CV

Education

• Ph.D in Computer Science, Texas A&M University Corpus Christi, 2022 - present
• M.S. in Software Engineering, University of Malaya, Kuala Lumpur, Malaysia, 2013
• B.S. in Computer Engineering

PROFESSIONAL SUMMARY

• Machine Learning Engeering RA, Texas A&M University, Corpus Christi, Aug 2022 – Now:
  • Design and implement RL and LLM frameworks.
  • Built Graph Neural Network (GNN) and Transformer-based models for multi-modal spatio-temporal Network traffic forecasting.
  • Developed LLM-powered frameworks for generating textual descriptions from visual scenes (Vision-to-Text transformation)
  • Integrated Retrieval-Augmented Generation (RAG) and Mixture of Experts (MoE) models into real-time AI systems.
  • Engineered time-series features and designed experiments to improve geospatial forecasting accuracy.
  • Implemented feedback-driven RL for optimizing privacy-preserving visual systems.
  • Conducted hyperparameter tuning and model evaluation using cross-validation, AUC, F1-score, and MAE.
  • Built CI/CD pipelines for workflows including data ingestion, model training, evaluation, and deployment.
  • Deployed ML models using Docker, AWS Lambda, and Amazon SageMaker for scalable cloud inference.
• Data Scientist, Dade Pooyan Co, Tehran, Iran, Jun 2016 – Jun 2022:
  • Developed and deployed fraud detection models using XGBoost, LightGBM, and deep neural networks.
  • Performed data preprocessing, feature engineering, and feature selection on large-scale financial transaction datasets.
  • Implemented imbalanced data handling techniques such as SMOTE, under-sampling, and class weighting.
  • Conducted exploratory data analysis (EDA) using Python libraries like Pandas, NumPy, Seaborn, and Matplotlib to identify data patterns and insights.
  • Built and maintained real-time analytics dashboards using Power BI to monitor key fraud metrics and system alerts.
  • Designed and executed A/B tests and statistical analyses to evaluate model improvements and business impact.
  • Wrote technical documentation and reports for model decisions and presented results to stakeholders and executive teams.
  • Built and managed data pipelines using SQL and Microsoft SSIS
• Business Analyst and Data Analytics, University of Applied Sciences, Tehran, Iran, Feb 2014 – Jun 2016:
  • Conducted research in graph-based anomaly detection and pattern recognition in online social networks.
  • Designed and taught university-level courses in Artificial Intelligence, Data Structures, Algorithms, and Software Engineering.
  • Performed data analysis using Python and R to extract meaningful insights from social network datasets.
  • Analyzed large datasets to discover behavioral anomalies and community structures in networks.
  • Created visual reports and dashboards to present research findings and academic assessments.
  • Conducted stakeholder interviews to elicit business and technical requirements
  • Analyzed and documented functional and non-functional requirements
  • Created use cases, user stories, and process flow diagrams
  • Translated business needs into technical specifications for development teams
  • Conducted stakeholder meetings and status updates to gather feedback and align goals
  • Worked closely with Product Owners and Scrum Masters to ensure alignment on deliverables

Skills

• Programming & ML Frameworks:
  • Python, C++, C#, R
  • PyTorch, TensorFlow, Scikit-learn, OpenCV, Hugging Face etc.
• AI/ML Techniques:
  • Reinforcement Learning (PPO, DQN, etc.)
  • Vision-Language Models (CLIP, BLIP, ViLT)
  • Generative AI & Large Language Models (LLMs, RAG, MoE)
  • Time-Series Forecasting (LSTM, Transformers, GNN)
  • Data Mining & Feature Engineering
• Cloud & Big Data Tools:
  • AWS (S3, Lambda, EC2), Google Cloud, Amazon Bedrock, Amazon Sagemaker
  • Docker, Kubernetes, Apache Spark
  • SQL, NoSQL, GraphDB
• Visualization & Analytics:
  • Microsoft Power BI, Matplotlib, Seaborn

CERTIFICATIONS & ACTIVITIES

• GenAI Pinnacle Program (2024, Analytics Vidhya)
• Reinforcement Learning (2024, Stanford Online Course)
• NVIDIA GPU Programming Workshop (2023, Three-Day Workshop)
• Microsoft Power BI Certification
• Advanced Deep Learning Implementation
• Big Data & Hadoop Ecosystem

AWARDS & HONORS

• Best Researcher Award (2020)
• Top Lecturer Award (2016)
• Scholar Achievement in Graduate Education (SAGE) Fellowship (2023, 2024)
• Member of The University ACM Programming Team