Scott W Linderman

Scott W Linderman is an Assistant Professor of Statistics at Stanford University with courtesy appointments in Electrical Engineering and Computer Science. He serves as an Institute Scholar in the Wu Tsai Neurosciences Institute and is affiliated with Stanford Bio-X and the Stanford AI Lab.

• Education:
  • PhD in Computer Science (2016) - Harvard University
  • SM in Computer Science (2013) - Harvard University
  • BS in Electrical and Computer Engineering (2008) - Cornell University
  • 3 years as Microsoft software engineer before graduate school

His research focuses on machine learning and computational neuroscience, developing:

• Advanced state space models (rSLDS, GP-SLDS)
• behavioral time series methods (GIMBAL, Keypoint MoSeq)
• deep state space architectures (S5, ELK)
• point process models (PP-Seq)
• scalable inference algorithms (SIXO, Structure-exploiting VI)

Key collaborations include:

• Prof. David Anderson (Caltech) - hypothalamic dynamics
• Prof. Bob Datta (Harvard Medical School) - behavioral sequencing
• Prof. Chris Ré (Stanford) - biomedical ML
• Prof. David Sussillo (Stanford) - neural network theory

Scientific contributions:

• Developed SSM and Dynamax software packages
• Leonard J. Savage Award recipient (2016)
• Bridging reinforcement learning and neural dynamics
• Advancing 3D keypoint tracking and behavioral syllable analysis

Labs & teams:

• Linderman Lab - computational neuroscience
• Stanford AI Lab - machine learning
• Wu Tsai Neurosciences Institute - interdisciplinary research
• Stanford Bio-X - cross-departmental collaboration