NetML Lab | University of Central Missouri

Join Our Research Team in Network Security and Machine Learning

Dr. Aksoy invites applications from dedicated and enthusiastic students eager to delve into the realms of Network Security and Machine Learning. We are on the lookout for individuals who bring a strong foundation in programming and a keenness to assimilate theoretical concepts in these cutting-edge fields.

If you are driven by curiosity and ready to contribute to groundbreaking research, we would love to hear from you. To express your interest, please arrange a meeting by visiting Dr. Aksoy's office, or submit your application via contact information provided below. Your application should include your Curriculum Vitae (CV) and a brief statement of your research interests and professional aspirations.

This is more than a call for participation; it's an invitation to be at the forefront of technological innovation in a dynamic and supportive research environment. We eagerly await the unique perspective you will bring to our team.

Research appeared in Chameleon Cloud Research Blog.
Research featured in NSA CAE Tech Talk Platform.
Research featured in Cybersecurity Guide Podcast.

Director:

Ahmet Aksoy, Ph.D. Assistant Professor aksoy {at} ucmo.edu Department of Computer Science & Cybersecurity University of Central Missouri

Current Students:

		Yaman Shrestha Leveraging Large Language Models for Efficient Incident Classification in Cybersecurity yxs33220 {at} ucmo.edu
		Khursaid Ansari Leveraging Large Language Models for Efficient Incident Classification in Cybersecurity kxa45490 {at} ucmo.edu
		Mayank Dembla AI-Driven User Behavior Fingerprinting for Enhanced Security and Threat Detection mxd08640 {at} ucmo.edu
		Joshua Kiran Yajjala AI-Driven User Behavior Fingerprinting for Enhanced Security and Threat Detection jxy55130 {at} ucmo.edu

Previous Students:

		Sundeep Varma Comparative Analysis of Feature Selection Algorithms for Automated IoT Device Fingerprinting sxv54730 {at} ucmo.edu
		Luis Valle Automated Network Incident Identification through Genetic Algorithm-Driven Feature Selection lev33910 {at} ucmo.edu
		Sachin Rana Automated Fast-flux Detection using Machine Learning and Genetic Algorithms sxr53490 {at} ucmo.edu
		Emiline Stewart Network Traffic Fingerprinting using Artificial Bee Colony Algorithm ers10570 {at} ucmo.edu
		Enya Pan Comparative Analysis of Feature Selection Algorithms for Automated IoT Device Fingerprinting exp99350 {at} ucmo.edu
		Sharwin Reddy Network Traffic Fingerprinting using Ant Colony Algorithm sxp32460 {at} ucmo.edu

Lab: