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AI-Driven Wireless + AI + UAV PhD Academic Researcher
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Muhammaduazir69/README.md

I help PhD students, research labs, and industry teams take wireless-networking + AI research from idea to a submission-ready paper in ๐—œ๐—˜๐—˜๐—˜, ๐—˜๐—น๐˜€๐—ฒ๐˜ƒ๐—ถ๐—ฒ๐—ฟ, and ๐— ๐——๐—ฃ๐—œ venues. My specialty is building simulations that are actually reproducible, publishable, and defensible in peer review.

If you're working on ๐Ÿฒ๐—š ๐—ก๐—ผ๐—ป-๐—ง๐—ฒ๐—ฟ๐—ฟ๐—ฒ๐˜€๐˜๐—ฟ๐—ถ๐—ฎ๐—น ๐—ก๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ๐˜€, ๐—ข-๐—ฅ๐—”๐—ก, ๐—ฉ๐Ÿฎ๐—ซ/๐—ฉ๐—”๐—ก๐—˜๐—ง, ๐—œ๐—ผ๐—ง/๐—œ๐—ผ๐— ๐—ง ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†, ๐—ผ๐—ฟ ๐——๐—ฅ๐—Ÿ/๐— ๐—”๐—ฅ๐—Ÿ ๐—ณ๐—ผ๐—ฟ ๐—ฐ๐—ผ๐—บ๐—บ๐˜‚๐—ป๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€, I can build it, debug it, write it up, and ship it.

๐—”๐—ฐ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—ฐ๐—ผ๐—น๐—น๐—ฎ๐—ฏ๐—ผ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€: Northeastern University (Prof. Josep Jornet), University of Luxembourg SIGCOM (Prof. Symeon Chatzinotas, Dr. Eva Lagunas).

๐Ÿ”น ๐—ฅ๐—˜๐—–๐—˜๐—ก๐—ง ๐—ช๐—ข๐—ฅ๐—ž (๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฑ โ€“ ๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ)

๐—ข๐—ฝ๐—ฒ๐—ป-๐˜€๐—ผ๐˜‚๐—ฟ๐—ฐ๐—ฒ ๐˜€๐—ถ๐—บ๐˜‚๐—น๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐˜๐—ผ๐—ผ๐—น๐—ธ๐—ถ๐˜๐˜€ (GitHub: Muhammaduazir69)

โ–ธ ๐—ก๐—ฆ๐Ÿฏ-๐—ก๐—ง๐—ก-๐—ง๐—ผ๐—ผ๐—น๐—ธ๐—ถ๐˜ โ€” end-to-end 6G Non-Terrestrial Network stack for NS-3 โ–ธ ๐—ก๐—ง๐—ก-๐—–๐—›๐—ข-๐—™๐—ฟ๐—ฎ๐—บ๐—ฒ๐˜„๐—ผ๐—ฟ๐—ธ โ€” 3GPP Rel-17/18 Conditional Handover with TTE-aware mechanisms โ–ธ ๐—ข-๐—ฅ๐—”๐—ก ๐—ก๐—ง๐—ก ๐—บ๐—ผ๐—ฑ๐˜‚๐—น๐—ฒ โ€” O-RAN architecture extended to satellite/aerial segments

๐—”๐—ฐ๐˜๐—ถ๐˜ƒ๐—ฒ ๐—ท๐—ผ๐˜‚๐—ฟ๐—ป๐—ฎ๐—น ๐—ฝ๐—ฎ๐—ฝ๐—ฒ๐—ฟ๐˜€

โ–ธ Teleoperation survey for semi-autonomous vehicles โ†’ IEEE Communications Surveys & Tutorials (3-layer framework: Communication / Control / Autonomy-Human Integration) โ–ธ ๐—›-๐— ๐—”๐——๐—ฅ๐—Ÿ ๐—ณ๐—ผ๐—ฟ ๐—ข-๐—ฅ๐—”๐—ก ๐Ÿฏ๐—— ๐˜ƒ๐—ฒ๐—ต๐—ถ๐—ฐ๐˜‚๐—น๐—ฎ๐—ฟ ๐—ป๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ๐˜€ โ€” hierarchical MAPPO / MASAC / Q-learning with AA-DCRA algorithm; OMNeT++ 6.0.3 + Simu5G + Veins/SUMO + PyTorch/LibTorch โ†’ MDPI Sensors โ–ธ ๐—ฃ๐—œ-๐——๐—ฅ๐—Ÿ ๐—ณ๐—ผ๐—ฟ ๐Ÿฑ๐—š ๐—ป๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ-๐˜€๐—น๐—ถ๐—ฐ๐—ฒ ๐—ผ๐—ฟ๐—ฐ๐—ต๐—ฒ๐˜€๐˜๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป for AGV teleoperation โ†’ Elsevier Vehicular Communications โ–ธ ๐——๐—ฃ-๐—œ๐——๐—ฆ-๐—ฉ๐—ก๐——๐—ก โ€” dual-plane IDS for Vehicular NDN โ†’ IEEE TVT / TNSM โ–ธ ๐—š๐—”๐—ง-๐— ๐—”๐—ฃ๐—ฃ๐—ข for Industrial IoT-Edge dynamic scheduling โ†’ Computers & Industrial Engineering

๐—Ÿ๐—ถ๐˜ƒ๐—ฒ ๐˜€๐—ถ๐—ฑ๐—ฒ ๐—ฝ๐—ฟ๐—ผ๐—ท๐—ฒ๐—ฐ๐˜๐˜€

โ–ธ aeroscope.live โ€” public ADS-B flight tracker (React / Vite)

๐Ÿ”น ๐—ฆ๐—œ๐— ๐—จ๐—Ÿ๐—”๐—ง๐—œ๐—ข๐—ก & ๐——๐—˜๐—ฉ๐—˜๐—Ÿ๐—ข๐—ฃ๐— ๐—˜๐—ก๐—ง ๐—ฆ๐—ง๐—”๐—–๐—ž

๐—ก๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ ๐˜€๐—ถ๐—บ๐˜‚๐—น๐—ฎ๐˜๐—ผ๐—ฟ๐˜€ โ–ธ NS-3 + 5G-LENA (NR), NS3-AI, NS3-gym, NS3-ORAN, NetSimulyzer โ–ธ OMNeT++ 6.0.3 + INET, Simu5G, Veins, SUMO, FLoRa, libPTP โ–ธ Mininet / Mininet-WiFi with RYU OpenFlow controller โ–ธ Contiki-NG / Cooja for IoT/IoMT (RPL OF0 & MRHOF, CoAP, OSCORE, EDHOC, MQTT)

๐—”๐—œ / ๐— ๐—Ÿ โ–ธ PyTorch, LibTorch, TensorFlow โ–ธ MARL: MAPPO, MASAC, QMIX, VDN โ–ธ Single-agent DRL: DQN, DDQN, PPO, DDPG, TD3 โ–ธ Libraries: EPyMARL, PantheonRL, custom MARL forks

๐—ฅ๐—ผ๐—ฏ๐—ผ๐˜๐—ถ๐—ฐ๐˜€, ๐—จ๐—”๐—ฉ & ๐˜€๐—ฒ๐—ป๐˜€๐—ถ๐—ป๐—ด โ–ธ NVIDIA Isaac Sim, Omniverse, Gazebo, ROS2, MoveIt โ–ธ Jetson Nano, DeepStream โ–ธ PX4, ArduPilot, MAVLink, QGroundControl (flight-control + mission-planning modifications) โ–ธ mmWave radar, SDR, LiDAR/UART integration

๐—”๐—น๐˜€๐—ผ: CMake, Docker, C++, Python, MATLAB

๐Ÿ”น ๐—ฆ๐—˜๐—ฅ๐—ฉ๐—œ๐—–๐—˜๐—ฆ

  1. ๐—˜๐—ป๐—ฑ-๐˜๐—ผ-๐—ฒ๐—ป๐—ฑ ๐˜„๐—ถ๐—ฟ๐—ฒ๐—น๐—ฒ๐˜€๐˜€ ๐˜€๐—ถ๐—บ๐˜‚๐—น๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ โ€” scenario design โ†’ results โ†’ publication plots
  2. ๐——๐—ฅ๐—Ÿ / ๐— ๐—”๐—ฅ๐—Ÿ ๐—ถ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป into NS-3 or OMNeT++ using NS3-AI, NS3-gym, or custom Python โ†” C++ bridges
  3. ๐—ฃ๐—ฎ๐—ฝ๐—ฒ๐—ฟ ๐—ฟ๐—ฒ๐—ฝ๐—ฟ๐—ผ๐—ฑ๐˜‚๐—ฐ๐˜๐—ถ๐—ผ๐—ป & ๐—ฒ๐˜…๐˜๐—ฒ๐—ป๐˜€๐—ถ๐—ผ๐—ป โ€” rebuild a baseline and extend it for your contribution
  4. ๐—–๐˜‚๐˜€๐˜๐—ผ๐—บ ๐—ฝ๐—ฟ๐—ผ๐˜๐—ผ๐—ฐ๐—ผ๐—น ๐—ฑ๐—ฒ๐˜ƒ๐—ฒ๐—น๐—ผ๐—ฝ๐—บ๐—ฒ๐—ป๐˜ โ€” MAC, routing, handover, slicing, security
  5. ๐—ฅ๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต ๐˜„๐—ฟ๐—ถ๐˜๐—ถ๐—ป๐—ด ๐˜€๐˜‚๐—ฝ๐—ฝ๐—ผ๐—ฟ๐˜ โ€” methodology, results, and discussion sections for Q1 targets
  6. ๐—ฃ๐—ต๐—— ๐˜๐—ต๐—ฒ๐˜€๐—ถ๐˜€ / ๐˜€๐—ถ๐—บ๐˜‚๐—น๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—บ๐—ฒ๐—ป๐˜๐—ผ๐—ฟ๐—ถ๐—ป๐—ด โ€” debugging, validation, defense prep

๐Ÿ”น ๐—ฅ๐—˜๐—ฆ๐—˜๐—”๐—ฅ๐—–๐—› ๐—”๐—ฅ๐—˜๐—”๐—ฆ ๐—œ ๐—ฃ๐—จ๐—•๐—Ÿ๐—œ๐—ฆ๐—› ๐—œ๐—ก

โ–ธ ๐Ÿฒ๐—š & ๐—ฏ๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ: NTN (LEO / HAPS), O-RAN, mmWave / THz, MIMO, beamforming, network slicing, TDD/FDD โ–ธ ๐—ฉ๐Ÿฎ๐—ซ / ๐—ฎ๐˜‚๐˜๐—ผ๐—ป๐—ผ๐—บ๐—ผ๐˜‚๐˜€ ๐˜ƒ๐—ฒ๐—ต๐—ถ๐—ฐ๐—น๐—ฒ๐˜€: Simu5G VANETs, 5G-LENA NR V2V with obstacle detection, VNDN security, AGV teleoperation, digital twins โ–ธ ๐—œ๐—ผ๐—ง / ๐—œ๐—ผ๐— ๐—ง ๐˜€๐—ฒ๐—ฐ๐˜‚๐—ฟ๐—ถ๐˜๐˜†: lightweight crypto in Contiki-NG, HL7-compliant multi-level encryption, sinkhole / DoS / DDoS / ARP spoofing / SYN flood detection with hybrid IDS โ–ธ ๐——๐—ฟ๐—ผ๐—ป๐—ฒ๐˜€ & ๐—ฎ๐—ฒ๐—ฟ๐—ผ๐˜€๐—ฝ๐—ฎ๐—ฐ๐—ฒ: PX4 / ArduPilot, MAVLink, Gazebo UAV scenarios, network-sliced UAV resource allocation โ–ธ ๐—”๐—œ ๐—ณ๐—ผ๐—ฟ ๐—ป๐—ฒ๐˜๐˜„๐—ผ๐—ฟ๐—ธ๐—ถ๐—ป๐—ด: federated learning (Flower + NS-3), digital-twin-enabled MADRL, GAT-based MARL for Industrial IoT

๐Ÿ”น ๐—–๐—ฅ๐—˜๐——๐—˜๐—ก๐—ง๐—œ๐—”๐—Ÿ๐—ฆ

โ–ธ ๐—ข๐—ฅ๐—–๐—œ๐——: 0009-0002-4104-2680 โ–ธ ๐—š๐—ถ๐˜๐—›๐˜‚๐—ฏ: Muhammaduazir69 โ–ธ ๐—ฃ๐˜‚๐—ฏ๐—น๐—ถ๐—ฐ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€: IEEE Access, MDPI Sensors, Elsevier Vehicular Communications โ–ธ ๐—š๐—น๐—ผ๐—ฏ๐—ฎ๐—น ๐—ฐ๐—ผ๐—น๐—น๐—ฎ๐—ฏ๐—ผ๐—ฟ๐—ฎ๐˜๐—ผ๐—ฟ๐˜€: Northeastern University, University of Luxembourg (SIGCOM), and PhD students across 15+ countries

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