I am a Ph.D. candidate in the Department of Computer Science at Virginia Tech, focusing on computer vision, distributed AI, and human–AI teaming. I am advised by Dr. Kurt Luther in the Crowd Intelligence Lab and by Dr. Feras Batarseh in the A3 Lab. During my doctoral studies, I also still serve as a Data Scientist and AI Research Engineer at the U.S. Army DEVCOM C5ISR Center, where I lead innovation projects in embedded vision, augmented reality, and AI-enabled threat recognition.

My research bridges technical development and applied deployment, exploring trustworthy AI, shared perception platforms, and crowd-in-the-loop methods to support decision-making in cyber-physical systems. My research has been published at top-tier HCI and AI conferences and journals like IUI, TiiS, and EAAI.

I bring expertise in leading cross-disciplinary teams, managing large-scale R&D portfolios across Technology Readiness Level (TRL) 6.2–6.3, and aligning advanced AI methods with mission-critical needs.

I am currently seeking opportunities as a Senior Technical Project Manager or AI R&D Manager, where I can combine my research expertise with program leadership to drive innovation and deliver transitionable solutions.

Publications

1. M. Wilchek, M. Nguyen, Y. Wang, K. Luther, and F. A. Batarseh. 2025. PerceptiSync: Trustworthy Object Detection using Crowds-in-the-Loop for Cyber-Physical Systems. ACM Transactions on Cyber-Physical Systems, Jul 2025. (ACM TCPS)
   

   • Introduces PerceptiSync, a framework for integrating human feedback into AI-driven object detection pipelines.
   • Evaluates system performance and trust calibration across distributed sensing platforms.

2. M. Wilchek, L. Wang, S. Dickinson, E. Feuerbacher, K. Luther, and F. A. Batarseh. 2025. KHAIT: K-9 Handler Artificial Intelligence Teaming for Collaborative Sensemaking. Proceedings of the 30th International Conference on Intelligent User Interfaces (IUI '25). (ACM IUI 2025)
   

   • Presents KHAIT, a system for augmenting canine search-and-rescue operations with AI-enabled sensing and AR interfaces.
   • Demonstrates collaborative decision-making between handlers, dogs, and AI agents.

3. M. Wilchek, K. Luther, and F. A. Batarseh. 2025. Ajna: A Wearable Shared Perception System for Extreme Sensemaking. ACM Transactions on Interactive Intelligent Systems (TiiS), Mar 2025. (ACM TiiS)
   

   • Introduces Ajna, a wearable AR platform that enables distributed teams to share AI-driven perception in extreme environments.
   • Evaluates system scalability and human-AI collaboration dynamics in simulated field scenarios.

4. M. Wilchek, W. Hanley, J. Lim, K. Luther, and F. A. Batarseh. 2023. Human-in-the-Loop for Computer Vision Assurance: A Survey. Engineering Applications of Artificial Intelligence, Vol 123, Part B, 2023, 106376. (EAAI)
   

   • Comprehensive survey of 100 human-in-the-loop methods for AI assurance in computer vision systems.
   • Highlights gaps in trust, explainability, and evaluation metrics for mission-critical AI deployments.

5. M. Wilchek and Y. Wang. 2021. Synthetic Differential Privacy Data Generation for Revealing Bias Modelling Risks. IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom), 2021. (IEEE ISPA 2021)
   

   • Proposes a synthetic data generation approach to evaluate bias modeling risks under differential privacy constraints.
   • Demonstrates applications for sensitive data environments and fairness analysis.