NetML Lab | University of Central Missouri

Join Our Research Team in Network Security and Artificial Intelligence/Machine Learning

We invite applications from dedicated and enthusiastic students eager to explore the cutting-edge fields of Network Security and Artificial Intelligence/Machine Learning. We are seeking individuals with a solid foundation in programming and a strong desire to deepen their understanding of theoretical and practical concepts in these rapidly evolving areas.

If you are driven by curiosity and excited to contribute to impactful 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 using the contact information provided below. Your application should include your Curriculum Vitae (CV) and a brief statement outlining your research interests and professional aspirations.

This is more than just an invitation to join a research group — it is an opportunity to be at the forefront of technological innovation within a dynamic and supportive environment. We look forward to the unique perspective and energy you will bring to our team.

Our research has been featured in:
Chameleon Cloud Research Blog
Cybersecurity Guide Podcast

Director:

Ahmet Aksoy, Ph.D. Associate Professor aksoy {at} ucmo.edu

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: