Slides

• De-supervising neural network models of the primate ventral stream. 2022-09-12, Kornfeld lab MPI
  [pdf]
• Artificial Neural Networks Converge to Brain-Like Processing in Vision and Language. 2022-04-06, Erlangen AI & ML meetup
  [pdf]
• The neural architecture of language: Integrative modeling converges on predictive processing. 2022-04-04, DNA Deviants Journal Club
  [Clubhouse recording]
• The future of Brain-Score. 2022-03-22, Cosyne 2022 Brain-Score workshop
  [pdf]
• The neural architecture of language: Integrative modeling converges on predictive processing. 2022-03-14, Boston College Hartshorne and Prud’hommeaux labs
  [pdf]
• BCS interviews. 2022-03-11, MIT
  [pdf]
• Thesis Defense. 2022-01-31, MIT BCS
  [recording (passcode: [email protected]!), pdf]
• Topographic ANNs Predict the Behavioral Effects of Causal Perturbations in Primate Visual Ventral Stream IT. 2021-10-15, Champalimaund Research Symposium (CRS21)
  [poster pdf]
• Deep Topographic Models Predict the Behavioral Effects of Neural Perturbations in  Primate Visual Cortex. 2021-10-05, C-BRIC
  [pdf]
• Topographic Neural Networks Predict the Behavioral Effects of Causal Perturbations in Primate IT Cortex. 2021-09-16, MIT Fiete Lab
  [pdf]
• Deep Spatial Models Predict the Behavioral Effects of Pharmacological Perturbations in Primate Visual Cortex. 2021-08-23, Takeda Fellowship Event
  [poster pdf]
• Topographic Neural Networks Predict the Behavioral Effects of Causal Perturbations in Primate IT Cortex. 2021-08-19, CBMM retreat
  [pdf]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2021-07-05, Telluride Workshop
  [pdf, video]
• Integrative Neurally-Mechanistic Models of Primate Visual Object Recognition. 2021-06-03, MIT Yang Lab
  [pdf]
• The neural architecture of language: Integrative modeling converges on predictive processing. 2021-05-20, Stanford NLP
  [pdf]
• The neural architecture of language: Integrative modeling converges on predictive processing. 2021-03-09, MIT BCS Saxe Lab
  [pdf]
• Engineering an Artificial Biological Intelligence. Guest Lecture, Program for Software Engineering. 2021-01-15, UNA/TUM, LMU
  [pdf]
• CBMM Panel Discussion: Should models of cortex be falsifiable? 2020-12-07, MIT (with Tomaso Poggio, Gabriel Kreiman, Josh McDermott, Leyla Isik, Susan Epstein, Jenelle Feather)
  [video]
• The neural architecture of language: Integrative modeling converges on predictive processing. 2020-12-01, France NLP GDR TAL
  [pdf]
• Integrative Benchmarking to Advance Neural Models of Vision and Language. 2020-11-25, Virtual Computational Neuroscience Journal Club
  [pdf, recording]
• Integrative Benchmarking and the Value of Quantitative Models. 2020-10-19, CCN GAC linear/nonlinear workshop
  [pdf]
• Wiring Up Vision: Minimizing Supervised Synaptic Updates Needed to Produce a Primate Ventral Stream. 2020-10-06, C-BRIC Annual Review
  [pdf]
• Artificial Neural Networks Accurately Predict Language Processing in the Brain. 2020-08-18, MIT BCS Cog Lunch
  [pdf, code]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2020-03-31, neuromatch.io contributed talk
  [pdf, video (starts at 22:45)]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2019-12-12, NeurIPS Oral
  [talk recording, slides pdf, slides powerpoint, poster pdf, code, 3min-video]
• Brain-Like Object Recognition with High-Performing Shallow Recurrent ANNs. 2019-10-29, MIT BCS Cog Lunch
  [pdf]
• Deep Networks and Pytorch. 2019-08-21, Harvard-MIT Computational Neuroscience Journal Club
  [notebook, github]
• Continual Learning with Self-Organizing Maps. 2018-12-07, NeurIPS Continual Learning Workshop
  [poster pdf]
• Aligning Deep Neural Networks and Visual Cortex. 2018-03-01, MIT IQ Launch
  [pdf, powerpoint]
• A Flexible Approach to Automated RNN Architecture Generation. 2018-02-14, Tenenbaum lab
  [pdf, powerpoint]
• Introduction to Deep Learning for Neuroscientists. 2017-10-27, MIT BCS Peer Lectures
  [powerpoint, pdf]
• Recurrent computations for pattern completion. 2016-20-10, Harvard Systems Club
  [pdf]