Jason Liang
Evolving neural networks and autonomous agents toward AGI.
Research Scientist & Principal Architect
About Me
I am an AI research scientist at Cognizant AI Lab, based in San Francisco. I received my Ph.D. in Computer Science from The University of Texas at Austin in 2018, advised by Risto Miikkulainen, and my B.S. in EECS from UC Berkeley in 2013.
My research is focused on autonomous agentic systems for System-2 reasoning, inference-time compute scaling, and large-scale neuroevolution as a path toward Artificial General Intelligence. I architected Caesar, an autonomous deep-research agent that uses adversarial self-refinement and a self-organizing knowledge graph for creative answer synthesis. I am the inventor of CoDeepNEAT, an evolutionary neural-architecture-search algorithm that has been cited over 1,500 times.
Share my vision for evolving self-improving agents toward AGI? I'd love to hear from senior researchers who think and act on the next paradigm. Reach me by email.
Interests
- Agentic Reasoning & Inference-Time Compute
- Neuroevolution & Neural Architecture Search
- Multi-Agent & Large Language Models
- Open-Ended Optimization & Meta-Learning
Education
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Ph.D. in Computer Science, 2018The University of Texas at Austin
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B.S. in Electrical Engineering & Computer Science, 2013University of California, Berkeley