M.Sc. Computer Engineering researcher specializing in NLP and deep sequence modeling, combined with university-level lecturing experience in
Artificial Intelligence and Operating Systems. Proficient in PyTorch, Hugging Face, and probabilistic graphical models, with a strong dual background in
machine learning research and academic instruction.
GPA: 3.29/4
Thesis: Persian Spell Checker Development Using Language Models (Evaluated as Excellent)
Core Coursework: Natural Language Processing, Deep Learning, Pattern Recognition, Statistical Machine Learning.
GPA: 3.14
Thesis: Applying Data Mining in Sales Prediction. (Score: 4/4)
Core Coursework: Artificial Intelligence, Data Science, Database Systems, Algorithms and Data Structures, Computer Networks.
GPA: 4/4
My research interests lie at the intersection of Natural Language Processing, sequence-to-sequence modeling, and deep learning reliability. Specifically, I am focused on the empirical evaluation and fine-tuning of pre-trained language models (including Transformers, BERT, and T5 architectures) for low-resource languages, leveraging parameter-efficient fine-tuning (PEFT/LoRA) and context-aware decoding methodologies.
Beyond sequence architectures, I seek to explore how structural generalization and Bayesian frameworks can be integrated within probabilistic graphical models to characterize uncertainty in unstructured datasets, ultimately aiming to enhance the robustness, cross-domain transferability, and evaluation standards of deep representation models under data-constrained regimes.
Gathered client requirements to build data pipelines, backend automation scripts, and custom data processing tools using Python, MySQL, and Flask.
Instructed foundational undergraduate courses in Artificial Intelligence and Operating Systems.
Prepared syllabi, designed comprehensive written/programming exams, and structured practical lab tasks focusing on state-space search algorithms, process synchronization, and memory-management schemes.
Managed system configurations, resolved networking bottlenecks, and managed hardware/software deployments.
Engineered a database-backed dynamic online assessment testing framework using PHP, structural JavaScript, and MySQL to streamline academic examination routines.