazon's first Fellow and builds and leads its central machine-learning team in Seattle, Palo Alto and New York.
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2018–2020
Machine learning at Goldman Sachs
From 2018 to 2020, he serves as managing director and global head of machine learning at Goldman Sachs in New York.
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2021–2024
Co-founding ficc.ai
By 2021, he is a co-founder of ficc.ai, which uses machine learning to price municipal bonds in real time. In 2024, he is the company's CEO.
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As of October 2026
Chief scientist at Poesis
As of October 2026, he is chief scientist at Poesis and an affiliate professor of computer science at UC San Diego. He is also an investing partner at Rohati Capital.
Career
- Since 1990University of California, San DiegoComputer science faculty, Co-founder
- NowPoesisChief scientist
- NowRohati CapitalInvesting partner
- From 2021ficc.aiCo-founder, CEO
- 2018–2020Goldman SachsManaging director and global head of machine learning
- 2014–2018AmazonFellow
- 1998–1999Harvard UniversityVisiting associate professor of computer science
- 1990University of TorontoPostdoctoral fellow
- Stanford UniversityVisiting Ph.D. student
Education
- 1990Cornell UniversityComputer science PhD
- University of CambridgeMathematics degree
Sources and credits
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- Charles Elkan | Jacobs School of Engineering
- Charles Elkan
- Noble Research Lab: Publications and software
- The Foundations of Cost-Sensitive Learning | ML Anthology
- The AI World Model for Finance
- Events Archive - NYU Stern
- Ficc.ai - IVC Data & Insights
- Gen AI Summit 2024
- Rohati Capital Closes $50M Inaugural Fund
- Council of Advisors | Jacobs School of Engineering





