Thomas Harrelson Email & Phone Number

- First ML engineer- Lots of 0 -> 1 stuff

Led Cross-Functional Development Team: Managed a team of six software developers, focusing on high-velocity operations. Responsibilities included stakeholder management for business-critical product prioritization, development scope planning, blocker identification and resolution, and conducting retrospectives for continuous process improvement.AI Project Leadership: Spearheaded multiple artificial intelligence initiatives, demonstrating expertise in AI applications and project management.Generative AI Application Development: Engineered chain-of-thought agent using Langchain to generate valid cloud lab code to run experiments at scale from natural language.ML/AI Model Development: Designed models to accurately predict experimental outcomes, such as liquid transfer failures and HPLC chromatograms.ML/AI Pipeline Development: Developed ETL pipelines for large scale deep learning model training using Metaflow, Sagemaker, Pytorch, and Torchserve.Backend Web Development Expertise: Developed a robust backend web framework using Python, optimized for AI-based scientific query resolution. Deployed on AWS EC2 using Kubernetes, enhancing system scalability and reliability.Go-Based Web Endpoint Design: Conceptualized and implemented a Go-written web endpoint for remote experiment execution and data analysis, deployed on AWS EC2 with Kubernetes integration.Python SDK Development for Experimentation: Created a Python SDK for streamlined experiment functions, interfacing with the above server infrastructure.Proteomics Web Service Creation: Built a Python-based proteomics web service on AWS EC2 with Kubernetes, simulating mass spectrometry fragmentation patterns for scientific experiments.Bio-Security and Safety Code Implementation: Developed safety and bio-security assessment functionality for DNA, RNA, and protein synthesis.

Utilized DFT and machine learning to design materials for detecting dark matter, correlating structural characteristics with magnetic impurities in superconducting qubits.

As a Graduate Student Researcher, I specialized in computational analysis and predictive modeling within the field of organic semiconductors. My research was pivotal in understanding the structure-function relationships of these materials, leveraging advanced computational methodologies validated through neutron scattering experiments.Key Contributions and Skills:Organic Semiconductor Research: Focused on carbon-based materials known for their excellent optical and electrical properties, akin to flexible plastics. Notably contributed to the development of organic electronics like OLEDs, commonly used in smartphone screens and high-end TVs.Computational Methodologies Expertise: Utilized an array of computational tools such as Molecular Dynamics (MD), Density Functional Theory (DFT), and Model Hamiltonian approaches, adapting techniques based on material types (amorphous, semicrystalline, crystalline).Electron-Phonon Interaction Analysis: Conducted in-depth DFT studies on crystalline materials, identifying electron-phonon interactions that significantly affect macroscopic electrical properties. Validated findings through inelastic neutron scattering experiments.Molecular Dynamics for Amorphous Materials: Investigated amorphous materials using Molecular Dynamics, identifying key molecular configurations. Applied DFT-parametrized Model Hamiltonians to elucidate their opto-electronic behavior.MD Forcefield Parametrization: Engaged in the development of a Molecular Dynamics forcefield, enhancing the prediction of structure and dynamics in organic semiconductors, corroborated by neutron scattering experiment data.

Oak Ridge National Laboratory

Theoretical/computational modeling of inelastic neutron scattering results.

San Carlos, Ca

Contributed to early phase drug development projects focusing primarily on formulation of pulmonary therapeutics using a proprietary spray drying method.Built computational models of filtration processes to elucidate deviations between contradicting experimental results.

Built software and ran sequencing experiments to understand the structure and function of long-intergenic non-coding RNA (lincRNA) scaffolds.

Doctor Of Philosophy (Phd), Chemical Engineering

Taken 40+ credit hours of graduate level courses in Chemical Engineering, Chemistry, Physics, and Materials Science departments. My thesis.

Master Of Science (M.S.), Chemical & Biomolecular Engineering

Bachelor Of Science (Bs), Chemical & Biomolecular Engineering

Bachelor'S Degree, Biology