Dr. Dang Quang Vinh
Vinh graduated with a Bachelor’s degree in Computer Science from Vietnam National University – Hanoi in 2009. He earned his PhD in Computer Science from Université de Lorraine in 2018, completing his thesis under the supervision of Prof. François Charoy and Dr. Claudia Ignat at Inria Nancy Grand-Est, France. He also holds a Bachelor’s degree in Law from Hanoi Law University (2013) and a Master’s degree in Financial Engineering from WorldQuant University (2021).
Vinh is actively involved in academic research, with over 50 papers indexed in Scopus, most of which he authored as the first author. As of August 2024, he has an h-index of 15 and more than 650 citations.
In addition to his academic achievements, Vinh has extensive experience in the software industry. He has served as a Project Manager at FPT Software, Head of Data Science at Be Group, Head of Data at DatViet VAC, and Chief Data Officer at several startups. He has also led R&D efforts at various other companies.
ACADEMIC QUALIFICATIONS
- Doctor of Philosophy (2014 – 2018)
Universite de Lorraine, Nancy, France
Thesis: Trust assessment in large-scale collaborative systems - Master in Computer Science (2009 – 2012)
Vietnam National University – Hanoi - Master in Financial Engineering (2019 – 2021)
WorldQuant University – USA - Bachelor in Computer Science (Hons) (2005 – 2009)
Vietnam National University – Hanoi - Bachelor in Law (2010 – 2013)
Hanoi Law University
PROFESSIONAL APPOINTMENTS
- RMIT University (Vietnam)
Lecturer (2023 – 2024) - Industrial University of Ho Chi Minh City (Vietnam)
Lecturer (2019-2023)
RESEARCH AREAS / FIELDS
- Machine Learning
- AI
- Cyber security
RESEARCH PUBLICATIONS
- Dang, Q.V. and Ignat, C.L., 2016, June. Quality assessment of wikipedia articles without feature engineering. In Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries (pp. 27-30).
- Dang, Q.V., 2019. Studying machine learning techniques for intrusion detection systems. In Future Data and Security Engineering: 6th International Conference, FDSE 2019, Nha Trang City, Vietnam, November 27–29, 2019, Proceedings 6 (pp. 411-426). Springer International Publishing.
- Dang, Q.V. and Ignat, C.L., 2016, November. Measuring quality of collaboratively edited documents: The case of Wikipedia. In 2016 IEEE 2nd international conference on collaboration and internet computing (CIC) (pp. 266-275). IEEE.
RESEARCH & CONFERENCE PRESENTATIONS / EXHIBITIONS
- Dang, Q.V., 2019, December. Reinforcement learning in stock trading. In International conference on computer science, applied mathematics and applications (pp. 311-322). Cham: Springer International Publishing.
- Dang, Q.V., 2020, October. Active learning for intrusion detection systems. In 2020 RIVF International Conference on Computing and Communication Technologies (RIVF) (pp. 1-3). IEEE.
- Dang, Q.V. and Vo, T.H., 2022. Reinforcement learning for the problem of detecting intrusion in a computer system. In Proceedings of Sixth International Congress on Information and Communication Technology: ICICT 2021, London, Volume 2 (pp. 755-762). Springer Singapore.
- Dang, Q.V. and Ignat, C.L., 2016, August. Computational trust model for repeated trust games. In 2016 IEEE Trustcom/BigDataSE/ISPA (pp. 34-41). IEEE.
- Dang, Q.V., 2021. Right to be forgotten in the age of machine learning. In Advances in Digital Science: ICADS 2021 (pp. 403-411). Springer International Publishing.
RESEARCH GRANTS
- Quang-Vinh Dang. (2021)
IUH
Intrusion Detection (1200$) - Quang-Vinh Dang. (2022)
IUH
Intrusion Detection using LLM(1200$)
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