Janet Echelman's Remembering the Future widens our perspective in time, giving sculptural form to the history of the Earth's climate from the last ice age to the present moment, and then branching out to visualize multiple potential futures.Constructed from colored twines and ropes that are braided, knotted and hand-spliced to create a three-dimensional form, the immersive artwork greets you with its grand scale presiding over the MIT Museum lobby.This large-scale installation by 2022-2024 MIT Distinguished Visiting Artist Janet Echelman, was developed during her residency at the MIT Center for Art, Science & Technology (CAST). Architect, engineer and MIT Associate Professor Caitlin Mueller collaborated on the development of the piece.The title, Remembering the Future was inspired by the writings commonly attributed to Søren Kierkegaard: "The most painful state of being is remembering the future, particularly the one you'll never have."As the culmination of three years of dedicated research and collaboration, this site-specific installation explores Earth's climate timeline, translating historical records and possible futures into sculptural form.Echelman's climate research for this project was guided by Professor Raffaele Ferrari and the MIT Lorenz Center, creators of En-ROADS simulator which uses current climate data and modeling to visualize the impact of environmental policies and actions on energy systems.Learn more about Janet Echelman and the MIT Museum x CAST Collaboration.Learn more about the exhibition at the MIT Museum.

On view October 1 -- December 11, 2025This exhibition draws on archival materials from the Aga Khan Documentation Center at MIT (AKDC) to explore a century of cultural heritage preservation in Aleppo, Syria. It takes as its point of departure the work of Kamil al-Ghazzi (1853–1933), the pioneering Aleppine historian whose influential three-volume chronicle, Nahr al-Dhahab fī Tārīkh Ḥalab (The River of Gold in the History of Aleppo), was published between 1924 and 1926.Ink, Stone, and Silver Light presents three modes of documentation—manuscript, built form, and photography—through which Aleppo’s urban memory has been recorded and preserved. Featuring figures such as Michel Écochard and Yasser Tabbaa alongside al-Ghazzi, the exhibition traces overlapping efforts to capture the spirit of a city shaped by commerce, craft, and coexistence. At a time when Syria again confronts upheaval and displacement, these archival fragments offer models for preserving the past while envisioning futures rooted in dignity, knowledge, and place.

AbstractWhat happens when we put the human mind at the center of human-computer interaction?This talk by Dr. Nataliya Kosmyna presents over a decade of interdisciplinary research on noninvasive, wearable brain–computer interfaces (BCIs) that enable new modalities of interaction. By leveraging biophysical sensors, these systems capture spatial and temporal data that reflect patterns of human behavior, cognition, and intent. When integrated with machine learning, this multimodal data opens new pathways for adaptive, brain-aware technologies.From robotics to space exploration, from health care and education to automotive systems and entertainment, this talk demonstrates how modeling the mind via physiological signals can lead to more intuitive, responsive, and personalized systems. It also discusses the challenges of working with brain-derived data in real-world settings and outlines future directions for BCI-driven human-computer interaction.BiographyDr. Kosmyna is a research scientist at MIT Media Lab’s Fluid Interfaces group and a visiting faculty researcher at Google. She has over 15 years of experience developing and designing end-to-end BCIs. Coming from a background in artificial intelligence (AI), neuroscience, and human-computer interaction (HCI), she is passionate about the idea of creating a partnership between AI and human intelligence, a fusion of the machine with the human brain.Kosmyna obtained her PhD in 2015 from the Université Grenoble Alpes, France. Most of her projects are focused around BCIs in the context of consumer grade applications. With the Fluid Interfaces group, she works on designing and testing novel hardware solutions and paradigms for different applications and users. She is also a public speaker, author of multiple research papers, and reviewer of numerous professional journals and conferences. She has served on UNICEF’s Expert Advisory Group on Neurotechnology and Children and as one of 24 international experts preparing a first draft recommendation on the ethics of neurotechnology for UNESCO.Throughout her career Kosmyna has won multiple honors, including a L’Oréal-UNESCO Women in Science award in 2016 and recognition as a top-ten French talent on the 2017 MIT Innovators Under 35 list. Her work has been covered in news outlets around the world, including the New York Times, the New Yorker, CNN, the Washington Post, Time, Nature, CBS News, the Telegraph, the Wall Street Journal, Fast Company, the Boston Globe, the Economist, MIT Tech Review, and more.

Location: 46-3310Zoom: https://mit.zoom.us/j/92495348437Speaker: Tamar RegevAffiliation: Fedorenko lab​​​​​​​Title: Characterizing the relationship between language and prosody using neural and computational approachesAbstract: Although much past work on human communication has focused on the verbal component of language, communication also relies on a variety of non-verbal cues, including visual cues, such as facial expressions and gestures, and auditory cues, such as non-verbal vocalizations and prosody. In the recent surge of interest in multimodal communication, these different cues have often been discussed on par with one another. However, I will here argue and provide empirical evidence that prosody occupies a privileged position among non-verbal communication signals, showing a uniquely tight relationship with language processing. First, I will present an fMRI investigation of brain areas that process prosody, revealing that prosody brain areas are similar in topography to, and show partial overlap with, language brain areas. This overlap is in sharp contrast to past work that has established that facial expressions, gestures, and non-verbal vocalizations are supported by brain areas distinct from the language areas. Second, I will describe a set of computational studies using information theory and large language models to quantify the overlap between prosodic and linguistic information in natural spoken language. The findings suggest that prosodic information is largely redundant with linguistic content. The overlap between prosodic and linguistic processing in the brain and in the information they carry suggests that prosodic and linguistic representations are tightly coupled within the cognitive architecture of human communication. I will speculate on why this might be, including the distributional properties of prosody vs. other cues during communication, the role of prosody in linguistic prediction, and the scaffolding that prosody may provide during early language learning.

Please join us for the CSAIL Forum with Alison GopnikCSAIL Forum hosted by Daniela Rus Title: Empowerment Gain as Causal Learning, Causal Learning as Empowerment Gain: A bridge between Bayesian causal hypothesis testing and reinforcement learning Speaker: Alison Gopnik Dept. of Psychology, UC Berkeley Date/time: Tuesday 12:00-1:00 EDT, November 4, 2025 Venue: Live stream via Zoom: Registration required Bio: https://psychology.berkeley.edu/people/alison-gopnik Abstract: Learning about the causal structure of the world is a fundamental problem for human cognition, and causal knowledge is central to both intuitive and scientific world models. However, causal models and especially causal learning have proved to be difficult for standard Large Models using standard techniques of deep learning. In contrast, cognitive scientists have applied advances in our formal understanding of causation in computer science, particularly within the Causal Bayes Net formalism, to understand human causal learning. These approaches also face challenges when it comes to learning however. In parallel, in the very different tradition of reinforcement learning, researchers have developed the idea of an intrinsic reward signal called “empowerment”. An agent is rewarded for maximizing the mutual information between its actions and their outcomes, regardless of the external reward value of those outcomes. In other words, the agent is rewarded if variation in an action systematically leads to parallel variation in an outcome so that variation in the action predicts variation in the outcome. Empowerment, then has two dimensions , it involves both controllability and variability. The result is an agent that has maximal control over the maximal part of its environment. “Empowerment” may be an important bridge between classical Bayesian causal learning and reinforcement learning and may help to characterize causal learning in humans and enable it in machines. If an agent learns an accurate causal model of the world they will necessarily increase their empowerment, and, vice versa, increasing empowerment will lead to a more accurate (if implicit) causal model of the world. Empowerment may also explain distinctive empirical features of children’s causal learning, as well as providing a more tractable computational account of how that learning is possible.

Speakers: Robin Pemantle (University of Pennsylvania)Title: Course development and active learning: a retrospective spanning nine coursesAbstract: The long term success of a new course depends on a lot of factors: personnel to teach the course, student incentives to take the course and learning goals (careful, different interested parties are likely to see these differently).I will tell some stories of course development spanning courses for pre-service teachers, calculus courses, and graduate level applied mathematics. Questions that will arise include whether to tweak an existing course versus re-invent from scratch and what pedagogies to build into the course. For clarity on the issue of pedagogy, one needs a solid understanding of the factors above, particularly the learning goals.Zoom link: https://cornell.zoom.us/j/92415199317Zoom Link Password: olsumeFor more information on OLSUME: https://olsume.org/