AI Engineer · Computer Vision · NLP & LLMs
Ph.D. applicant in Natural Language Processing & Machine Learning. Building domain-specific LLMs, generative vision systems, and reproducible AI research.
About Me
I am an AI engineer and researcher with a focus on natural language processing, machine learning, computer vision, and large language models. My work spans domain-specific LLM development—including supervised fine-tuning, LoRA/QLoRA, preference alignment, RAG pipelines, and agent systems—as well as generative vision models for real-world deployment.
Based in Tehran, Iran, I lead applied R&D across industry collaborations while teaching machine learning and mentoring students on deep learning and LLM research. I am seeking industry roles and Ph.D. opportunities at the intersection of NLP, multimodal learning, and efficient model training.
Research Interests
SFT, LoRA/QLoRA, alignment (DPO, GRPO), RAG, and agent workflows for domain-specific language models.
Diffusion pipelines, facial analysis, multi-modal feature learning, and production vision systems.
Multi-GPU training (FSDP/DeepSpeed), quantization (AWQ/GGUF), vLLM, TensorRT-LLM, and Dockerized serving.
Open curricula, university teaching, and research mentorship in ML, deep learning, and LLMs.
Industry Experience
Makan System
Resana — Tehran, Iran
AIHomeDesign — Remote
Baharan Company — Tehran, Iran
Freelance / Contract Roles — Iran
Education
Artificial Intelligence Focus
Tarbiat Modares University, Tehran, Iran
Thesis: Designing a Fashion Recommendation System using Deep Learning — multi-modal pipeline fusing visual and textual product features.
Advisor: Prof. Gholam Ali Montazer
Islamic Azad University, Isfahan, Iran
Thesis: Implementation of a Pyramid Security System with Firewall
Research & Publications
Pourmirzaei, M., Montazer, G.A., Mousavi, E. ATTENDEE: an AffecTive Tutoring system based on facial EmotioN recognition and heaD posE Estimation to personalize e-learning environment.
Journal of Computers in Education, 12: 65–92. doi:10.1007/s40692-023-00303-w
Beygi, M., Fallahi, M., Vali, R., Mousavi, E., Saberian, M., Li, J., Barari, A. FELA-DNN framework to predict the seismic bearing capacity of skirted strip footing built on a non-cohesive slope.
Soil Dynamics and Earthquake Engineering, 171: 107932. doi:10.1016/j.soildyn.2023.107932
Amiri, M., Montazer, G.A., Mousavi, E. Educational Customization by Homogenous Grouping of e-Learners based on their Learning Styles.
arXiv:2408.12619
Pourmirzaei, M., Montazer, G.A., Esmaili, F., Mousavi, E., Karamizadeh, S. How Self-Supervised Learning Can be Used for Fine-Grained Head Pose Estimation?
arXiv:2108.04893
ProtBERT-NER: Transformer-based sequence labeling for post-translational modification sites in cancer-associated proteins. Manuscript in preparation from Ph.D. thesis supervision of Sima Abolhassani Khajeh.
Contribution: Thesis supervision and ML/DL/LLM instruction; major ProtBERT implementation, training pipelines, and benchmarking.
Full list on Google Scholar.
Teaching & Mentoring
Tarbiat Modares University — Tehran
Taught machine learning for master’s and Ph.D. students over five semesters under Prof. Gholam Ali Montazer. Course materials maintained in an open-source repository.
Freelance, Remote
Developed instructional materials on ML, deep learning, GenAI, LLMs, and PyTorch; authored 100+ tutorials with 120,000+ cumulative views on Medium.
Open-source curriculum
Open-source curriculum developer for GenAI, LLMs, and AI agents.
Ph.D. student, Islamic Azad University, Qeshm International Branch. Supervised thesis on protein language models and PTM site prediction (ProtBERT-NER); mentored through ML, DL, and LLM coursework.
Computer science student, Dalhousie University, Canada. Mentored on M.Sc. thesis research on code-understanding language models, including model design, training workflows, and scholarly writing.
Remote, independent ML/DL/GenAI mentorship through structured programs on project design, experimentation, and reproducible model development.
Selected Projects
Open-source curriculum · TMU
Comprehensive ML course for master’s and Ph.D. students covering supervised and unsupervised learning with practical Python applications.
Tutorial series · GenAI deployments
Comprehensive tutorial series on generative AI, LLMs, and AI agent deployments.
From-scratch LLM implementation
From-scratch LLM implementation emphasizing training efficiency and text generation fundamentals.
PyTorch · Computer vision
Deep learning pipeline for predicting human age from facial images.
Skills & Tools
Core Technologies
Languages
English
Advanced (IELTS 6.5; Duolingo 110)
Turkish
Intermediate
Persian
Native