Hi there 👋
I'm H M Quamran Hasan
Theoretically, a .
In practice, an inquisitive and self-motivated researcher with a sharp focus on solving real-world problems leveraging artificial intelligence and data.
About
I am a Master's graduate in Computer Science from the University of Alberta, with a background in Computer Science and Business Technology Management from KAIST.
My interests lie in NLP, explainable AI, and trustworthy large language model applications for clinical and legal reasoning.
I also work as an AI Enablement Analyst at Servus Credit Union, where I develop AI agents, build applied AI/ML solutions, and support AI adoption across the organization.
Education
Alberta, Canada
Degree: MSc. Computer Science
Relevant Coursework
- Introduction to Natural Language Processing
- Machine Learning Essentials
- Foundations of Trustworthy Machine Learning
Daejeon, South Korea
Degree: BSc. Computer Science, Double Major in Business Technology Management, Semi Minor in Artificial Intelligence
Relevant Coursework
- Introduction to Natural Language Processing
- Introduction to Data Science
- Data Science Methodology
- Introduction to Artificial Intelligence
- Data Structures
- Introduction to Algorithms
- Probability and Statistics
- Principles of Marketing
- Marketing Research
Experience
Servus Credit Union
Aug 2025 - Present | Edmonton, Canada
AI Enablement Analyst
- Development and monitoring of agents with 1000+ weekly active users.
- Improving AI enablement through support and development of AI use cases across the organization.
UofA xAI Lab
Sep 2024 - Aug 2026 | Edmonton, Canada
Research Assistant
- Working on the integration of large language models in the fields of explainable medical and legal AI.
- Supervised by Dr. Randy Goebel and Dr. Mi-Young Kim
AMII
Dec 2024 - Apr 2025 | Edmonton, Canada
Work-Integrated Learning Opportunity
- Built case studies for 5 startups on using Transformers for Ectopic Beat Detection, Differential Privacy with LLMs, and agentic AI.
- Collaborated with AMII Scientists to provide technical coaching to startups in integrating ML techniques into their service.
Molpax Bio
Feb 2024 - June 2024 | Daejeon, South Korea
Artificial Intelligence Researcher
- Developed and deployed a novel metric and a model with a precision of 0.83 for cell structure detection for qualitative and quantitative evaluation of NASH.
- Achieved an FID score of 12.97 and precision of 0.77 after developing a GAN model to generate lung tissue Whole Slide Images.
- Tools: Python, OpenCV, PyTorch, Tensorflow, NumPy
KAIST Data Mining Lab
July 2023 - Dec 2023 | Daejeon, South Korea
Research Intern
- Contributed to the DB4DL project, focusing on enhancing distributed training efficiency for Transformers.
- Conducted research under the Undergraduate Research Program on models such as BERT and T5 to identify optimal parallelism strategies.
- Tools: Python, Numpy, Pytorch
KAIST Users & Information Lab
Mar 2023 - Dec 2023 | Daejeon, South Korea
Research Intern
- Benchmarked LLMs' accuracy for reasoning tasks in Bengali by 20% through back translation and CoT reasoning.
- Tools: Python, Seaborn, Transformers
Sicpama
Nov 2022 - Feb 2023 | Seoul, South Korea
Data Scientist
- Led the UX/UI team to optimize service UI based on user behavior analysis using Hotjar and Google Analytics.
- Designed and implemented a streamlined data collection strategy using Google Tag Manager.
- Achieved a 90% reduction in data collection time by automating POS data collection.
- Improved sales by developing a recommendation system from the ground up.
- Tools: Python, Pandas, Numpy, Scikit-Learn, Seaborn, Selenium, Hotjar, Google Analytics, Google Tag Manager, Google BigQuery, Tableau, MySQL
Kooky
Jan 2022 - Aug 2022 | Seoul, South Korea
Data Analyst
- Achieved a 150% increase in users by identifying potential markets and improving market-wise user experience.
- Achieved an 80% increase in user engagement, by leading the content team based on user behavior analysis.
- Led data collection, storage, and extraction for insights.
- Guided data-driven go-to-market and artist selection through user location and behavior analysis.
- Tools: Python, Pandas, Numpy, Scikit-Learn, Seaborn, Google Analytics, Google Tag Manager, Google BigQuery, Tableau, MySQL
Skills
Programming Languages
Frameworks & Tools
Cloud & Data
Publications
Projects
Trashinator
A minimalistic and affordable AI-based trash sorter based on SAP Technologies.
Accomplishments
- Tools: SAP Analytics Cloud, Arduino, AWS, SAP Hana Database, SAP AppGyver
- Led the data collection and analysis using SAP services like Hana Cloud and SAP Analytics Cloud.
- Demoed the project to the senior executives of SAP Korea.
- Team ranked 1st out of 5 teams.
Detecting Fake Import Declarations
Using machine learning techniques to identify fake import declarations.
Accomplishments
- Tools: Python, Scikit-Learn, Pandas, Machine Learning
- Achieved a 91.12% accuracy in detecting fake import declarations.
- Earned 10th position out of 82 participants.