Mingbo Cai 蔡明博

338 posts

Mingbo Cai 蔡明博

Mingbo Cai 蔡明博

@mingbocai

Assistant Professor, Department of Psychology, University of Miami Contact me for postdoc/PhD inquiry. Opinions here do not reflect my employer.

Katılım Haziran 2009
745 Takip Edilen657 Takipçiler
Mingbo Cai 蔡明博
Mingbo Cai 蔡明博@mingbocai·
I probably turned on autopilot in my outlook several months ago. Today I finally realized that all it does is popping out a big panel asking if I like its reply (which I never see) and I have spent all these months just closing it because it immediately blocks the words I was typing. Did I miss anything? How do people use this feature?
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Jingnan Du
Jingnan Du@jingnandu049·
I am thrilled to share that I’ll be joining the University of Notre Dame (@NotreDame) as an Assistant Professor of Psychology this July!☘️🧠 Please reach out if you're interested in joining my lab! More details to follow soon.
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Xiang Li | 李想
Xiang Li | 李想@XiangHCI·
I’m very happy to share that I will be joining @HKUniversity as an Assistant Professor in the Department of Data and Systems Engineering, starting in October 2026. 🥰 1/4
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Adrienne Fairhall
Adrienne Fairhall@alfairhall·
Last chance to comment on the proposal to limit student visas to 4 years, making it impossible for foreign students to complete a PhD program in the US—at great loss to our research enterprise, which attracts brilliant youth from across the world: federalregister.gov/documents/2025…
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Bonan Zhao / 赵博囡
Bonan Zhao / 赵博囡@BonanZhao·
My Lab at the University of Edinburgh🇬🇧 has funded PhD positions for this cycle! We study the computational principles of how people learn, reason, and communicate. It's a new lab, and you will be playing a big role in shaping its culture and foundations. Spread the words!
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Mingbo Cai 蔡明博
Mingbo Cai 蔡明博@mingbocai·
Welcome to contribute your article to this research topic!
Frontiers - Neuroscience@FrontNeurosci

New Research Topic "Neuro-Inspired Computation 2025", supporting the Neuro-Inspired Computation Course @ the University of Tokyo (July 2–5, 2025) 🧠Led by Prof Takao Hensch & @mingbocai 🔎Scope&confirm: fro.ntiers.in/RT72364 Focus on the intersection of biological and artificial intelligence 💡in FrontiersIn #NeuralCircuits Critical topics: • Network architectures • Intrinsic dynamics • Plasticity & criticality • Neuromodulation • Reinforcement & multi-agent learning

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Amishi Jha
Amishi Jha@amishijha·
Heading to the 🧠 the Cognitive Neuroscience Society 🧠 meeting in Boston? Come check out @CogNeuroUMiami Jha Lab’s posters! A43 (presented by Brooke Schwartzmanan), A144 (by Jason Tsukahara), B158 (presented by Jha Lab alum @anthonyzanesco— Asst. Prof at Univ of Kentucky)
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Darshan 🦖
Darshan 🦖@darshan·
Oppenheimer lied to you. He wasn't the hero who saved the Manhattan Project. When his reactor was failing, he needed a Chinese woman to prevent nuclear disaster––that he later erased from history. Here's the true story of physics' greatest cover-up:
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Richard Sutton
Richard Sutton@RichardSSutton·
The original RL algorithms, inspired by natural learning, were online and incremental—they were streaming in the sense that they learned from each increment of experience as it happened, then discarded it, never to be processed again. The streaming algorithms were simple and elegant, but the first big successes of RL in deep learning were not with streaming algorithms. Instead, methods such as DQN chopped the stream of experience into individual transitions, then stored and sampled them in arbitrary batches. Subsequent work followed, extended, and refined the batch approach into asynchronous and offline RL, while the streaming approach languished, unable to produce good results in popular deep learning domains. Until now. Now researchers at the University of Alberta have shown that streaming RL algorithms can work just as well as DQN on Atari and Mujoco tasks (arxiv.org/pdf/2410.14606). How did they do it? Mostly just by getting signal normalization and step-size bounding right for the streaming case—otherwise they use standard streaming algorithms like TD(lambda) and Q(lambda). To me it looks like they were simply the first researchers knowledgeable of streaming RL algorithms to seriously address deep RL without being over-influenced by batch-oriented software and batch-oriented supervised-learning ways of thinking.
Mohamed Elsayed@mhmd_elsaye

Would you believe that deep RL can work without replay buffers, target networks, or batch updates? Our recent work gets deep RL agents to learn from a continuous stream of data one sample at a time without storing any sample. Joint work with @Gautham529 and @rupammahmood.

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Mingbo Cai 蔡明博
Mingbo Cai 蔡明博@mingbocai·
Super happy to share this work led by the amazing @FakeWeiChen ! The first developmental work from my lab. It was a fun experience to have conducted this study at @miraikan, one of the coolest science museums in Japan, while I was at @IRCN_UTokyo !
Wei Chen@FakeWeiChen

🧠 Happy to share our preprint: “The developmental trajectories of generalization and discrimination in reinforcement learning reflect multiple underlying cognitive processes” 👉 osf.io/preprints/psya… [1/N]🧵

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Lucy Lai, PhD
Lucy Lai, PhD@drlucylai·
uploaded later than i hoped, but here's my step-by-step video guide on ✨HOW TO WRITE A STATEMENT OF PURPOSE!✨ in it, i analyze my very own SoP that got me into Harvard + other top schools 😍 please share widely! #phdchat #admissions youtube.com/watch?v=fQP1rX…
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UMiami-Psychology
UMiami-Psychology@UMiamiPsych·
We are accepting applications for a full-time, tenure-eligible, or tenure-track faculty member to join our department in August '25. The opening is part of a College of A&S cluster hire dedicated to artificial intelligence (machine learning). Details: psy.miami.edu/about-the-depa…
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daniel messinger
daniel messinger@danielmessinger·
Lynn Perry & Ivette Cejas with an experiment in nature showing that the types of words a child knows shape their subsequent language development, especially for cochlear implant users, perhaps because shape based nouns (eg cup) guided their word learning. onlinelibrary.wiley.com/doi/10.1111/de…
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