Experiences

  • 2020-2025 - Ph.D. UNIVERSITY OF NEW BRUNSWICK, FREDERICTON, NB

    Focus: Machine Learning Algorithm Design and Machine Learning Interpretability

    Recognition: Frank J. and Norah Toole Research Award, Best Presentation at Toole Speaker Symposium

    Authored four publications in high-impact journals focused on the development of deep learning models (GNNs) for predictive analytics, decision-making, and explainable AI, improving model transparency See list of publications on aichemist.ca/expertise.

    2017-2019 - M.Sc. WESTERN UNIVERSITY, LONDON, CANADA

    Focus: Numerical Methods for Quantum Chemistry

    Authored two publications in high-impact journals focused on the development of numerical algorithms for modeling material properties for applications in sustainable material development and energy storage applications. See list of publications on  aichemist.ca/expertise

    2012-2017 - B.Sc. WESTERN UNIVERSITY, LONDON, CANADA

    Recognition: NSERC Undergraduate Research Award, Graduated with Distinction

  • SEP 2020 - JAN 2025

    Lead Data Scientist - UNIVERSITY OF NEW BRUNSWICK, FREDERICTON, NB

    ·         Team Leadership and Mentorship: Led a cross-disciplinary team of 7+ researchers, mentoring junior members and coordinating efforts to develop impactful machine learning driven solutions.

    ·         Machine Learning Development: Designed and deployed deep learning models (CNNs, RNNs, GNNs), integrating NLP pipelines with built-in uncertainty estimation for building model confidence.

    ·         Champion of Explainable AI: Designed explainable AI methods to reveal key trends in the data, fostering model transparency and stakeholder confidence. Explore my portfolio for engaging explanations, compelling visuals, and real-world applications that bring my work to life.

    ·         Data Pipeline Engineering: Engineered scalable ETL pipelines using Python and SQL, optimizing data ingestion, transformation, and deployment for AI-driven solutions. Automated workflows with real-time analytics to improve business intelligence operations and drive strategic insights.

    ·         Data Visualization: Leveraged Power BI and Tableau to design interactive dashboards, supporting evidence-based business strategies.

    SEP 2017 - SEP 2019

    Research Assistant - WESTERN UNIVERSITY, LONDON, ON

    ·         Algorithm Development: Developed innovative numerical algorithms for predicting material properties, contributing to sustainable material development and energy storage applications.

    ·         Cloud Computing Optimization: Optimized cloud-based simulation leveraging high-performance computing to accelerate the analysis of large-scale molecular systems.

    ·         Collaborative Workflow Standardization: Partnered with physicists and chemists to standardize workflows for advanced quantum chemical modeling.

    MAY 2016 - SEP 2016

    Data Science Intern (Nuclear Waste Research) - SURFACE SCIENCE WESTERN, LONDON, ON

    ·         Statistical Analysis: Conducted statistical and predictive modeling on nuclear waste container durability, ensuring long-term environmental safety and compliance.

    ·         Quality Assurance Adherence: Adhered to strict quality assurance protocols mandated by NWMO ensuring high data accuracy and reproducibility in all analyses.

    ·         Predictive Modeling Exploration: Delivered findings to industry stakeholders and explored machine learning models for predictive material degradation, laying groundwork for future research.

    SEP 2015 - SEP 2017

    Production Operator - MAGNA INTERNATIONAL INC., LONDON, ON

    ·         High-Volume Production: Worked in a fast-paced environment to produce daily car seating targets, collaborating with engineers, managers, and other operators.

    ·         Quality Control Expertise: Maintained stringent quality standards detecting minute defects and ensuring they are addressed without halting production.

  • Oct 2023 - Best Presentation at Toole Speaker Symposium for demonstrating outstanding scientific communication skills and engaging audiences during technical explanations

    Awarder: The University of New Brunswick

    May 2020-2024 - Frank J. and Norah Toole Graduate Scholarship for excellent research performance and contributions to the field of machine learning

    Awarder: The University of New Brunswick

    February 2017 - NSERC Undergraduate Research Assistant Award for showing strong young researcher and academic skills

    Awarder: The Natural Sciences and Engineering Research Council of Canada

    May 2018 - Teaching Assistant Training Certificate for learning how to effectively deliver scientific lessons to young audiences

    April 2017 - Chemistry Alumni Award for Graduating with strong academic achievement (3.77 GPA)

    Awarder: Foundation Western by John Newton Moore

  • Publications

    [1] Amer Marwan El-Samman and Stijn De Baerdemacker. “Amide - amine + alcohol = carboxylic acid." Chemical reactions as linear algebraic analogies in graph neural networks.” In: Chemical Science (2025, Under Review) (10.26434/chemrxiv-2024-fmck4)

    [2] Amer Marwan El-Samman, Incé Amina Husain, Mai Huynh, Stefano De Castro, Brooke Morton, and Stijn De Baerdemacker.“Global geometry of chemical graph neural network representations in terms of chemical moieties”. Digital Discovery 3 (2024), p. 544-557

    [3] Amer Marwan El-Samman, Stefano De Castro, Brooke Morton, and Stijn De Baerdemacker. “Transfer Learning Graph Representations of Molecules for pKa, 13C-NMR, and Solubility”. Canadian Journal of Chemistry 102 (2024), p. 275-288

    [4] Amer Marwan El-Samman, Egor Ospadov, and Viktor Staroverov. First Ionization Energy as the Asymptotic Limit of the Average Local Electron Energy. Journal of Chemical Theory and Computation 16 (2020), p. 6886-6893

    [5] Amer Marwan El-Samman, and Viktor Staroverov. Asymptotic behavior of the average local ionization energy in finite basis sets. The Journal of Chemical Physics 153, 134109 (2020)

    [6] Amer Marwan El-Samman and Stijn De Baerdemacker. “A Global Explanation of Graph Neural Network Models of Chemistry: Applications in Molecular Modelling.” In: Preparation (2025)


    Conference Presentations

    July 2022 - Interpretability and Explainability of Neural Network Chemistry Conference Presentation

    World Association of Theoretical and Computational Chemistry 2022

    University of Bristish Columbia

    June 2022 - Neural Network Chemistry and Need for its Explainability Conference Presentation

    Atlantic Association of Research in Mathematical Sciences (AARMS) 2022

    Memorial University of Newfoundland

    August 2021 - Interpretability of Deep Learning Chemistry Virtual Conference Presentation

    The 104th Canadian Chemistry Conference and Exhibition (CCCE) 2021

    Virtual Conference

    July 2018 -Ionization potentials from ab initio ground-state wave functions Conference Presentation

    The 28th Canadian Symposium on Theoretical and Computational Chemistry (CSTCC)

    University of Windsor

    November 2018 - The Limit of the Average Local Electron Energy Conference Presentation

    The 33rd Symposium of Chemical Physics

    University of Waterloo

  • 2021-Present President and Founder of SciClubUNB

    Leading a community of science enthusiasts, revolved around scientific collaboration and communication. Gives monthly opportunities for professors and students of UNB to present and discuss their favorite research topics

    Connects researchers from various disciplines in one all-encompassing interdisciplinary community where creative problem solving and exchange of ideas are encouraged

    2017-2019 Chemistry Outreach Event Planner and Organizer

    An event organizer for community outreach events lead by Western University’s chemistry department. Often performed engaging presentation to wide audiences (of all ages and backgrounds)

    Loves to strum on the guitar, take photos of nature, write poetry (@alovesmpoetry), and explore science and technology topics during free time