Michigan Tech at Forefront of Federal Cybersecurity Research

Michigan Tech’s cybersecurity research program has been recognized nationally for its academic and research excellence. Michigan Technological University has been designated as a National Center of Academic Excellence in Cyber Research (CAE-R) by the U.S. National Security Agency (NSA). The CAE-R designation recognizes Michigan Tech as meeting rigorous requirements set forth by the NSA and . . .

Student-Athlete Rallies for the Win: Computer Science Grad Shares Secret to Her Success

Juggling academics and athletics, along with the challenges of being a woman in a field dominated by men, hasn’t always been easy for Leiya Rybicki. But Rybicki’s wide support system and leadership skills helped her persevere. The Huskies Women’s Volleyball Team member earned her bachelor’s degree in computer science in spring 2024. Michigan Tech — . . .

Sam Russ ’24, BS in Computer Science, Receives ROTC Distinguished Graduate Award

Sam Russ ’24 BS in Computer Science has received the Air Force ROTC (AFROTC) Distinguished Graduate Award, which is awarded to the top 10% of Air Force ROTC graduates from all universities nationwide. A second AFROTC graduate, Nicholas Drechsler BS in Mechanical Engineering, also received the Distinguished Graduate Award. The Distinguished Graduate Award is the . . .

Crowdsourcing Ticks for Disease Surveillance

Tick Talk, the crowdsourcing tick collection project conducted last year at Michigan Tech, has returned for a second year. Tick collection has already begun for 2024. MTU’s Genomic Sequencing Lab wants ticks from you, your family and your pets. The goal of this project is to identify the prevalence of tick-borne illnesses in the Copper Country. Please . . .

Paper by CS Grad Student Pawel Pratyush Published in Bioinformatics Journal

A paper by graduate student Pawel Pratyush, PhD in Computer Science, has been published in Bioinformatics, a publication of Oxford University Press and a top journal in the bioinformatics field. The title of the paper is, “LMCrot: An enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language model.” . . .