teaching & supervision

Teaching

1. Polytech Paris-Saclay, Paris-Saclay University (associate professor, 2023-now)
   • Programmation orientée objet (POO) (cycle d’ingénieur): Fall 2025
   • Objets connectés (cycle d’ingénieur): Fall 2025
   • Robotique (cycle d’ingénieur): Fall 2025
2. Hanoi University of Science and Technology (lecturer, 2023-2025)
   • Virtual Reality (AC4010, undergraduate): Fall 2023, Fall 2024
   • Augmented Reality (AC4020, undergraduate): Fall 2023, Fall 2024
   • Fundamentals of Data Communication (ET4070, undergraduate): Summer 2024
   • Multimedia Data Compression and Coding (ET4262E, undergraduate): Spring 2024
3. Troy University (invited lecturer, 2023-present)
   • Computer Security (CS4451, undergraduate): Spring 2024
   • Foundations of Computer Science (CS3310, undergraduate): Fall 2023
4. Paris-Saclay University (teaching assistant, 2020-2022)
   • Communication Numérique (G10, graduate): Fall 2020
   • Joint Research Project (MN915/MN916, graduate, joint program with Institut Polytechnique de Paris): Fall 2020, Fall 2021

Supervisions

Ph.D students

1. Thanh Pham (HUST, 2024–2028, co-advised with Prof. Trung-Kien Dao)
   Topic: Fault-tolerant algorithm for distributed mutual exclusion (mutex)
2. Tuan-Vu Truong (VinUniversity, 2023–2027, co-advised with Prof. Van-Dinh Nguyen)
   Topic: Resouce allocation for network slicing in open radio access network (Open RAN)
3. Minh-Tuong Nguyen (VinUniversity, 2023–2027, co-advised with Prof. Van-Dinh Nguyen)
   Topic: Resource allocation for serverless functions in mobile edge cloud environments

Master’s Students

1. Kim-Hoan Do, (HUST, 2024-2026)
   Topic: Resource allocation for Open RAN slicing
2. Quang-Lap Luu (HUST, 2023-2025)
   Topic: Machine learning for typhoon formation prediction

Alumni

1. Tuan-Anh Do (HUST, 12/2023-04/2024), now at Viettel High Technology (VHT)

Resources

Networking

• L. Peterson, O. Sunay, and B. Davie, Private 5G: A Systems Approach, 2022.
• L. Daniel and K. Narayanan, Mathematical Modelling for Computer Networks, Univ. of Helsinki.
• O. Brun, Modèles et algorithmes pour l’ingéniérie de trafic, INSA Toulouse.
• O. Brun, Modèles & Algorithmes pour la Planification des Réseaux, INSA Toulouse.
• Z. Han, Game Theory in Wireless and Communication Networks: Theory, Models, and Applications, Univ. of Houston.
• E. Altman, Selected Topics in Telecoms and Queueing Networks, Inria Sophia Antipolis.

Optimization & Maths

• Z. Han, Selective Topics on Optimization, Univ. of Houston.
• S. Boyd and L. Vandenberghe, Convex Optimization, Stanford University.
• S. Boyd and L. Vandenberghe, Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares, Stanford University.
• L. El Ghaoui, Hyper-Textbook: Optimization Models and Applications, UC Berkeley, 2021.

ML/AI

• S. Amidi, Artificial Intelligence (CS221), Machine Learning (CS229), Deep Learning (CS230), Stanford University.
• A. Smola and M. Li, Introduction to Deep Learning (STAT157), UC Berkeley.
• S. Lall and S. Boyd, Introduction to Machine Learning (EE104), Stanford University.
• E. Brunskill, Reinforcement Learning (CS234), Stanford University.
• Yuki Asano et al., Deep Learning Course, M.Sc in Artificial Intelligence, Univ. of Amsterdam.