Writing Together Online offers structured time to help you spring into writing and stay focused this semester. We offer writing sessions every workday, Monday through Friday. Join our daily 90-minute writing sessions and become part of a community of scholars who connect online, set realistic goals, and write together in the spirit of accountability and camaraderie. The program is open to all MIT students, postdocs, faculty, staff, and affiliates who are working on papers, proposals, thesis/dissertation chapters, application materials, and other writing projects. For more information and to register, go to this link or check the WCC website. Please spread the word and join with colleagues and friends.Register for Spring 2025 Writing Challenge 1Choose those sessions that you want to attend during Challenge 1: February 10th through March 21stMondays 9:00–10:30amTuesdays 8–9:30am and 9:30–11amWednesdays 9:00–10:30amThursdays 8–9:30am and 9:30–11amFridays 8–9:30am and 9:30–11amMIT Students and postdocs who attend at least 5 sessions per challenge will be entered into a raffle of three $25 Amazon gift cards. The raffle will take place on Friday, March 21st. The more you participate, the more times you will be entered into the raffle of prizes.For more information and to register, check the WCC website. Please spread the word and join with peers and friends.The funding support for this program comes from the Office of Graduate Education

All sessions will take place on Zoom until March 7.On February 28, we’ll have a discussion "Black History Month."On March 7, we’ll be discussing "AI."Meet other MS&PC members from all over the world, get resources and information about life at MIT/Cambridge/Boston, exchange ideas, and engage in cultural conversations in a friendly and casual environment, while working on English fluency.Please email ecgatmit@gmail.com for more information.

🌍 2025 MIT Energy and Climate Career Fair📅 Date: Friday, February 21, 2025, 10:00 AM - 1:00 PM ET📍 Location: Student Center Bldg. W20 - Sala De Puerto Rico (W20-202)Exploring career opportunities in energy, climate, or sustainability? Don’t miss the MIT Energy and Climate Career Fair! Connect with top employers like Schneider Electric, SESCO, GE Vernova, and more, hiring for internships and full-time roles in renewables, energy storage, finance, consulting, R&D, and beyond. Open to all students in the Greater Boston area. Want to get more involved? Volunteer at the fair—enjoy free lunch, support the event, and network directly with leading companies!Register to attend and sign up to volunteer!

Speaker: David Alverez-Melis (Harvard University)Title: Towards a ‘Chemistry of AI’: Unveiling the Structure of Training Data for more Scalable and Robust Machine LearningAbstract: Recent advances in AI have underscored that data, rather than model size, is now the primary bottleneck in large-scale machine learning performance. Yet, despite this shift, systematic methods for dataset curation, augmentation, and optimization remain underdeveloped. In this talk, I will argue for the need for a “Chemistry of AI”—a paradigm that, like the emerging “Physics of AI,” embraces a principles-first, rigorous, empiricist approach but shifts the focus from models to data. This perspective treats datasets as structured, dynamic entities that can be transformed through optimization and seeks to characterize their fundamental properties, composition, and interactions. I will then highlight some of our recent work that takes initial steps toward establishing this framework, including principled methods for dataset synthesis and surprising recent findings in dataset distillation.Biography: David Alvarez-Melis is an Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences, where he leads the Data-Centric Machine Learning (DCML) group. He is also a Researcher at Microsoft Research New England and an Associate Faculty at the Kempner Institute for Natural and Artificial Intelligence. He holds a Ph.D. in Computer Science from MIT and degrees in Mathematics from NYU and ITAM. David’s research seeks to make machine learning more broadly applicable (especially to data-poor applications) and trustworthy (e.g., robust and interpretable) through a data-centric approach that draws on methods from statistics, optimization and applied mathematics, and which takes inspiration from problems arising in the application of machine learning to the natural sciences.

A 50 minute, (usually) student-led tour of MIT D-Lab, D-Lab prototypes, and our workshop! Hear about the 23-year history of D-Lab, our founding director Amy Smith, our 12+ MIT classes, research groups, humanitarian innovation program and more! Not free at tour time? Stop by anytime to look around or email d-lab-tours@mit.edu.

How can we leverage the tools of nanotechnology to address pressing, unresolved research challenges in neuroscience?We are hosting a collaborative workshop series to bring together the worlds of nanotechnology and neuroscience at MIT. We aim for these sessions to foster community and inspire transformative ideas at the intersection of these two fields. Our vision is that these workshops will increase interaction across disciplinary boundaries and lay the scientific and technological groundwork essential for the formation of the Alzheimer’s Hub at MIT.Registration is required. Link to register: https://docs.google.com/forms/d/e/1FAIpQLSemOOffdoLnS4R2dIUD7hb8hTxJO_s-OWWUTdJSzpBP1ncT9g/viewform