Education

• Ph.D in Artificial Intelligence - Shahid Beheshti University  (Enrolled in 2022)
• M.Sc  in Artificial Intelligence - Shahid Beheshti University (2017-2020)
• B.Sc. in Computer Science -   Shahid Beheshti University (2012-2016)
  

 Skills

• Programming & Frameworks
• Python, MATLAB,C++
• Django, FastAPI,Docker
• Git, Jira
• SQL Server
• AI / ML Skills
• Classical  Machine learning
• Neural Network
• Deep Learning (CNNs, GANs, Transformers)
• Computer Vision
• Signal Processing & Audio Processing
• NLP (NER, Sentiment, Topic Modeling, Chatbots, RAG, LLM Fine-Tuning)
• Data Science
• Data Cleaning & Pre-processing
• Feature Engineering and Exploratory Data Analysis (EDA)
• Statistical Modeling and KPI analytics
• Databases
• SQL Server
• MySQL
• Big Data Ecosystem
• Kafka, Redis, Hadoop
• Elasticsearch, Kibana
• KPI design & BI dashboards
• Product management (Agile, Scrum)

 Examples of completed projects

• Computer Vision
  Developed large-scale pipelines for object detection, facial analytics, and real-time video intelligence using CNN–Transformer and multimodal representation learning.
  Built clinical-grade diagnostic models for fetal imaging, Parkinson’s detection, ECG arrhythmia classification, and breast cancer analysis.
• Data Science & Product Analytics
  Developed enterprise-level KPI dashboards, automated analytics platforms, and large-scale data processing workflows.
  Wrote advanced SQL queries for data extraction, transformation
• Natural Language Processing, LLMs & MLLMs
  Developed domain-specific conversational agents, psycholinguistic text assessment models, and specialized NLP pipelines.
  Implemented semantic retrieval engines and end-to-end RAG architectures using large and multimodal language models.
  Recommender Systems
  Designed hybrid recommendation engines leveraging collaborative filtering, content-based modeling, and embedding-based similarity ranking.
• Edge AI & Distributed Inference
  Optimized deep learning models for edge deployment using quantization, distillation, and model compression.
  Applied teacher–student learning methods to improve performance on constrained devices.
• Signal & Audio Intelligence
  Designed advanced speech-processing systems (STT/TTS, multi-speaker) and deep-learning-based noise suppression frameworks.
  Built temporal biomedical signal-analysis models, including ECG anomaly detection.