Roberts Innovation Fund backs next-generation engineering in bioelectronics, AI, extreme materials

From leaf-thin neural implants designed to treat epilepsy to artificial intelligence systems that act as scientific laboratory collaborators, this year’s Roberts Innovation Fund awards span an extraordinary range of engineering ambition. Drawing faculty from nearly every Yale School of Engineering & Applied Science department, the Fund’s fourth award cycle invests $1 million in accelerator support for 10 inventions advancing technologies that span artificial intelligence, biomedical engineering, sustainable systems, and advanced materials, reflecting the breadth of discovery across Yale Engineering.

Since its launch in 2022, the Roberts Innovation Fund continues to catalyze frontier breakthroughs across Yale Engineering. The 2026 award cycle reflects the School’s commitment to advancing a culture of innovation and cross-disciplinary collaboration that moves research toward real-world applications. This year’s $1 million deployment includes $500,000 from the Roberts Innovation Fund and a matching $500,000 investment from Yale Engineering.

In line with Yale Engineering’s strategic vision, the Roberts Innovation Fund strengthens the School’s entrepreneurial ethos and commitment to high-impact research, accelerating laboratory innovations into solutions for society. Yale Engineering Dean Jeffrey Brock noted that the strength and breadth of proposals in the 2026 cycle underscore both the wide range of technologies the Fund can support and the deep commitment among faculty to translating their research beyond the laboratory.

“Our awardees demonstrate the strength of Yale Engineering’s culture of innovation and collaboration,” said Brock. “Our faculty are pushing discovery at the frontiers of science and technology, and through the Roberts Innovation Fund, we are helping transform those fundamental insights into solutions that address the world’s greatest challenges.”

The Roberts Innovation Fund is one of five accelerator funds managed by Yale Ventures to support faculty technology commercialization with significant potential to benefit a wide-ranging number of fields. In addition to funding, awardees receive world-class support and mentorship with access to industry experts and more than $1.8M in cloud computing credits and other resources from Amazon, Google, and Microsoft as well as an opportunity to present at the annual Yale Innovation Summit.

“What is especially striking about this cohort is the extraordinary range of breakthrough innovations with the potential to transform industry and our world,” said Claudia Reuter, Executive Director, Engineering Innovation & Director of the Roberts Innovation Fund. “From AI-enabled discovery and cutting-edge advances in material science and robotics to biomedical platforms, these projects embody Yale Engineering’s powerful combination of academic ingenuity and real-world ambition. At Yale Ventures, we look forward to partnering with these faculty teams to translate visionary ideas into transformative solutions.”

“
Our faculty are pushing discovery at the frontiers of science and technology, and through the Roberts Innovation Fund, we are helping transform those fundamental insights into solutions that address the world’s greatest challenges.
Jeffrey Brock
Yale Engineering Dean

The Roberts Innovation Fund is open to Yale faculty with a primary or secondary appointment at Yale Engineering who have developed novel innovation that addresses a significant problem with potential for scale. Applicants must demonstrate technical feasibility and a clear plan for the use of awarded funds to advance commercialization milestones.

One of this year’s awardees, Claudia Cea is developing NeuroLeaf, a leaf-thin neuromodulation platform designed to detect and stop seizures before they occur. Currently being tested in animal models, the technology integrates ultra-flexible bioelectronics with real-time neural sensing to intervene at the earliest signs of epileptic activity.

“Our goal is to create a neuromodulation system that is both minimally invasive and intelligent enough to anticipate seizures before they happen,” said Cea, assistant professor of electrical & computer engineering. “Support from the Roberts Innovation Fund allows us to refine the technology in preclinical models while building the translational roadmap needed to move toward human applications. Partnering with Yale Ventures through the Roberts Innovation Fund gives us the commercialization guidance to bring this innovation closer to patients.”

2025-2026 Roberts Innovation Fund Awardees:

Continuous, Ultrahigh Temperature Plasma Synthesis of Extreme Particles

Liangbing Hu, Carol and Douglas Melamed Professor of Electrical & Computer Engineering & Materials Science
Qian Zhang, Postdoctoral Associate

Advanced technologies in aerospace, energy, and electronics increasingly demand materials that maintain performance under extreme conditions. Hu’s technology leverages a scalable ultrahigh-temperature stable plasma (USP) process to introduce a new paradigm for materials synthesis for designing metastable, multielement, and compositionally complex particles across metals, ceramics, and semiconductors.

Design of Intrinsically Porous Polymer-Based Membranes for Crude Oil Refining

Mingjiang Zhong, Associate Professor of Chemical & Environmental Engineering and Chemistry
Jaeman Park, Postdoctoral Associate
Zhongren Jiao, PhD Candidate
Victoria Meola, PhD Candidate

Petroleum refining is one of the most energy- and carbon-intensive industries, consuming over 1,100 terawatt-hours annually. The Zhong lab’s technology aims to reduce carbon emissions and energy consumption with their design of intrinsically porous polymer membranes for petroleum fractionation. Operating under mild, pressure-driven conditions, their membrane platform enables precise and rapid molecular separations of crude oil engineered through polymeric structures, with over 90% energy reduction compared to conventional distillation systems.

Engineering Macrophages for Next-Generation Immune Cell Therapies

Kathryn Miller-Jensen, Professor of Biomedical Engineering and Molecular, Cell and Dev Biology
Hao Yuan Kueh, Associate Professor of Immunobiology and Biomedical Engineering

The Miller-Jensen Lab and Kueh Lab's collaborative technology represents a potential breakthrough in the treatment of chronic degenerative diseases including Alzheimer’s, through enabling advances in engineering macrophage-based therapies. The team is developing a novel genetic screening approach to identify targets to overcome obstacles that currently limit macrophage-based therapies, and will use these targets to optimize macrophage functionality for future disease-specific applications. This project holds the promise of unlocking the potential of macrophages as a next-generation cell therapy.

ExpoSeq: Environmental Sequencing for Personalised Health Insights

Krystal Pollitt, Associate Professor of Epidemiology and Chemical & Environmental Engineering
Jeremy Koelmel, Associate Research Scientist

ExpoSeq addresses a critical gap in precision medicine by providing comprehensive, personalised data on what individuals are exposed to in their daily environments and translating those findings into accessible, personalised health reporting. The Fresh Air wristband passively captures over 1,000 airborne contaminants, including organic chemicals, microplastics, and respiratory pathogens. ExpoSeq integrates these wearable exposomic measures with biological markers to generate a personalised exposure profile, equipping individuals, clinicians, and researchers with the environmental data needed to understand and ultimately reduce environment-related health risks.

Geomancer: An Al scientist for lab-in-loop

Smita Krishnaswamy, Associate Professor of Computer Science and Genetics
João Felipe Rocha, PhD Student

Unlike most current AI scientists operating as data analysis assistants, Geomancer proposes an AI scientist that infers a simulatable model of the underlying system from which it generates hypotheses, designs experiments, and uses feedback to update the model. Geomancer builds on the Krishnaswamy Lab's vast prior work in deep dynamics inference to use multimodal data to automatically learn virtual neural generative models of the data, allowing for live feedback and dynamics inference for pharma applications and research institutions.

Geometric Amplification of Laser Light

Jack Harris, Professor of Physics and Applied Physics
Yogesh Patil, Research Scientist

Geometric Amplification will dramatically improve amplifiers intended to avoid the loss or corruption of data over long distances to support Internet infrastructure. With their invention of a new type of amplifier, the Harris Lab’s Geometric Amplification will advance telecommunication hardware with greater power-efficiency, phase insensitivity, and greater tunability.

GlycoDx: Spatial Glycan Signatures for Early Diagnosis and Therapeutic Stratification

Rong Fan, Harold Hodgkinson Professor of Biomedical Engineering and Pathology
Anthony Fung, Postdoctoral Researcher

GlycoDx is developing the first clinically deployable platform that harnesses the diagnostic power of distinct cell-surface sugar molecules with an AI-empowered spatial Glyco-Code for early disease detection and therapeutic stratification. Unlike genomic or proteomic markers, glyco-codes capture very early disease transitions and therapy-relevant immune and tumor states. This uniquely multiplexed glyco-profiling and AI-driven analytics approach represents a fundamentally new dimension in molecular diagnostics.

NeuroLeaf: A Leaf-Thin Neuromodulation Platform for Epilepsy Treatment

Claudia Cea, Assistant Professor of Electrical & Computer Engineering
Petar Barac, Postdoctoral Researcher
Simone Belli, Postdoctoral Researcher

For the 52 million people living with epilepsy—of which 35% of patients are drug-resistant—NeuroLeaf seeks to leverage cutting-edge flexible bioelectronic technology to detect and treat epilepsy in real-time. Compared to current rigid, battery-powered solutions, the Cea lab solution works to deliver drugs locally via ionic communication and a multimodal interface with goals to further optimize the device’s circuit design and system integration.

SilhouetteDB: Differentially Private Graph Database and Distributed Benchmark

Quanquan Liu, Assistant Professor of Computer Science
Pranay Mundra, PhD Candidate

SilhouetteDB is a fault-tolerant, distributed, and oblivious coordination layer for privacy-preserving algorithms. Built for the next generation of secure distributed systems, this project represents the future of oblivious coordination. This solution will fill a current need in the market for enterprises in finance, healthcare, government, and social platforms which rely on graph analytics, but can’t safely use or share them.

VisualFT: Six-Axis Force-Torque Sensing with a Single Camera

Aaron Dollar, Frederick W. Beinecke Professor of Mechanical Engineering and Computer Science
Vatsal Patel, PhD Candidate

Six-axis force-torque (FT) sensors are commonly used by robots to measure contact forces, but traditional sensors are expensive, fragile, and prone to environmental interference. VisualFT overcomes these limitations by leveraging camera-based sensing and a novel mechanical amplification structure. This approach eliminates the need for complex electronics and high-precision manufacturing, resulting in a robust and affordable sensor.