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Tahernezhad/README.md

Farajollah (Fred) Tahernezhad-Javazm, PhD

AI/ML researcher and engineer applying deep learning, reinforcement learning, and optimization to real-world problems.

Currently a Postdoctoral Researcher specializing in graph neural networks, neuroevolution, and multi-objective optimization, with a strong engineering background in building end-to-end ML systems.

  • Core expertise: deep & reinforcement learning · graph neural networks · time-series analysis · multi/many-objective optimization · LLM engineering
  • Reach me: tahernezhad.jv@gmail.com

LinkedIn ORCID Email

Featured projects

Languages and tools

My Skills

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  1. Cartesian-Genetic-Programming-for-Truss-Optimization Cartesian-Genetic-Programming-for-Truss-Optimization Public

    Cartesian Genetic Programming for 2D truss topology optimization.

    Python

  2. Deep-Q-Learning-Stock-Trading Deep-Q-Learning-Stock-Trading Public

    DQN stock-trading agent with a custom Gymnasium environment and yfinance data.

    Python 4

  3. Neuroevolution-Graph-Neural-Network Neuroevolution-Graph-Neural-Network Public

    A neuroevolutionary framework for structural optimization that trains Graph Neural Networks (GNNs) with a genetic algorithm.

    Python 2

  4. UK-Regional-Insights UK-Regional-Insights Public

    A geospatial data analytics project analyzing 26 years of UK economic (GVA) and deprivation (IMD) data. Features an ETL pipeline, spatial statistics, and interactive visualizations.

    Jupyter Notebook

  5. My-LLM-Learning-Journey My-LLM-Learning-Journey Public

    My practical portfolio of LLM engineering projects.

    Python

  6. Continuous-Control-Workbench Continuous-Control-Workbench Public

    A clean PyTorch implementation of PPO, SAC, and TD3 made from scratch. It is built for testing and comparing continuous control RL algorithms on complex environments such as BipedalWalker-v3.

    Python