About
Senior Data Scientist with over 6 years of experience specializing in statistical modeling, mathematical modeling, predictive modeling, deep learning modeling, machine learning, quantitative methods, computer vision, natural language processing, and agentic AI.
Work Experience
Senior Data Scientist
Beacon Hill, 11/2025 - Present
- Investigated multi-agent agentic AI systems specifically designed to manage complex processes in civil litigation.
- Conducted statistical evaluation of retrieval-augmented generation (RAG) models for entity identification and claim analysis in legal civil cases.
- Synthesized empirical results through rigorous statistical analysis into comprehensive technical documentation to communicate novel research findings to internal teams.
- Collaborated with legal and technical stakeholders to ensure AI system alignment with litigation requirements and compliance standards.
Data Scientist
Danta Technologies, 04/2025 - 10/2025
- Devised and executed a proof-of-concept initiative on multi-agent agentic AI systems, driving enhanced personalization and customer support solutions.
- Established a RAG model for a major telecom client, resulting in reduced support resolution time.
Senior Machine Learning Engineer
Michaels Stores, 04/2022 - 01/2025
- Carried out proof-of-concept initiatives to enhance visual search, search systems, recommendation engines, and content moderation.
- Researched, designed, developed, optimized, and tested quantitative methodologies, statistical models, predictive models, machine learning models (including linear regression, logistic regression, decision trees, random forests, clustering), deep learning models (CNNs, and transformers) to improve visual search, visual recommender, and learning to rank.
- Utilized transformer-based small and large language models (including BERT, RoBERTa, DeBERTa, SBERT, MiniLM, FLAN-T5, GPT-2, and GPT-4) to improve text classification, sentiment analysis, query understanding, and product tagging.
- Performed ad hoc quantitative analysis and conducted exploratory data analysis (EDA) to identify patterns, trends, and anomalies for model development and feature engineering; Conducted model performance analysis, quantified model limitations, provided comprehensive interpretations, explanations, and conclusions.
- Created and maintained technical documentation for modeling (including project plans, model descriptions, mathematical derivations, data analyses, processes, and quality controls) and delivered technical presentations and reports to both technical and non-technical audiences, explaining model performance and key findings.
Research Associate
University of Colorado Colorado Springs, 02/2020 - 04/2022
- Formalized the science of artificial intelligence for open-world novelty; Devised unsupervised novelty characterization and adaptation for open-world deep learning classifiers; Investigated novel approaches integrating statistical extreme value theory to enhance machine learning models.
- Boosted performance of open-world image classifiers, change-point detection, and computer vision triplet tasks, primarily by strategically utilizing statistical extreme value theory and through the training and fine-tuning of deep learning models, including Convolutional Neural Networks (CNNs) and Transformers via both supervised and unsupervised learning.
Education
| University | Degree | Duration |
|---|---|---|
| The University of Texas at Dallas | PhD in Electrical Engineering | May 2016 - Dec 2019 |
| University of California, Riverside | Master of Science in Electrical Engineering | Sep. 2015 - Sep. 2015 |
| University of Tehran | Master of Science in Mechatronics Engineering | Sep. 2011 - Feb. 2014 |
| Shahrood University of Technology | Bachelor of Science in Robotics Engineering | Sep. 2006 - July 2011 |
Skill
- Machine Learning: Deep Learning, Unsupervised Learning, Supervised Learning, Incremental Learning, Clustering
- Data Science: Research, Analytics, Exploratory Data Analysis, Quantitative Analysis, Data Visualization, Optimization
- Statistics: Statistical Modeling, Pattern Recognition, Regression, Classification, Hypothesis Testing, A/B Testing, Model Validation
- Computer Vision: Image Classification, Object Detection, Image Segmentation, Object Tracking, Image Processing
- Artificial Intelligence: Agentic AI, Generative AI, Discriminative AI, Natural Language Understanding (NLU), NLP, LLM, RAG
- Programming:Python (Pytorch, Keras, TensorFlow, OpenCV, Scipy, Numpy, Scikit, Langgraph), SQL, NoSQL, Git, MATLAB