experiences
A showcase of my professional experiences and achievements.
Sep 2023 - Present
Nashville, TN, USA
Graduate Research Assistant
Vanderbilt University
- Currently working on a project funded by NSA "Improving Malware Classifiers with Plausible Novel Samples"
- Research Interests on Security and Privacy in AI Systems, Federated Learning, Reinforcement Learning, Ethical AI Usage
Skills: Federated learning, generative models, adversarial machine learning, backdoor attacks, machine unlearning, deep learning, predictive modeling
Sep 2022 - July 2023
Hanoi, Vietnam
Research Assistant
Vinuni-Illinois Smart Health Center
- Developed a novel imperceptible attack achieving 100% success rates with durable backdoor effects, bypassing defenses in federated learning.
- Conducted and published a comprehensive survey of backdoor attacks, defenses, and future directions in FL.
- Evaluated federated unlearning methods empirically using MNIST, CIFAR-10, and CIFAR-100, demonstrating challenges in balancing unlearn time and efficacy.
Skills: Federated learning, generative models, adversarial machine learning, backdoor attacks, machine unlearning, deep learning, predictive modeling
Sep 2019 - Aug 2022
Hanoi, Vietnam
Undergraduate Researcher
- Designed a reinforcement learning-based optimization algorithm for wireless rechargeable sensor networks, optimizing charging locations and times to extend network lifetime by up to 8.29x over existing methods.
- Developed applications for Fi-Mi, an AI-driven mobile air quality monitoring and forecasting system, enabling real-time data processing and display from sensors mounted on buses in Vietnam.
Skills: Optimization, reinforcement learning, application programming, time-series forecasting and calibration
Oct 2022 - Dec 2022
Tokyo, Japan
AI Research Intern
National Institute of Advanced Industrial Science and Technology (AIST)
- Developed FedGrad, a defense achieving a 90% reduction in attack success rates.
- Designed methods for near-perfect malicious participant detection in federated learning systems.
- Demonstrated robust performance of FedGrad against advanced attacks, even with 50% malicious clients under heterogeneous data settings.
Skills: Federated learning, adversarial machine learning, defense mechanisms, heterogeneous data, AI research
May 2021 - Dec 2021
Hanoi, Vietnam
Software Engineer Intern
- Developed fast, reliable, customizable online storefronts for retail businesses (Front-end).
- Designed and reviewed technical architecture proposals for emerging features, including multilingual conversion and integrating databases to support multiple languages.
Skills: Front-end development, technical architecture design, multilingual systems, database integration, retail technology
Jun 2020 - Feb 2021
Hanoi, Vietnam
Software Engineer Intern
MDC Software Solutions
- Developed a mobile-platform social network for product reviews, enhancing user engagement through seamless UI/UX design and providing real-time feedback features.
- Researched and deployed cutting-edge deep learning models (YoLo and StyleGAN) on iOS apps, enabling advanced features such as real-time image recognition and predictive analytics for enhanced user experience.
Skills: Mobile app development, UI/UX design, real-time systems, deep learning models, YoLo, StyleGAN, iOS development, predictive analytics
Dec 2021 - Aug 2022
Hanoi, Vietnam
Undergraduate Researcher
Vinuni-Illinois Smart Health Center
- Developed FedDRL, a deep reinforcement learning-based FL aggregator addressing data heterogeneity and cluster-skewed distributions, outperforming FedAvg and FedProx by up to 4.05% on various datasets.
- Designed the PIKA architecture, combining external prescription data and knowledge graphs to enhance pill image recognition, achieving up to a 34.1% F1-score improvement over baselines.
Skills: Federated learning, adversarial robustness, anomaly detection, deep reinforcement learning, graph modeling, object detection