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UNI

Building Secure and Trustworthy Autonomous Systems

Self-funded 🎓 Artificial Intelligence 🎓 Computer Science machine learning autonomous systems artificial intelligence privacy cyber-physical systems security embodied ai critical infrastructure

Explore security and trust issues in autonomous systems including robots and vehicles. Develop resilient cyber-physical systems using advanced AI and privacy techniques. Address real-world challenges in infrastructure protection and autonomous system safety.

AI-generated overview

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Why This Research Matters

Research in secure and trustworthy autonomous systems is critical as these technologies become integral to transport, robotics, and infrastructure. Enhancing their security and resilience protects against cyber threats and privacy breaches, supporting safer deployment and public trust in autonomous technologies.

Additive Manufacturing Optimization modeling

Project Description

Project Overview

This research project aims to develop secure, resilient, and trustworthy autonomous cyber-physical systems. It includes focus areas such as autonomous driving, humanoid robots, and embodied AI/physical AI systems integrated into critical infrastructure. The project addresses key challenges in the interaction between cyber and physical components to improve overall system safety and reliability.

What You Will Do

Students will engage in research related to security and privacy, artificial intelligence, cyber-physical systems, embodied AI, and critical infrastructure. The work will involve designing, modeling, and testing approaches that enhance security and trustworthiness in autonomous systems, with implementations potentially advancing autonomous driving technologies and robotic systems.

Expected Outcomes

The project expects to deliver novel methodologies and tools for improving the security and robustness of embodied AI systems and cyber-physical infrastructures. Outcomes include secure autonomous platforms resistant to cyber threats, advancements in privacy-preserving AI, and contributions toward safer deployment of autonomous technologies.

Why This Matters

As autonomous systems penetrate critical sectors of society, ensuring their security and dependability becomes paramount. This research will help prevent security breaches, protect privacy, and secure infrastructures critical to social and economic well-being, enabling safer adoption of autonomous technologies globally.

Entry Requirements

BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or a relevant field. Research experience in AI/ML, Cyber-Physical Systems, or Cybersecurity is required. Proficiency in Python and hands-on experience with machine learning libraries are necessary.

How to Apply

Send your application package to Dr. Shahriar at hshahriar@vt.edu. For detailed instructions please visit: shahriar0651.github.io/

Eligibility

UK/Home
EU
International

Supervisor Profile

DH
Dr. Hasan Shahriar
University of Arkansas

Dr. Hasan Shahriar earned his PhD in Computer Science from Virginia Tech in Spring 2026 and will start as Assistant Professor at the University of Arkansas in Fall 2026. His research interests lie in optimization modeling and additive manufacturing, with a focus on improving mechanical properties through advanced methodologies such as the Grey-Taguchi approach. He is an emerging scholar in cyber-physical systems and autonomous system security.

Key Publications

2022 5 citations
Grey-Taguchi approach to optimize fused deposition modeling process in terms of mechanical properties and dimensional accuracy
2021 2 citations
Grey-Taguchi Approach for Optimizing Fused Deposition Modeling Process in Terms of Mechanical Properties and Dimensional Accuracy

Research Contributions

Application of Grey-Taguchi approach to optimize fused deposition modeling processes focusing on mechanical properties and dimensional accuracy.
Enables improvements in additive manufacturing processes by enhancing product quality and accuracy.

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