MoJa Ardestani
Applied ML Researcher
Focused on Deep Learning, NLP, and LLMs, with expertise in RAG and Agentic Systems, delivering scalable, reliable solutions that turn ideas into real-world impact.
About Me
I am an AI researcher and applied scientist working at the intersection of Deep Learning, Natural Language Processing (NLP), and Large Language Models (LLMs). My work bridges academic research and real-world applications, covering structured and unstructured data and addressing challenges in supervised, unsupervised, and retrieval-augmented learning.
I have contributed to architecture design, technical scoping, and ML solution development across academic and industry projects. Beyond hands-on experimentation, I bring experience in cross-functional communication and stakeholder collaboration, with a strong emphasis on ethical deployment—including bias mitigation, factual consistency, explainability, and robustness. These experiences reflect my commitment to building principled AI and creating scalable, trustworthy systems for dynamic environments.
Currently completing my Master of Science in Computing Science at the University of Alberta, I focus on evaluation frameworks for LLM outputs, system design for Retrieval-Augmented Generation (RAG), and strategies for responsible GenAI deployment. I am passionate about advancing interpretable, reliable AI systems that align with human values and drive high-impact applications.
Education
University of Alberta
Edmonton, Canada
M.Sc. in Computing Science
Expected Sept 2025
GPA: 4.0 / 4.0
Coursework
Thesis (In Progress)
"LongRecall: A Structured Evaluation Pipeline for Recall in Generative QA"
Amirkabir University of Technology
Tehran, Iran
B.Sc. in Computer Engineering
Major: Artificial Intelligence
2018 – 2022
GPA: 3.95 / 4.0
Selected Coursework
Thesis
"Design and Implementation of a Content-Based E-book Recommendation System"
Professional Experience
AI Research Planning & Initiation (AIRPI)
Amii, Edmonton, Canada — 2025/7 - Present- Designing searchable knowledge base for RAG systems aligned with business needs
- Evaluating classification methods to improve metadata quality and enable effective cross-format retrieval
- Collaborating cross-functionally with scientists and product managers to define roadmap milestones
- Investigating feedback mechanisms to continuously improve system performance and usability
Client Coaching - Startup Mentorship
Amii, Edmonton, Canada — 2024/12 - 2025/05- Coached the design and refinement of healthcare-related chatbots, ensuring safe and reliable deployment in sensitive domains.
- Advised startups on LLM system design, supporting ideation, architecture, and deployment planning
- Provided mentorship on fine-tuning and RAG, adapting recommendations to client constraints
- Guided ethical LLM deployment, including bias mitigation and output safety in real-world use cases
- Explained ML strategies to both technical and non-technical team members to support informed decisions
Project Validation - Technical Advisement
Amii, Edmonton, Canada — 2024/1 - 2024/4- Advised on designing an LLM-based pipeline for automated report generation using a RAG framework
- Supported evaluation of factual accuracy, addressing hallucination and explainability
- Recommended strategies for embedding fine-tuning to improve domain-specific retrieval
Research & Development Intern
Amirkabir University of Technology, Tehran, Iran — 2021/4 - 2023/5- Developed and deployed an advanced hybrid book recommendation system for Taaghche
- Combined word embeddings with fine-tuned BERT + CNN, boosting recommendation relevance by ~20%
- Used Siamese networks for pairwise similarity scoring, enhancing cold-start and long-tail ranking
- Applied SVR and KNN as fallback models to handle sparse user data, reducing false negatives by ~15%
Research Experience
Research Assistant
University of Alberta, Edmonton, Canada — 2024/2 - Present- Proposed a recall evaluation pipeline for LLM-generated answers in free-form and list-based QA
- Developed a modular system combining fact extraction, candidate selection, and entailment checking
- Applied the pipeline to high-stakes domains such as law and medicine, emphasizing factual completeness
- Achieved up to +40% F1 improvement over lexical baselines and +30% over holistic prompting
Research Intern
AGH University of Science and Technology, Krakow, Poland — 2022/7 - 2023/2- Studied overfitting mitigation in incremental learning via custom adaptation and weighting strategies
- Proposed dynamic backpropagation weights based on inverse cluster size via incremental clustering
- Designed learning schemes tailored to changing data distributions in long-term tasks
- Improved model generalization in evolving data environments through adaptive optimization
Teaching Experience
Teaching Assistant
University of Alberta, Edmonton, Canada — 2023/9 - 2025/4Supporting undergraduate and graduate students in computing science courses, providing guidance on assignments and projects.
- Conducted office hours and tutorial sessions for various computing science courses
- Graded assignments and provided detailed feedback on student work
- Mentored students on research projects and final course projects
- Assisted in developing course materials and practice problems
Machine Learning Instructor
Tehran Institute of Technology, Tehran, Iran — 2021/4 - 2023/5Teaching machine learning concepts and practical applications to students at the Tehran Institute of Technology.
- Designed and delivered comprehensive machine learning curriculum
- Taught fundamental concepts including supervised and unsupervised learning
- Guided students through hands-on projects and practical implementations
- Provided mentorship on machine learning applications and best practices
Teaching Assistant
Amirkabir University of Technology, Tehran, Iran — 2019/9 - 2022/4Supporting undergraduate students in computer engineering and computing science courses.
- Assisted professors in various computer engineering courses
- Conducted laboratory sessions and provided technical support
- Graded assignments and provided constructive feedback
- Helped students understand complex technical concepts
Notable Projects
Enhanced LLMs for knowledge graph construction via prompt-based alignment for factual consistency. Developed an automated evaluation framework for scalable assessment of generated outputs.
Developed a system for generating explanations of SQL queries from natural language questions using Spider and BIRD datasets with LLMs to generate and evaluate SQL queries.
Implemented COVID-19 Detection via Lung X-Ray Classification using DenseNet-121 for efficient transfer learning and feature extraction from medical images.
Skills & Expertise
Core Expertise
Machine Learning & NLP
Infrastructure & Cloud
Programming Languages
Data & Tools
Leadership & Community
Director of External Relations & Partnerships
CSGSA, University of Alberta 2024 - 2025Leading external partnerships and relationship building for the Computing Science Graduate Students' Association.
Director of Competitions & Events Committee
SSC, Amirkabir University of Technology 2020 - 2022Managed and organized academic competitions, hackathons, and technical events for the Student Scientific Chapter.
Director of Scientific Committee
Amirkabir Artificial Intelligence Summit 2020 - 2021Led the scientific committee for one of Iran's premier AI conferences, overseeing research presentations and technical content.