Annual Department Highlights

2022-23 Department Highlights

The Department of Computer Science is pleased to share our academic year accomplishments. Highlights include department recognitions, student accomplishments, notable research awards, and annual student enrollment.

Faculty

  • 21 Tenure-track/Tenured
  • 3 Instructional Track

New Faculty

  • Serein Al-Ratrout, Assistant Teaching Professor
  • Ye Duan, Professor
  • Wenbin Zhang, Assistant Professor

Fall 2022 Student Enrollment

Computer Science

  • BS    438
  • MS     26
  • PhD   29

Software Engineering

  • BS    118

Cybersecurity

  • MS      7

Data Science

  • MS    39

New Degree Programs

  • MS in Applied Computer Science
  • BS in Data Science

Student Highlights

  • Fall 2022 NCL cybersecurity competition – Michigan Tech team ranked 8th in the nation

Faculty Recognition

  • Michigan Tech recognized as National Center for Academic Excellence in Cyber Defense
  • Bo Chen: Distinguished Member, European Alliance for Innovation, Class of 2022
  • Keith Vertanen: Dave House Associate Professor of Computer Science
  • Briana Bettin: Lead author of the best paper at the 27th ACM Conference- on Innovation and Technology in Computer Science Education
  • Zhenlin Wang: Co-author of the best paper at the 2023 ACM International Conference on Supercomputing

Funding Highlights

  • Chen, B., Wang, Z., SaTC: CORE: Small: Hardware-assisted Self-repairing in Decentralized Cloud Storage against Malicious Attacks, NSF
  • Nekritch, Y., AF: Small: Fundamental Geometric Data Structures, NSF
  • Mayo, J., Phase II STTR: MDA20-T002 Non-Real-Time Hardware-Assisted Computer-System Simulation, DoD
  • Onder, S., Collaborative Research: SHF: Medium: Vectorized Instruction Space (VIS), NSF
  • Havens, T., Enabling the Future of Great Lakes Biological Resource Assessment, DoI
  • Dukka, K., Wang, Z., Brown, L., MRI: Acquisition of a GPU-accelerated cluster for research training and outreach, NSF
  • Havens, T., SAR Signature Management, DoD
  • Dukka, K., Deep learning based approaches for protein post-translational modification site prediction, NSF

External Funding ($)