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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.

why CHIPS research?

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

TECH 206 | (713) 313.4482
Curriculum Vitae

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


Professor and Acting Dean and Chair
TECH 314B | (713) 313.1871
Curriculum Vitae

Professor and Interim Chair
TECH 125 | (713) 313.7914
Curriculum Vitae

TECH 105 | (713) 313.7285
Curriculum Vitae

Associate Professor
TECH 323 | (713) 313.7994
Curriculum Vitae

Associate Professor
TECH 418 | (713) 313.7967
Curriculum Vitae

Assistant Professor
TECH 101 | (713) 313.7119
Curriculum Vitae

Associate Professor
TECH 205 | (713) 313.1864
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.