Brokoslaw Laschowski

Imagine a brain decoding algorithm that could generalize across different subjects and tasks. Today, we’re one step closer to achieving that vision. Introducing the flagship paper of our brain decoding program: www.biorxiv.org/content/10.1... #neuroAI #compneuro @utoronto.ca @uhn.ca

📢 @kempnerinstitute.bsky.social is hiring! We are recruiting for two new faculty roles: Tenure-Track Professor in Computer Science as well as Assistant Professor of Neurobiology. Learn more: bit.ly/4zwJ1tx

Vector Institute is hiring an Applied Machine Learning Scientist in Physical AI. Come join us in Toronto. @vectorinstitute.ai www.linkedin.com/jobs/view/44...

Building thinking machines. Follow @laschowski-lab.bsky.social for updates. 

#NeurIPS2026 decisions are out. Congrats to those accepted. If yours wasn’t, keep going.

This week at 100 College: Thursday, 9.24 | 10:00 - 11:15 am WTI Inspiring Speaker: Tom Griffiths, "Mapping the jagged edges of AI with the tools of cognitive science" 🔗 wti.yale.edu/event/2026-09/inspiring-speaker-tom-griffiths Open to the Yale community. wti.yale.edu/events #KnowTogether

Invited talk at @msftresearch.bsky.social on building computational models of intelligence. Thanks for having me. @laschowski-lab.bsky.social

Faculty position opening in computational neuroscience at Duke University. academicjobsonline.org/ajo/jobs/32697

We are not thinking machines. We are feeling machines that think. — Dr. António Damásio

Interested in a #PhD in machine learning & theoretical neuroscience? Applications for 2027 entry to the Gatsby Unit PhD programme are now open! 💰 Fully-funded 4-year programme 🤝 Close links to @sainsburywellcome.bsky.social ℹ️ www.ucl.ac.uk/life-science...

Proud to lead the UofT summer research program in computer science for students from Ukraine. @utoronto.ca @uoftcompsci.bsky.social @vectorinstitute.ai

Dario Amodei, who co-founded Anthropic, the company behind the Claude chatbot, called for a global slowdown of artificial intelligence development in a 3,800-word essay on Saturday. His appeal for a pause follows months of escalating concerns across the technology industry. nyti.ms/4AatwIK

Our mission: reverse-engineer intelligence. Follow Machine Intelligence Lab for updates. @utoronto.ca @laschowski-lab.bsky.social

Our new study on bidirectional representational alignment between biological and artificial neural networks. @utoronto.ca @laschowski-lab.bsky.social arxiv.org/abs/2608.18244

Are you a #UofT student in computer science, math, physics, or engineering? Want research experience? We’re recruiting students to explore theory and algorithms for inverse reinforcement learning. Email me your resume and transcript.

I started in neuroscience. Then spent several years building intelligent machines. Now I study general principles of learning and intelligence. Follow @laschowski-lab.bsky.social for updates.

#UofT ranked among world’s top 25 universities by ShanghaiRanking Consultancy 🗺️ uoft.me/cB7

UofT is hiring an Assistant Professor in Electrical and Computer Engineering, with a focus on Artificial Intelligence, through the Canada Impact+ Emerging Leaders program. Come join us in Toronto. @utoronto.ca jobs.utoronto.ca/job/Toronto-...

Ontario faculty leading established AI research programs: Vector's Faculty Affiliate open call is live! 📣 ~20 spots for a three-year term, for active faculty at Ontario post-secondary institutions Details and application: na3.hubs.ly/y0zQ4H0

Proud professor. The next-generation of machine learning researchers from Ukraine. @utoronto.ca @laschowski-lab.bsky.social

Applications are open for a junior faculty position in neurocognition @yale.edu. We invite exceptional candidates investigating cognition to apply by October 15, 2026. Learn more: wti.yale.edu/opportunities/faculty-neurocognition Apply: apply.interfolio.com/189343 #KnowTogether #ScienceAtYale

Meet Brandon Wong, an MSc student @uoftcompsci.bsky.social studying representation learning for neural decoding. His current research explores how diffusion latents affect downstream learning.

www.youtube.com/watch?v=UW3j...

Version 2 of Theory of Contravariance w/ @dyamins.bsky.social is out! New material on contravariance for Transformers, and the theory of Representational Similarity Analysis (RSA) and centered kernel analysis (CKA)/Procrustes.

Introducing our framework for interpreting reward functions recovered by inverse reinforcement learning. www.biorxiv.org/content/10.6... @utoronto.ca @laschowski-lab.bsky.social

The Neuroscience Department at UC Berkeley is hiring an Asst Professor in Computational Neuro. All areas of computational/theoretical neuro are welcome. Deadline Oct 30. Join our neuroscience community! aprecruit.berkeley.edu/JPF05446 #AcademicJobs #Neuroscience #NeuroJobs

Applications are now open for the Vector Distinguished Postdoctoral Fellowships. Come join our world-class machine learning research community. Apply by August 31: vectorinstitute.ai/research-tal...

Exclusive: Nvidia is investing in former OpenAI Chief Scientist Ilya Sutskever’s secretive artificial-intelligence lab, part of a long-term partnership that could boost the startup’s access to computing power while helping the chip giant fend off a rival wsj.visitlink.me/UseU5L

Come join us in Toronto. UofT is hiring an Associate Professor/Professor and endowed Hinton Chair in Artificial Intelligence. @utoronto.ca @uoftcompsci.bsky.social jobs.utoronto.ca/job/Toronto-...

Aditya Rajeev presenting his research on valence-driven memory prioritization in machines. @utoronto.ca @uoftcompsci.bsky.social

Brandon Wong presenting his research on diffusion latent representations for brain-machine interface decoding. @utoronto.ca @uoftcompsci.bsky.social

Building computational models of learning, memory, and representation to better understand intelligence in brains and machines. Congratulations to Aditya Rajeev, Brandon Wong, and Samuel Kostousov. @utoronto.ca

Valence-driven memory prioritization in machines by Aditya Rajeev, Sofiya Zbaranska, Sheena Josselyn, and Brokoslaw Laschowski. @utoronto.ca

Bidirectional representational alignment between brains and machines by Samuel Kostousov, Abhin Kaushik, and Brokoslaw Laschowski. @utoronto.ca

Inverse reinforcement learning of multi-agent interactions by Justin Chow, Yunran Yang, and Brokoslaw Laschowski. @utoronto.ca

Diffusion latent representations for brain-machine interface decoding by Brandon Wong and Brokoslaw Laschowski. @utoronto.ca

@utoronto.ca has announced a new, multi-year partnership with @cohere.com, which was founded in 2019 by former U of T computer science students and has become the world's leading sovereign AI company. www.utoronto.ca/news/u-t-par...

New paper: We introduce a framework for studying how intermediate representation choice affects downstream learning and reconstruction, with an initial demonstration in neural speech decoding using diffusion latents. www.biorxiv.org/content/10.6... @compneurolab.bsky.social @utoronto.ca

A brain-inspired framework for memory prioritization in neural networks based on valence https://www.biorxiv.org/content/10.64898/2026.05.05.723022v1

Interpreting Rewards from Inverse Reinforcement Learning https://www.biorxiv.org/content/10.64898/2026.07.08.736783v1

Diffusion Latent Representations for Neural Decoding https://www.biorxiv.org/content/10.64898/2026.07.08.737343v1

1/6 Why have deep neural networks aligned so strongly with brains for the past 15 years? What explains it? @dyamins.bsky.social & I make progress on this question in our new paper👇 In a nutshell, we *prove* that for sufficiently hard tasks, the choice of alignment metric does *not* matter.

Congrats to the 2026 test of time award winners! #icml2026

📢 Just announced! Join us for the #KempnerInstitute workshop “Learning Dynamics in Natural and Artificial Intelligence: Evolution, Adaptation, and the Foundations of Efficient Learning.” Learn more, register, or submit an abstract 👉 bit.ly/3QwJlHR

#UofT ranked first in Canada, 20th globally in latest U.S. News & World Report university rankings 🌎 uoft.me/cv3

🧠 Imagine being able to control machines by thinking. @drlaschowski.bsky.social (MIE) and his Computational Neuroscience Lab are working to make it possible. They've developed a new algorithm that could make brain decoding more accurate and efficient. Read the story: uofteng.ca/25h7c8

We've updated the preprint of our Naturalistic Computational Cognitive Science paper (arxiv.org/abs/2502.20349) — we've tried to clarify and streamline the arguments, and added some new examples: 1/5

www.amacad.org/publication/... my new article in the American academy of arts and sciences journal Daedalus. Part of a special issue in AI+Science lead by James Manyika.

This week, #FlatironCCN hosted a three-day workshop that brought together researchers in theoretical #neuroscience and control theory to foster collaboration. #science

Thanks to Tatiana Engel (@engeltatiana.bsky.social) from @princeton.edu for a great talk on Friday! She presented modeling approaches that leverage low-dimensional structure in neural population activity to design effective stimulation patterns. Watch the talk ➡️ youtu.be/rYvZoshNUVk

Blake Richards now : Why Artificial Intelligence needs literal synapses. - how modern AI and neuroscience research converge today