Ryan C.
Research Scientist – Organic Chemistry
Experience
Research Scientist – Organic Chemistry
Columbia University, Department of Chemistry and Chemical Biology
- Conducted research on reaction mechanisms, stereochemistry, and retrosynthesis strategies.
- Applied high-temperature and pressure-dependent reaction modeling in carbon conversion systems.
- Integrated advanced spectroscopy and analytical chemistry in the study of catalyst-driven reactions.
- Co-authored publications focusing on structured chemical reasoning and model-based reaction analysis.
Chemistry Reasoning and Assessment Consultant
Independent Contractor
- Designed high-complexity chemistry problems aimed at evaluating conceptual understanding and abstract reasoning across topics such as chemical thermodynamics, equilibrium, and reactor design.
- Worked with academic platforms and AI startups to simulate PhD-level chemistry exams and scenarios mimicking real-world industrial conditions.
- Evaluated AI-generated solutions for problems involving gas-phase reactions, energy balances, and pressure-dependent kinetics; provided detailed written assessments of logical consistency and scientific validity.
- Applied expert judgment to assess how effectively language models interpret problem constraints, derive relevant rate laws, and sequence multistep calculations.
- Contributed to benchmarks assessing LLMs’ chemistry reasoning by tagging solution steps, classifying errors, and recommending clarity improvements.
Chemistry Lecturer and Problem Developer
Online
- Designed undergraduate and graduate-level chemistry questions for exams and problem sets with a focus on analytical reasoning.
- Developed and assessed problems related to reaction engineering, thermodynamics, and chemical kinetics under varying reactor conditions.
- Led classes on deriving rate expressions, calculating equilibrium concentrations at elevated temperatures, and evaluating reactor outputs.
- Fostered structured problem-solving through real-world-inspired assignments requiring logical deduction and multi-variable reasoning.
AI Model Trainer – Chemistry
TELUS International
- Created and reviewed chemistry problems involving complex reaction mechanisms, equilibrium, kinetics, and spectroscopy.
- Analyzed AI-generated responses for logical soundness, chemical accuracy, and step-by-step reasoning.
- Identified knowledge gaps in large language models and proposed refinements to improve chemistry-specific logic and depth.
- Developed rate laws and reactor models for gas-phase and packed-bed reactions, assessing model understanding of reaction engineering.
- Collaborated cross-functionally with developers to provide structured feedback on model interpretation of multi-step problem-solving.
Summary
Ph.D.-level Chemistry researcher with extensive expertise in organic chemistry, physical chemistry, analytical methods, and problem-based learning. Experienced in AI model evaluation and chemistry question development to test deep reasoning, critical thinking, and structured problem-solving. Proven ability to assess AI-generated solutions for logic, completeness, and accuracy. Passionate about using domain knowledge to bridge scientific expertise with cutting-edge AI research.
Languages
English
ElementaryEducation
University of Cambridge
Ph.D. · Organic Chemistry · United Kingdom
University of Maryland
M.Sc. · Chemistry · United States
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