Recent External Grants
Deshwal wins NSF CAREER Award: Aryan Deshwal, Assistant Professor in Computer Science and Engineering, is the recipient of a CAREER Award from the National Science Foundation titled “CAREER: Adaptive Experimental Design to Accelerate Scientific Discovery and Engineering Design.” This 5-year award starts July 1, 2026, and will provide Prof. Deshwal with $599,550 in research funding. The project seeks to transform how experiments are selected to accelerate engineering design and scientific discovery. Discovering new materials, safer chemicals, and better manufacturing processes often depends on running costly experiments in real-world laboratories. In many areas of science and engineering, researchers must choose from many possibilities, and testing each experimental design is resource-intensive. The project will develop novel artificial intelligence (AI) methods to help engineers and scientists adaptively decide which experiments to run next, so promising discoveries can be found with far fewer trials than traditional trial-and-error methods. The project will also strengthen the future AI workforce by training undergraduate and graduate students through new courses and research opportunities, create open-source tools, and benchmark problems to advance AI and scientific discovery.
Humann Receives NSF Award for Powered Prosthetic Legs Research: Rachel Gehlhar Humann, Assistant Professor in Mechanical Engineering, has received a research grant from the National Science Foundation titled “Encoding Biological Step Placement Swing Control Strategies in Powered Prosthetic Legs.” Her collaborators (senior personnel) include Dr. Stephen J. Guy, Associate Professor of Computer Science and Engineering, and Dr. Sara Koehler-McNicholas from the Minneapolis Veterans Affairs Administration. Adjusting step length is a central strategy humans use to maintain balance and change walking speeds in daily life. However, current robotic prosthetic legs do not consider step placement. Prosthetic users experience reduced gait stability and an increased risk of falls compared to able-bodied individuals. This NSF project aims to address these limitations by developing control methods for robotic prostheses that can intelligently adjust step length in response to the user’s motion to maintain balance. Enabling prostheses to adapt to an individual’s real-time motion and mimic human step placement behavior would improve stability and safety. This work aims to improve prosthetic options for veterans and other Americans living with limb loss. By partnering with the Minneapolis Veterans Affairs Health Care System, this research will facilitate engagement with veterans with amputation, reducing the gap between technology development and the population it is intended to serve. This project will also enhance engineering education by providing hands-on research opportunities for students and facilitating interdisciplinary learning in controls, robotics, and biomechanics. The project's research objective is to encode human step-placement strategies into the swing-control formulation of multi-joint lower-limb powered prostheses. Traditional human step placement models require full-body state information, such as center of mass, which standard sensors cannot directly measure. To overcome this limitation, this research, in collaboration with Dr. Stephen J. Guy, will develop a center-of-mass estimation method based entirely on onboard prosthesis sensing. Additionally, this project will develop user-specific, data-driven step-placement predictors that provide goals for a task-space prosthesis controller. This framework will first be validated in forward-dynamic simulations and then experimentally evaluated through human-subject testing with individuals with lower-limb amputation. This project is expected to restore the link between human motion and prosthesis step placement, providing a unified prosthesis control framework for a range of walking speeds, speed transitions, and perturbations. The project has a budget of $504,342 and a duration of 3 years (10/2026-09/2029).
Chen Wins NSF CAREER Award: Zhu-Tian Chen, Assistant Professor in Computer Science and Engineering, is a recipient of a CAREER Award from the National Science Foundation titled “CAREER: Situated Visual Augmentation for Human-AI Complementarity in Physical Spaces.” This 5-year award starts June 15, 2026, and will provide Prof. Chen with $682,882 in research funding. This project will develop adaptive augmented reality (AR) interfaces that help people engage with artificial intelligence (AI) more deliberately in real time while avoiding unnecessary disruption to physical tasks. AI is becoming a powerful decision-making tool, but most AI systems still deliver advice on desktop screens. This is a poor fit for people working in physical environments, such as surgeons, facility teams, first responders, and coaches. AR can place AI guidance directly into these settings, but simply moving information off a screen is not enough. In these settings, people must divide attention among the environment, movement, and the task itself, which can lead them to accept or reject AI advice too readily. By improving how people and AI work together in real-world context, the project will support safer, more accurate, and more accountable decision-making in settings where errors are costly. The project will also train students in spatial computing, create open tools and learning materials, and broaden participation through courses, tutorials, and workshops.
Kodandaramiah Receives Multiple NIH Grants: Suhasa Kodandaramiah, Associate Professor in Mechanical Engineering, is Co-I on NIH grant 1R24OD039899-01 along with John Bichof (contact PI), titled “Cryopreserved Zebrafish Embryos as a Resource: Dissemination for Global Research Impact.” This $2,650,000 grant will develop new approaches for cryopreserving Zebrafish embryos. The project is a collaboration with the Zebrafish International Resource Center (ZIRC) at UT Austin. Dr. Kodandaramiah’s lab will help develop automated technologies for robust cryopreservation of zebrafish embryos. The startup company Objective Biotechnology, launched by members of Prof. Kodandaramiah’s research lab, has received a $3.1 million Phase II SBIR grant to commercialize computer vision-guided automated microinjection systems. Although this is not a university grant, the university owns the underlying technology and has licensed it to Objective Biotechnology. The new funding will enable the startup to develop its next-generation automated microinjection robotic platform, expanding the diverse biological species and research models it can target.
Rajamani Co-Leads New NCHRP Project: Rajesh Rajamani, Professor in Mechanical Engineering, is co-leading a NCHRP project funded by the Federal Highway Administration together with Amir Molan, Assistant Professor in Civil Engineering at the University of Mississippi. The project is titled “Performance-Based Superelevation Design Criteria.” The project aims to analyze and refine road superelevation (road bank angle) design guidelines using vehicle-performance-based criteria to address challenges in existing guidelines. The project will focus on the interaction between vehicles and horizontal curves, emphasizing performance measures that prioritize safety, enhance user comfort, and align with acceptable design and construction tolerances. Specifically, the project aims to update current superelevation design criteria to meet the evolving demands of modern transportation, reflecting significant advancements in both vehicle fleets and active safety technologies. Improving superelevation design criteria is critical because horizontal curves are widely recognized as high-risk roadway elements, with crash rates approximately 1.5 to 4 times greater than those of comparable straight sections, according to past studies. The project has a $550,000 budget and a 24-month duration.
Levin Co-Leads New Project on Portable Tool for Optimization of Intersection Signal Timings: Michael Levin, Associate Professor in Civil, Environmental and Geo Engineering, is co-leading a Minnesota Local Road Research Board project together with Rajesh Rajamani, Professor in Mechanical Engineering. The project is titled “Portable Tool for Periodic Evaluations of Intersection Signal Timings.” The safety and efficiency of traffic-signal-controlled intersections depend on appropriate signal timing for intersection users. Yellow, all-red, and crosswalk timings that are too short can create intersection conflicts. Similarly, effective green times that are too small for volumes create long queues and congestion. Signal timings are typically evaluated only every 2-5 years because data collection currently requires a laborious manual process of counting vehicle and pedestrian volumes. Observing intersection behavior to check for safety or efficiency issues is expensive and often does not occur unless major issues are reported. This project will develop a portable device containing low-cost off-the-shelf radar and camera sensors to record the trajectories of intersection users. Fusing camera and radar measurements will enable accurate trajectory tracking, capture signal timings, and differentiate pedestrians, bicycles, and vehicles. The device will compute volumes of specific types of intersection users and their turning movements and evaluate the optimality of signal timings. This is a 2-year project with a budget of $247,824 in direct costs.
Choi Co-Leads New MnDOT Project on Predicting Traffic Speed Distributions: Seongjin Choi, Assistant Professor in Civil, Environmental and Geo Engineering, is co-leading a Minnesota Department of Transportation project together with Raphael Stern, Associate Professor in Civil, Environmental and Geo Engineering. The project is titled “Img2Speed: Generative AI and Multimodal Machine Learning for Predicting Operating Speed Distributions from Roadway Design and Context.” This project will develop a tool that estimates operating speed distributions directly from roadway design and context. Typically, drivers choose speeds based on how a road feels (context) rather than what the sign says, yet the influence of context and road design elements has not been well quantified in a form usable in practice. The project will develop an LLM/VLM-assisted ETL pipeline that converts heterogeneous spot-speed reports into a standardized dataset with automated QA and human-in-the-loop QC, then fuse it with street-view imagery, GIS layers, and cross-section data. Multimodal machine learning models will predict the operating speed metrics used in practice with interpretable attributions to specific design features. Independent spot-speed studies, including before/after data at treatment sites, will then validate the model and test transferability to retrofit scenarios. This is a 2-year project with a budget of $166,847 in direct costs.
Ilic Receives Prestigious DARPA Director’s Fellowship: Ognjen Ilic, Assistant Professor in Mechanical Engineering, has received a DARPA Director’s Fellowship, a highly selective, one-year award that provides $500,000 in additional funding to top performers in the DARPA Young Faculty Award (YFA) program. The fellowship will support Ilic’s continued work on his project “Ultralightweight Nanophotonic Radiators for Adaptive and High-Power Heat Rejection.” Effective thermal management in space is becoming increasingly important as small spacecraft take on more computationally intensive tasks. Advanced onboard computing, imaging, communications, and autonomous operations can generate substantial heat, while small satellites have limited surface area to reject it. In the vacuum of space, spacecraft cannot rely on convection to remove heat and must ultimately reject it as thermal radiation. These constraints can limit how much computing power and other high-performance electronics a small spacecraft can operate continuously. Ilic’s research aims to address this bottleneck with lightweight deployable structures that can radiate high heat loads while adapting to the widely varying thermal conditions experienced in orbit. Ilic's team is developing adaptive thermal emitters based on solid-state phase-change materials that can operate across a broad spectrum, from solar wavelengths through the thermal infrared, combining very low solar absorption with highly switchable thermal emissivity. The team has also developed a new experimental platform for conducting near-space thermal tests aboard stratospheric payloads, enabling the evaluation of thermal emitters under radiative conditions representative of low Earth orbit (LEO). The project’s emphasis on enabling power-intensive onboard computing, imaging, and communication is identified as one of the key DARPA-relevant capabilities. Potential applications include continuous space reconnaissance with reduced distortion or interruption from time-varying thermal stresses; autonomous spacecraft performing power-intensive onboard computing, imaging, and communications; and deep-space missions that depend on stable temperature management.
Coughlin and Aerospace Faculty Receive NASA AI Workforce Development Award: Michael Coughlin, Associate Professor in the School of Physics and Astronomy, will lead a three-year program at the Minnesota Space Grant Consortium of annual summer workshops, monthly colloquia, and faculty-led curriculum development that trains faculty and students across the consortium in agentic AI for NASA-relevant science and engineering. The project is titled “AI Agents for NASA Science and Engineering: Training Minnesota's Next-Generation Aerospace Workforce.” The project will provide $600,000 in total funding over a period of three years, starting June 2026. Because tomorrow's aerospace professionals must be fluent in directing AI agents to accelerate real technical work and understand the failure modes of "vibe coding," we aim to train both capabilities together. Each summer workshop will cover three days. Along with joint sessions, faculty will work on NASA applications and curriculum design, while students focus on verification, validation, reproducibility, and scientific integrity in AI-assisted research. Workshops are held in early June so students can immediately apply the skills in summer placements, including three competitive program-funded internships each year. The workshops rotate across the consortium: the University of St. Thomas (AI for manufacturing and aerospace engineering), Carleton College (AI for astrophysics), and Concordia College Moorhead (AI for remote sensing and Earth observation), with case studies contributed by partner faculty on real problems. Monthly Zoom colloquia sustain the community between workshops and prepare participants with varying coding backgrounds. Other key research team Co-Investigators are Demoz-Gebe Egzhiaber and Ryan Caverly; both are faculty from Aerospace Engineering and Mechanics.
Yang Leads New LCCMR Project on Wildfire Management: Ce Yang, Associate Professor in Bioproducts and Biosystems Engineering, is the PI on a new project that has received support from the Legislative-Citizen Commission on Minnesota Resources (LCCMR) and has been selected for inclusion in their annual recommendations to the Minnesota Legislature on how to allocate proceeds from the state’s Environment and Natural Resources Trust Fund. The project is titled “Wildfire Early Detection and Prescribed-Burn Management Using Drones,” and will provide $823,000 in direct costs to the project team. Other partners on the research team include Jiarong Hong, a professor of mechanical engineering; engineers from the startup company Particle4X; and Troy Mielke from the University of Minnesota Cedar Creek Ecosystem Science Reserve. The project plans to develop autonomous, long-range drone swarm systems equipped with advanced sensors for early wildfire detection and safer prescribed burns to improve air quality and wildfire response strategies. Wildfires increasingly threaten Minnesota’s forests, communities, and air quality. This project will deliver an operational fire and smoke monitoring capability for Minnesota land managers and air-quality agencies, improving wildfire detection, smoke tracking, and protection of communities and natural resources. Rather than developing stand-alone technology, the project will conduct an operational pilot that integrates a coordinated fleet of long-endurance drones equipped with thermal, optical, and air-quality sensors into existing state wildfire detection and monitoring programs. If the 2027 Legislature approves it and the Governor signs it into law, the project would begin as early as July 2027.
Hong Leads New LCCMR Project on Early Warning System for Harmful Algal Blooms: Jiarong Hong, Professor in Mechanical Engineering, is the PI on a new project that has received support from the Legislative-Citizen Commission on Minnesota Resources (LCCMR) and has been selected for inclusion in their annual recommendations to the Minnesota Legislature on how to allocate proceeds from the state’s Environment and Natural Resources Trust Fund. The project is titled “HAB Early Warning Using Imaging Triggered eDNA Analysis,” and will provide $299,000 in direct costs to his research lab. Harmful algal blooms (HABs) are an escalating threat to Minnesota’s lakes, endangering human health, pets, and local economies. Driven by cyanobacteria, these blooms produce potent cyanotoxins, with risks accelerating under increasingly warm conditions with high nutrient levels. Currently, local managers rely on visual checks and periodic (typically weekly) water sampling, followed by laboratory assays, to assess beach safety. This project will pilot a proactive early warning system for beach HABs that combines automated flow imaging with targeted eDNA confirmation. It will deliver validated alert thresholds, manager-ready deployment playbooks, and a public dataset linking cyanobacteria dynamics to Minnesota water conditions. If the 2027 Legislature approves it and the Governor signs it into law, the project would begin as early as July 2027.