Speakers

Below are speakers in alphabetical order. Click a title to jump to the talk in the Schedule.

Jonathan D. Cohen

Princeton Neuroscience Institute

Short bio here.

https://example.org

• Constructing and Fitting Computational Models of Mind and Brain With PsyNeuLink (Talk, 17:00–17:30)

---

Nathaniel Kutz

University of Washington

Nathan Kutz is the Boeing Professor of AI and Data-Driven Engineering in the Department of Applied Mathematics and Electrical and Computer Engineering and Director of the AI Institute in Dynamic Systems at the University of Washington, having served as chair of applied mathematics from 2007-2015. He received the BS degree in physics and mathematics from the University of Washington in 1990 and the Phd in applied mathematics from Northwestern University in 1994. He was a postdoc in the applied and computational mathematics program at Princeton University before taking his faculty position. He has a wide range of interests, including neuroscience to fluid dynamics where he integrates machine learning with dynamical systems and control.

https://example.org

---

Sebastian Musslick

Princeton University

Short 2–3 sentence bio here.

https://example.org

• Introduction to Automated Scientific Discovery (Talk, 17:00–19:00)

---

Akshay Kumar Jagadish

AK

• Generating computational cognitive models using LLMs (Talk, 17:00–17:30)
• Computational Cognitive Models using LLMs (Tutorial, 20:00–21:00)

---

Daniel Weinhardt

DW

• Sparse Identification of Cognitive Equations (Talk, 18:30–19:00)
• Cognitive Model Discovery with SPICE (Tutorial, 20:00–21:00)

---

Kevin Miller

KM

• Cognitive model discovery via disentangled RNNs (Talk, 17:00–17:30)
• Discovering symbolic cognitive models from behavior (Talk, 16:30–17:00)

---

Kyle LaFollette

KL

• Equation Discovery in Reinforcement Learning (Talk, 18:00–18:30)

---

Lukas Stelz

LS

• Dynamical System Discovery with SINDy (Tutorial, 20:00–21:00)

---

Marcel Binz

MB

• Centaur: A foundation Model of Cognition (Talk, 18:30–19:00)

---

Marcello Mattar

MM

• Knowledge Distillation with Tiny-RNNs (Talk, 16:30–17:00)

---

Marina Dubova

MD

• Against theory-motivated experimentation in science (Talk, 16:30–17:00)

---

Martyna Plomecka

MP

• LLMs for Automated Datascience (Talk, 18:30–19:00)

---

Matthew Flatt

MF

• Automated Experimental Design With SweetPea (Talk, 16:30–17:00)

---

Milena Rmus

MR

• Generating computational cognitive models using LLMs (Talk, 17:00–17:30)
• Computational Cognitive Models using LLMs (Tutorial, 20:00–21:00)

---

Muhip Teczan

MT

• Cognitive Model Discovery with SPICE (Tutorial, 20:00–21:00)

---

Nathan Kutz

NK

• Sparse Identification of Non-Linear Dynamics (Talk, 17:00–19:00)

---

Nathaniel Daw

ND

• To be announced (Talk, 16:30–17:00)

---

Peter Clark

PC

• Multi-Agent LLMs for Scientific Discovery (Talk, 16:30–18:00)

---

Se-Eun Choi

SC

• Dynamical System Discovery with SINDy (Tutorial, 20:00–21:00)

---

Tom Griffiths

TG

• Integrative Experimental Design (Talk, 18:00–19:00)

---

Victoria Bosch

VB

• CorText: From visually evoked brain responses to text captions (Talk, 18:00–18:30)

---

Younes Strittmatter

YS

• Introduction to AutoRA (Tutorial, 20:00–21:00)
• PsyNeuLink (Tutorial, 18:00–19:00)
• Integrating PsyNeuLink with AutoRA (Tutorial, 20:00–21:00)
• SweetPea (Tutorial, 17:00–17:30)
• SweetBean (Tutorial, 18:00–19:00)
• Integrating Web-Based Experiments with AutoRA (Tutorial, 20:00–21:00)
• Automated Experiment Sampling (Talk, 17:00–17:30)
• Closing the Loop: Integrating Samplers (Tutorial, 20:00–21:00)
• LLMs as Synthetic Participants (Tutorial, 20:00–21:00)

---