Hongmei Dang, Ph.D., is an Associate Professor in the Department of Electrical and Computer Engineering (ECE) and Program Director for the Master of Science in Electrical Engineering program.
She specializes in the Full-Stack Architecture of high-performance computing systems, with a focus on the “Algorithms-to-Silicon” design methodology. Her work optimizes the intersection of AI/ML requirements, computer architecture, advanced VLSI, and deep-submicron semiconductor physics.
Dr. Dang’s current research is dedicated to bridging the gap between high-level algorithmic logic and physical silicon realities. By focusing on PPA-optimized hardware (Power, Performance, Area), she addresses the critical efficiency, and latency demands of next-generation AI workloads. Before, her research focused on semiconductor physics and fabrication. This deep-level expertise ensures her architecture is grounded in the physical realities of deep-submicron manufacturing, maintaining high performance at the advanced process nodes.
Experience
Courses Taught
Digital System-Level Design (Computer Architecture)
Advanced Digital Integrated Circuit Design (Advanced VLSI)
Microelectronics I & II (and associated Laboratory)
Semiconductor Physics & Device Fabrication
Expertise
Technical Expertise & Research Leadership
Dr. Dang leverages a unique dual-background in Electrical and Computer Engineering (PhD) and Physics (MS) to lead research in hardware-software co-design. Her technical leadership and expertise include:
Advanced Computer Architecture: System-level design and optimization of the vertical stack, from high-level algorithms down to hardware-efficient execution logic.
Full-Stack RTL & VLSI: Driving digital modules from microarchitecture specifications through Verilog RTL and physical implementation.
Physically-Aware Design: Mitigating deep-submicron constraints, including interconnect RC delay and thermal/power scaling, at the architectural level.
Industry Collaboration
A recognized leader in orchestrating high-impact research, Dr. Dang has managed a $5.2M research portfolio. Her initiatives were supported by strategic partnerships, such as the Apple HBCU New Silicon Initiative, as well as federal grants from the National Science Foundation (NSF) and the Department of Energy (DOE). In 2024, she received the Excellence in Funding Award at UDC for her success in managing complex semiconductor research programs and infrastructure.
Impact
As the Director of the Master of Science in Electrical Engineering program, she defines Advanced VLSI and Computer Architecture tracks, mentoring graduate students through the end-to-end silicon lifecycle and preparing them for the roles in the semiconductor industry.
Selected Publications
Garfield, B., Orebiyi, D., & Dang, H. (2023). Development of earth-abundant benign TiO2 /Sb2Se3 solar cells for renewable energy application. Proceedings of the Emerging Researchers National Conference.
Dang, H., Ososanya, E., & Zhang, N. (2022). Improving reliability of window-absorber solar cells through CdS nanowires.Optical Materials, 132, 112721. https://doi.org/10.1016/j.optmat.2022.112721
Dang, H., Ososanya, E., & Zhang, N. (2022). Comparison of electrical characteristics of Schottky junctions based on CdS nanowires and thin film. Nanotechnology, 33.https://doi.org/10.1088/1361-6528/ac51eb
Dang, H., Tyagi, P., Ososanya, E., & Klein, K. (2021). Project based course enabled nanotechnology education for senior level undergraduate and graduate students. Proceedings of the ASME 2021 International Mechanical Engineering Congress and Exposition. Volume 9: Engineering Education.https://doi.org/10.1115/IMECE2021-68827
Dang, H., Valdivia, J., Robera, J., Onwuvuche, O,, Lodge, T., Ososanya, E., & Wang, L. (2020). Modeling efficiency loss in Sb2Se3 solar cells. Proceedings of the 2020 Photovoltaic Specialists Conference.
Selected Grants
Apple. (2021). Apple HBCU new silicon initiative.
Department of Education. (2022). Development of efficient and stable perovskite solar cells with SnO2 as electron transport layer.
National Science Foundation. (2020). MRI acquisition of dual beam FIB/SEM to enable new capabilities for research, education, and training at UDC.
National Science Foundation. (2019). Center for nanotechnology research and education at UDC.
National Science Foundation. (2019). Acquisition of a VersaLab physical property measurement system at UDC.
