Researchers from the Gwangju Institute of Science and Technology (GIST), Korea, in collaboration with researchers from the Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory (MIT CSAIL), have developed “EMSWalker,” a new VR locomotion system that provides walking-related bodily sensations while the user remains seated.
RNA vaccines, which have been proven effective against Covid-19, are now being developed for many other diseases, including cancer. One of the drawbacks to these vaccines is that they require ultracold storage, but researchers from MIT have found a promising way to overcome that limitation.
This talk will explore the portfolio construction process at Trexquant and the practical application of deep learning methods in quantitative trading.
Denis will introduce Mixture of Experts (MoE) models and demonstrate their behavior through a toy example using synthetic data. He will then discuss how neural networks are constructed and applied within Trexquant's real-world trading strategies, including aspects of model setup and expert construction that are specific to quantitative trading.
Add to calendarAmerica/New_YorkTrexquant Tech Talk: Applications of Deep Learning Methods in Quantitative Trading 09/30/2926
Join us for a CSAIL Alliances Tech Talk!
This talk will explore the portfolio construction process at Trexquant and the practical application of deep learning methods in quantitative trading.
Denis will introduce Mixture of Experts (MoE) models and demonstrate their behavior through a toy example using synthetic data. He will then discuss how neural networks are constructed and applied within Trexquant's real-world trading strategies, including aspects of model setup and expert construction that are specific to quantitative trading.
The lecture will also cover other deep learning approaches used in quantitative research, including Convolutional Neural Networks (CNNs), Graph Neural Networks (GNNs), and Contrastive Learning, and conclude with examples comparing portfolios constructed using these methods with those based on traditional linear models.
Agentic AI—systems that move beyond generating content to taking autonomous, goal-directed actions in real time—is top of mind in the news, in research, and in business.
MIT CSAIL has a very strong Agentic AI research ecosystem, with PIs exploring last mile AI, security, deployment, cost, physical AI, and so many aspects of the agentic space.
Join us for a day-long summit and be a part of what’s next in artificial intelligence.
Add to calendarAmerica/New_YorkMIT CSAIL Agentic AI Summit11/09/2026
Agentic AI—systems that move beyond generating content to taking autonomous, goal-directed actions in real time—is top of mind in the news, in research, and in business.
MIT CSAIL has a very strong Agentic AI research ecosystem, with PIs exploring last mile AI, security, deployment, cost, physical AI, and so many aspects of the agentic space.
Join us for a day-long summit and be a part of what’s next in artificial intelligence.
Engage directly with MIT CSAIL researchers defining the next generation of AI. What comes next with agents? From research talks, to industry perspective, to small group lunches you’ll leave with a clear view of what Agentic AI can mean for your organization, where the technology is heading, and what questions remain unsolved.
This event is for CSAIL Alliances Members, the MIT Community, and companies interested in connecting with CSAIL research. Space is limited for attendees outside of MIT or CSAIL Alliances; please apply to attend and watch for a follow up email!
Researchers created a new technique that accurately and rapidly matches X-rays captured during surgery with a patient’s preoperative 3D medical scan. This method could make it easier for clinicians to precisely pilot minimally invasive surgical tools, leading to faster and safer procedures.
As a child, you likely saw a few Disney movies depicting inanimate objects, such as clocks, cups, and toys, as interactive companions to humans — an act of pure magic, seemingly. But scientists at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are now doing something similar: transforming stationary items into self-aware tools that perceive and respond to human motion to complete a task.
This event is offered by TNT, and open to the CSAIL Alliances community
TNT, the startup community and accelerator for MIT and Harvard, is hosting Building in Deep Tech, a panel with Silicon Valley Bank, with a mixer after. If you're building something hard, hardware, bio, energy, or AI at the research edge, this room is for you.
“What you see is what you get” is a guiding principle for many software engineers — create programs where the content you’re editing looks the same as the final product. But when you’re using generative AI (genAI) systems to 3D print, say, a mug, you’ll likely get a cup that can’t hold your coffee. Why is that?
