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Intelligent and Quantum Secure Advanced Cyber Defense Research (IQSeC) Lab

Research Overview

The IQSeC Lab develops practical, forward-looking research at the intersection of machine learning, cybersecurity, and quantum security. Our work spans malware analysis, traffic analysis, intelligent cyberdefense, and quantum-secure communication, with a particular emphasis on preparing security systems for the post-quantum era.

Machine Learning for Endpoint Security

We build adaptive malware analysis and detection systems that remain effective as threats, software behavior, and data distributions change over time.

  • Continual learning for evolving malware families
  • Robust detection under concept drift and class imbalance
  • Reliable models that reduce catastrophic forgetting

Machine Learning for Network Security

We study how intelligent methods can reveal, measure, and defend against privacy and security risks in modern networked systems and encrypted traffic.

  • Traffic analysis and side-channel leakage in encrypted communications
  • Attack and defense models for privacy-preserving networks such as Tor
  • Data-driven techniques for resilient network defense

Quantum Security

Quantum security is a central focus of the lab. We study how communication and cyberdefense systems should evolve in the presence of quantum capabilities, from analyzing post-quantum vulnerabilities to designing quantum-secure communication frameworks.

  • Post-quantum cryptography for resilient next-generation security systems
  • Quantum key distribution and architectures for quantum-secure communication
  • Quantum machine learning and intelligent cyberdefense for emerging threat models

Current Students

The IQSeC Lab is fortunate to have a group of bright and dedicated students who contribute to advancing our research.

PhD Students

  • Saeefa Rubaiyet Nowmi
  • Md Mahmuduzzaman Kamol

BS/MS Students

  • Jesus Lopez
  • Viviana Cadena
  • Cristina L Alarcon
  • Eduardo Menendez

Visiting Scholars and Collaborators

  • Se Eun Oh, Assistant Professor, Ewha Womans University
  • Zahra Asadi Naderabadi
  • Shahrooz Pouryousef
  • Haeseung Jeon
  • Jungmin Park
  • Saeyeon Hong
  • Jimin Park
  • AHyun Ji
  • Md Mahmudul Alam Imon

Collaborators

The IQSeC Lab collaborates with respected academic institutions and industry to advance research. These partnerships enable us to leverage complementary expertise and perspectives in pursuit of shared research goals.

Prospective Students

If you are a current UTEP student, please email me to set up a meeting to discuss further.
If you are not a current student and are interested in working with me, please continue reading.

General PhD/MS openings remain limited.
A dedicated PhD opening in Quantum Security and Intelligent Cyberdefense is currently posted.

View the current PhD opening

Qualifications

A prospective PhD student should hold a bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or a related field. The ideal candidate is motivated to conduct research in machine learning and cybersecurity and demonstrates proficiency in at least three of the preferred skills listed.

My goal is to provide resources and guidance to help students become strong, independent researchers.

Preferred Skills/Experience

  • Programming in Python, PyTorch, and/or TensorFlow
  • Research or hands-on experience in Malware Analysis
  • Experience in Wired and Wireless Networking
  • Research or practical experience in ML/AI
  • Experience with Large Language Models (LLM)
  • Basic understanding of Quantum Information Science
  • Familiarity with Kali Linux, MITRE ATT&CK framework, Pentesting, and Hugging Face is a plus

Some Useful Resources