Microelectronics Digital Twins Research and Education
Mission and goals
This initiative aims at amplifying the research and innovation at Texas Southern University in the area of semiconductors, microelectronics and advanced packaging. The research initiative is paired with education opportunities and workforce development.
Our goal is to participate as a members in the Semiconductor Manufacturing and Advanced Research with Twins ( SMART ) USA Institute USA Institute. SMART is a CHIPS Manufacturing USA Institute, an industry-led, government enabled broad partnership to supercharge innovation in industry today, led by Semiconductor Research Corporation.
Research groups and centers:
- Center for Scientific Machine Learning for Material Science
- Center for High Performance Computing
- Advancing Basic Science Research and Undergraduate Education in Computer Vision
Point of Contact
Contact Information
Department of Physics
Technology Building, Room 201
Texas Southern University
3100 Cleburne Avenue, Houston TX 77004
tel: 713-313-4482
fax: 713-313-1833
Investigators
Professor and Acting Dean and Chair
TECH 314B | (713) 313.1871
wei.li@tsu.edu
Curriculum Vitae
Professor and Interim Chair
TECH 125 | (713) 313.7914
graham.thomas@tsu.edu
Curriculum Vitae
Associate Professor
TECH 323 | (713) 313.7994
aladdin.sleem@tsu.edu
Curriculum Vitae
Associate Professor
TECH 418 | (713) 313.7967
yunjiao.wang@tsu.edu
Curriculum Vitae
Assistant Professor
TECH 101 | (713) 313.7119
ismet.sahin@tsu.edu
Curriculum Vitae
Associate Professor
TECH 205 | (713) 313.1864
mark.harvey@tsu.edu
Curriculum Vitae
Current Graduate Students
Current and Past Summer Research Students
Research and Development
- Digital Twins and Simulation of Manufacturing processes driven by Machine Learning and AI
- Analog Semiconductor devices and multimodal microelectronics
- AI/Linear Algebra specialized chips
- Advanced Optimization: Supply Chain, Chip Architecture, Routing, Packaging, Integration
- “There’s Plenty of Room at the Bottom” (Richard P. Feynman): Low dimensional quantum material defect-based devices
Equipment and Labs
High Performance Computing Lab
Presentations and Conference Papers
Journals Papers
- D. Vrinceanu Accurate quantum states for a 2D-dipole Nanomaterials 14, 206 (2024)
Graduate Programs
- MS in Computer Science: “Machine Learning and Artificial Intelligence”
- MS in Mathematics: “Statistical Learning”
- MS in Engineering (Fall 2025): “Integrated Circuits & Systems”, “Power Engineering”
- Ph.D. in Physics (Fall 2025): “Solid State Physics”, “Quantum Physics”
Workforce Development Strategy:
Building relations with local semiconductor leaders to identify and quantify essential skills and knowledge for technological workforce of the future.
