Milad Tatar Mamaghani

Research scientist and engineer working on secure, reliable, and energy-efficient AI-native wireless communication systems in 6G and beyond.

About Me

I’m Milad, originally from Mamaqan, a town near Tabriz in northwestern Iran, and now based in Sydney, Australia. I completed my Ph.D. in Electrical Engineering at Monash University and later worked as a Postdoctoral Research Fellow at the Australian National University.

My work sits at the intersection of wireless communications, signal processing, optimization, machine learning, and applied AI. I have worked on physical-layer security, non-terrestrial networks, integrated sensing and communications, MIMO beamforming, reconfigurable intelligent surfaces, and data-driven resource allocation for beyond-5G and 6G networks. More broadly, I am interested in AI-native systems, data science and analytics, simulation engineering, and software development that turns complex technical ideas into practical, testable, and impactful solutions.

My work has led to 17+ peer-reviewed publications, 600+ citations, two IEEE Best Paper Awards, competitive scholarships, awards, grants, and international recognition for contributions to secure and intelligent wireless technologies. I have also served the research community as a volunteer reviewer, TPC member, and conference session chair for leading international venues. Outside work, I enjoy hiking, swimming, and overthinking my next chess moves.

Education

Monash University
Ph.D. in Engineering
Monash University, Melbourne, Australia · Jan. 2019–Dec. 2022
Amirkabir University of Technology
B.Sc. in Electrical — Communications Engineering
Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran · Sep. 2012–Oct. 2016
Also awarded B.Sc. in Control Engineering with extra course credits (Feb. 2018).

IEEE JSAC Sep 2025
Securing Integrated Sensing and Communication Against a Mobile Adversary: A Stackelberg Game with Deep Reinforcement Learning
Models ISAC security as a Stackelberg game, tackling via a hybrid SCA-DRL optimisation approach; published in the highest-impact communications journal (IF 17.2).
IEEE TWC Jul 2024
Secure Short-Packet Communications via UAV-Enabled Mobile Relaying: Joint Resource Optimization and 3D Trajectory Design
Jointly optimizes UAV 3D trajectory and power usage with low-complexity algorithm for MTC-constrained networks.
IEEE ICC Jun 2024 Best Paper
On the Average Information Leakage of Finite Blocklength Transmissions over Rayleigh Fading Channels
IEEE ICC Best Paper Award — top 0.6% of 2,364 submissions. Introduces average information leakage as a new FBL security metric over fading channels.

All publications →

Core Skills

Programming & Tools
Python MATLAB C/C++ Git/GitHub Docker Linux LaTeX
Scientific Computing & Optimization
NumPy SciPy Pandas Matplotlib CVXPY Simulation
Machine Learning & AI
PyTorch TensorFlow Keras Scikit-learn Deep Reinforcement Learning RLHF Evaluation
Wireless Communications
5G/NR 3GPP IEEE 802.11 MIMO/Beamforming OFDM RF Propagation Link-Budget Analysis
Signal Processing & RF Systems
DSP Spectral Analysis Channel Estimation Detection Theory SDR GNU Radio USRP
Languages
English (Fluent) Persian (Native) Azeri (Native) Turkish (Intermediate)

News

Apr 2026
🚀 Personal website relaunched.

Mar 2026
📚 Our new work submitted to IEEE TCOM.

Oct 2025
📚 Our IoT-J paper featured in IEEE ComSoc Best Readings

Sep 2025
📚 Our paper published in IEEE JSAC

2024
🇦🇺 Received Australian Global Talent.

Jun 2024
🏆 Received Best Paper Award at IEEE ICC 2024.

Sep 2024
🏆 Received Best Paper Award by IEEE ComSoc SPCC Technical Committee.