Forging our Future
Within the College of Engineering Technology, our 'Forging our Future' research initiatives are driving the digital and physical transformation of global industry through advanced manufacturing and intelligent systems. Our work pushes the boundaries of innovation in areas like additive manufacturing and 3D printing, advanced materials characterization, industrial automation, and the integration of 'Industry 4.0' technologies, while fostering the cross-disciplinary expertise required to lead the next generation of smart manufacturing and production.
Featured Faculty
Research Summary
At Trefoil Lab, we focus on the discovery, processing, and design of advanced materials that perform in extreme environments and enable next-generation energy technologies. Our work spans from atomic-scale synthesis to architected systems, integrating chemistry, materials science, and mechanical engineering. By coupling experimental research with machine learning and additive manufacturing, we accelerate the design–discovery cycle for functional materials.
Broader Impact
Our research addresses urgent global needs in sustainable energy, resilient infrastructure, and advanced manufacturing. Materials that can withstand extreme conditions, store and convert energy efficiently, and be produced with minimal waste are critical for tackling climate change, energy security, and technological competitiveness.
Research Summary
My research focuses on developing robust causal learning frameworks for robotic manipulation. In the ROCAL lab, I aim to move beyond simple correlation-based learning to build models that understand the underlying "physics" of interaction, enabling robots to reason about cause and effect when handling complex, deformable, or fragile objects. This involves creating new methods to learn causal relationships directly from multi-modal sensory data, such as vision, touch, and proprioception.
Broader Impact
This research addresses a fundamental scientific challenge in AI and robotics: creating machines that can generalize and adapt to new situations. By learning causal models, robots can move beyond pattern matching and begin to understand their environment, leading to safer, more reliable, and more autonomous systems. Societally, this work has direct applications in critical areas like robotic surgery, where understanding the causal impact of a tool's movement is essential for improving patient outcomes, and in advanced manufacturing for the delicate assembly of electronics and other fragile components.
Research Summary
I focus my research on critical challenges in electronics manufacturing, with particular emphasis on soldering and semiconductor packaging processes. I investigate methods to optimize manufacturing parameters to minimize defect formation and systematically evaluate their influence on device reliability. Through this work, I aim to advance understanding of the relationship between process control, defect mechanisms, and long-term performance in electronic assemblies.
Research Summary
I passionately study pedagogy and innovate educational technologies to best form effective engineering problem-solvers for our world. My research ranges from evaluating the ethical implications of engineering judgment during design to creating AI teaching tools for problem-solving. I welcome collaborations with those interested in aligning classroom practice with human-centered values, whether through research, curriculum design, or developing new tools to support learners.
Broader Impact
Engineering is often taught as a series of disconnected equations and technologies that are isolated from the people and problems it is meant to serve. My research focuses on reshaping educational experiences to help students develop engineering judgment that centers human and societal needs. This includes designing instructional strategies grounded in learning science and integrating AI tools that connect technical content with real-world relevance.
Research Summary
My research is dedicated to transforming conventional and digital printing manufacturing technologies into a strategic platform that converges printed flexible electronics with sustainable materials science. One stream advances functional printing of electronics, sensors and circuits using conductive inks, photonic curing, rheological control, and interface engineering—driving scalable applications in smart packaging, IoT and wearables, healthcare diagnostics, automotive and aerospace systems, and environmental monitoring. Another stream develops bio-based nanofibers, biopolymers, sustainable coatings and barrier materials by engineering agricultural residue-based materials to replace petroleum-based and PFAS “forever chemicals” containing products, while achieving superior mechanical, barrier, and optical performance. Together, these innovations position printing technologies as a cross-sector catalyst for climate resilience, health innovation, and global manufacturing competitiveness, advancing both scientific discovery and industrial impact.
Broader Impact
This work advances printed electronics enabling lightweight flexible electronics, sensors and circuits for applications in (1) IoT: wearable and embedded devices, (2) medical & healthcare: biosensors, antimicrobial surfaces, and diagnostic packaging, (3) automotive, aerospace & space: lightweight, temperature-resistant printed sensors and coatings, (4) environmental protection: PFAS-free barriers, and waste valorization. (5) consumer packaging: sustainable food and non-food packaging with improved barrier and safety properties. This dual pathway—sustainability and functionality—links materials research to societal imperatives such as circular economy, decarbonization, and next-generation smart manufacturing.
Research Summary
My research lab pioneers photonic technologies & studies the behavior of light in a variety of applications, including communications and healthcare. My research also encompasses reliability testing and biomedical science & engineering.
Broader Impact
My research in photonics seeks to improve fiber-optic communication systems, free-space optical communications, and healthcare, and seeks to deepen understanding of the behavior of light. My research in biomedical science & engineering seeks to improve diagnosis and treatment of diabetes, cancers, and heart disease. My research in reliability testing seeks to advance the state of art in manufacturing.
Research Summary
Design and simulation of the packaging materials and structure in the supply chain for improving the barrier and physical protection.
Broader Impact
Packaging science is relevant to sustainability and food security.
Research Summary
I research applied deep learning models to strengthen cybersecurity for computer systems, IoT devices, communication networks, and hardware. The main challenge is twofold: (1) learn patterns to authenticate a device, system, or person, and (2) identify anything that falls outside those patterns—intrusions, anomalies, or spoofing attempts. For example, in the wireless field, I focus on RF sensing and device fingerprinting, while in hardware, I use side-channel electromagnetic (EM) emissions to authenticate IoT components.
Broader Impact
My research addresses key challenges in ensuring the trustworthiness of cyber-physical systems at scale, including understanding complex, high-dimensional signals, handling variant conditions and noisy real-world environments, and distinguishing legitimate behavior from anomalies. It relates to broader questions of reliability, robustness, and resilience in intelligent systems—important aspects for the forthcoming generation of networked devices and autonomous systems infrastructure.
Societally, the stakes are high: everyday life now depends on connected devices across energy, healthcare, transportation, and manufacturing. Breaches and counterfeits pose a threat to safety, privacy, and supply-chain integrity, increasing costs and degrading public trust. By improving how we verify identity and detect misuse across these systems, this research supports safer critical infrastructure and more resilient services that the public can rely on.
Research Summary
Coding and modulation for communications, including bandwidth-efficient coding. Signal processing in communications, potentially using ML techniques. Development of teaching tools and platforms for hands-on software-defined networking.
Broader Impact
Improving the capability and security of our communication systems and networks.
Research Summary
Using model-based design tools and code generation to accelerate the development of FPGA-targeted algorithms. UAV localization in GPS-denied environments via embedded vision. Developing hardware efficient AI algorithms for localization and navigation.
Broader Impact
Accelerating the development of FPGA algorithms will increase the rate of innovation. This work is sponsored by the Mathworks, a leader in scientific computing.
