Thang N. Dinh

Associate Professor
2019-present
Assistant Professor
2013-2019
Department of Computer Science
Virginia Commonwealth University
Thang Dinh

Education

Ph.D, Computer Engineering
University of Florida, USA 2008 - 2013
B.S, Information Technology
Vietnam National University, Hanoi, Vietnam 2003 - 2007

Contact

ERB 2321, College of Engineering,
Virginia Commonwealth University,
Richmond, VA, 23284
Email: tndinh [at] vcu.edu

Research Interests:

  • Graph Machine Learning
  • Quantum Computing
  • Approximation Algorithm
  • Applications: Social Networks, Blockchain and Distributed Learning,
    Smart grids, Network security, Drug Discovery, Pandemic modeling
My Erdos number is 3 via the following path: Paul Erdos – Ronald Graham – Panos Pardalos.

Awards and Honors

Selected Publications

  1. Thai, Phuc, My T Thai, Tam Vu, and Thang N Dinh. FastHare: Fast Hamiltonian Reduction for Large-scale Quantum Annealing." 2022 IEEE International Conference on Quantum Computing and Engineering (QCE), 2022.
  2. Thai, Phuc, My T. Thai, Tam Vu, and Thang N. Dinh. SaPHyRa: A Learning Theory Approach to Ranking Nodes in Large Networks." The 38th IEEE International Conference on Data Engineering (ICDE 2022), 2022.
  3. Dinh, Thang N, and My T Thai. AI and blockchain: A disruptive integration., IEEE Computer Magazine, 2018.
  4. Nguyen, Hung T, Tri P Nguyen, Tam N Vu, and Thang N Dinh. Outward influence and cascade size estimation in billion-scale networks." Proceedings of the ACM on Measurement and Analysis of Computing Systems (SIGMETRICS), 2017
  5. Dinh, Thang N, Xiang Li, and My T Thai. Network Clustering via Maximizing Modularity: Approximation Algorithms and Theoretical Limits." IEEE International Conference on Data Mining (ICDM), 2015.

Full List of Publications Google Scholar DBLP Scopus

Research Projects

Quantum-inspired State Estimation

Develops a novel quantum-inspired framework for power state estimation, addressing cyber risks and operational challenges in decentralized grids.

  • Design a quantum network architecture for secure communication in smart grids
  • Develop efficient quantum computing solutions for power state estimation
  • Propose a robust and trustworthy distributed system state estimation using quantum technologies and deep learning

Quantum Leap in Health Optimization

Harness the power of near-term quantum devices for addressing the most pressing human health challenges, including timely drug discovery, a crucial capability in preparation for future pandemics.

  • Innovative approaches to map medical optimization problems onto limited-capabilities NISQ quantum devices
  • Idenitfy optimal positions and shapes of molecules to target proteins
  • Quantum-accelerated medical data analysis for improved diagnoses and treatment plans
Trustworthy and Privacy-preserving Federated Learning

Develops a principled and systematic federated learning framework that offers protection against threats from both malicious users and servers.

  • Develop lightweight secure aggregation and backdoor inspection mechanisms
  • Design a succinct non-interactive argument of knowledge (SNARK) attestation for high accuracy and efficiency
  • Propose a blockchain-based FL architecture for privacy and security protection

Fighting Misinformation and Covert Terrorism Groups on Social Media
Scalable analysis for billion-scale social networks to unveil social dynamic patterns
  • Investigate how the misinformation propagates so quickly and widely into the network
  • What about Twitter and Facebook makes people so gullible and willing to believe anything?

The research is made possible thanks to the support of

NSF DOE CCI Virginia VCU Harmony One Nvidia D-Wave

Teaching