Indrakshi Ray
Director
Professor in Computer Science Department at Colorado State University
Email: Firstname.Lastname@colostate.edu
Office: CSB 440
Phone: 970-491-7986
Computer Science Department
Colorado State University
The RaysCyberLab is part of the Computer Science Department of Colorado State University (Fort Collins, CO). Members of the laboratory are engaged in cutting-edge research on all aspects of computers, networks, and information security. We do both theoretical and systems work in areas such as data and application security, network security, security modeling, risk management, trust models, privacy and digital forensics, database systems, e-commerce, and formal methods in software engineering. Current research includes:
Indrajit Ray won the NSF Convergence Accelerator Award – Proactive End-to-End Zero Trust-Based Security Intelligence for Resilient Non-cooperative 5G Networks
Hossein Shirazi, from our group, won the Anita Reed award 2021
Dr. Indrajit Ray has got a new grant, Flexible Simulation Environment for the Evaluation of Cyber Risk in Nuclear Power Plants, from DoE, 2021
Dr. Indrakshi Ray has been awarded the Professor Laureate at the College of Natural Sciences of Colorado State University, 2021 – Dr. Ray’s Professor Laureate lecture on Youtube
Statnett, Norway, joins CSU’s Cybersecurity Analytics and Automation Center
Cyber Risk Research joins CSU’s Cybersecurity Analytics and Automation Center
We won the best paper award for the paper “Improved Phishing Detection Algorithms Using Adversarial Autoencoder Synthesized Data”, 2020.
Congressman Joe Neguse announces $199,748 grant for Colorado State University COVID-19 research.
NSF awarded RAPID: Ensuring Integrity of COVID-19 Data and News across Regions
Our research won the platinum award in CSU Ventures: Drivers of Innovation category at the CSU graduate showcase.
We participated at the inaugural Cyber-Truck Challenge, Warren, Michigan, 2017. The event was a great success. Read more at CSU source.
Colorado State University to deploy machine-learning tool that can detect falsified COVID-19 medical records.
Poster Paper accepted at The 24th ACM Conference on Computer and Communications Security, 2017.
Full-Length paper accepted at The 15th International Conference on Privacy, Security, and Trust, 2017.