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News
Dec 17, 2025
Eric Fossum Named 2026 Recipient of IEEE Jun-ichi Nishizawa Medal
Dartmouth Engineer Professor Eric R. Fossum, whose innovations have transformed the way the world captures digital images, is the 2026 recipient of the IEEE Jun-ichi Nishizawa Medal, one of the organization’s highest honors.News
Dec 17, 2025 | Dartmouth Development
Dartmouth to Expand Financial Aid for Engineering Undergraduates
Dec 04, 2025
Dartmouth Engineering Professor Appointed as a Lead Author on UN Climate Change Assessment Report
Dec 01, 2025 | Dartmouth Engineer
Modern Alchemy: Transforming small-scale gold mining with community-centered innovations
Nov 26, 2025 | Dartmouth Engineer
Building Bridges: Students in "Solid Mechanics" Test their Designs
In the News
environment coastal & offshore
Nov 19, 2025
Undersea Storms Are Melting Antarctic Glaciers from Below
Features research co-authored by Professor Yoshihiro Nakayama, that describes storm-like ocean circulation patterns beneath Antarctic ice shelves that could cause aggressive melting with major implications for global sea-level rise projections.
The Business of Materials
Nov 17, 2025
High-Entropy Alloys, Additive Manufacturing, and Ice Mechanics
Podcast host Isha Ghiya speaks with Professor lan Baker whose work spans high-entropy alloys, additive manufacturing, and the physics of ice and snow. Baker also shares his motivation for writing materials science books for the general public, including Fifty Materials That Make the World and an upcoming book on how materials shape modern sports.
EdTech
Nov 11, 2025
AI in Computer Science Education: Closing the New Digital Divide in K–12
Professor Rafe Steinhauer is quoted in an article about efforts in K-12 schools to integrate generative AI guidelines and instruction into curricula and policy. "[School] districts are never going to have more power to shape the use of GenAI in their communities than right now, so it's imperative that they act collectively, guided by their core educational values," said Steinhauer.
MIT Sloan School of Management
Nov 03, 2025
AI agents, tech circularity: What’s ahead for platforms in 2026
Professor Geoffrey Parker is one of four experts outlining four emerging trends that show where platforms are heading next. "The code assistance is certainly here," said Parker. "It's valuable, but the tech debt is actually a strategic risk and could be really expensive, especially for incumbent organizations."
Research Quick Takes
Dec 11, 2025
Guide for Generating Spatial Data
PhD student Ruixu (Rachel) Huang is a co-lead author of "Systematic benchmarking of imaging spatial transcriptomics platforms in FFPE tissues" published in Nature Communications. A collaboration between the Goods Lab and the Broad Institute of MIT and Harvard, the study is the first to compare commercial platforms for generating spatial data.
Dec 04, 2025
Better Printed Solar Cells
Postdoc Yanan Li, PhD students Julia Huddy and Masha Klymenko, and Professor Will Scheideler coauthored "Spatial-Uniformity–Driven Bayesian Optimization for Rapid Development of Printed Perovskite Solar Cells" published in Small. (This came out of work recently funded by DOE in Scheideler's SENSE Lab.) "Metal halide perovskites are a promising emerging solar technology, but challenges in reliability and large‑area scalability still hinder widescale adoption. This work uses a machine‑learning–driven Bayesian optimization approach to improve the uniformity of printed perovskite films—addressing a key bottleneck for scaling low‑cost, roll‑to‑roll manufacturing and enabling higher‑efficiency, more reliable solar cells," said Scheideler.
Nov 20, 2025
Toward Optimal Auctions
PhD student Mai Pham, will present her paper, coauthored with professors Vikrant Vaze and Peter Chin, titled "Advancing Differentiable Mechanism Design: Neural architectures for combinatorial auctions" for a workshop at the Conference on Neural Information Processing Systems. Although auctions are considered an effective way of allocating limited resources when demand is high, designing auctions that are simultaneously optimal for the participants, system operator, and greater society is challenging. The paper presents a new approach that leverages modern deep learning architectures and algorithms to meet this challenge.