Fatih Dinc
Researcher
Now Member of Technical Staff · Goodfire
@fatihdin4enfatihdinc.github.io ↗GitHub ↗Latest move
UC Santa Barbara → Goodfire · Member of Technical Staff
Theoretical neuroscientist. PhD in applied physics at Stanford, working with Mark Schnitzer on memory using large mouse brain-imaging data, then a postdoc at UC Santa Barbara. Developed the EXTRACT and CORNN tools and studies how biological and artificial networks learn.
Path
GoodfireMember of Technical StaffNEW- UCUC Santa BarbaraPostdoctoral Scholar (with Boris Shraiman and Nina Miolane)2025–2026
Stanford UniversityPhD, Applied Physics2019–2025- PIPerimeter Institute / University of WaterlooMSc, Physics2018–2019
- BUBoğaziçi UniversityBS, Physics and Electrical Engineering2014–2018
- NTNTT ResearchResearcher (with Hidenori Tanaka)
Papers
- CORNN: Convex optimization of recurrent neural networks for rapid inference of neural dynamicsNeurIPS 2023 2023Fits recurrent network models to large recordings of neural activity quickly by recasting the fit as a convex optimization problem.
- A ghost mechanism: An analytical model of abrupt learning in recurrent networksPhysical Review X 2025Builds a mathematical model of why recurrent networks sometimes learn a task suddenly after a long plateau.
- Dynamical phases of short-term memory mechanisms in RNNsICML 2025 2025Maps which mechanisms recurrent networks use to hold information in short-term memory, depending on the task and training settings.
SourcesLatest move: Xfatihdinc.github.ioEducation and jobs are read from their own homepage or employer's page; papers checked on arXiv. From LinkedIn only the person's own public posts are read; GitHub is a link only.