Jonathan Fine
Computer Science · Purdue University West Lafayette
Publications
155
Citations
2,916
Est. group size
~8
Recurring co-author estimate
Active years
60
Publishing since 1967
Jonathan Fine's recent work focuses on applying machine learning to pharmaceutical chemistry, particularly predicting how molecules behave in liquid chromatography (a lab technique used to separate and purify chemical compounds). This includes building models to predict 'retention time' (how long a compound takes to pass through a chromatography column), developing software tools for optimizing chemical experiments and organizing large chemical libraries, and studying drug purification and stability. Some earlier and tangential publications touch on toxicology, environmental health, and unrelated topics like typesetting software and aesthetics.
Publication output was higher and more variable earlier in the decade (peaking around 2020) but has settled into a steadier, lower rate of roughly 5-8 papers per year in the most recent five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Uncertainty-Aware Learning of Multiple Conditions as a Framework for Streamlined Retention Time Prediction to Accelerate Method Development
Analytical Chemistry · 2026
- Purification of Pharmaceuticals via Retention Time Prediction: Leveraging Graph Isomorphism Networks, Limited Data, and Transfer Learning
Journal of Separation Science · 2025
- Paddy: an evolutionary optimization algorithm for chemical systems and spaces
Digital Discovery · 2025
- Stability impact from a titanium dioxide-free film-coated tablet: An analytical investigation into photo-, physical, and chemical stability of compressed tablets made with alternative film-coating materials
Journal of Pharmaceutical Sciences · 2025
- Dedenser: A Python Package for Clustering and Downsampling Chemical Libraries
Journal of Chemical Information and Modeling · 2025
- Purification of Pharmaceuticals via Retention Time Prediction: Leveraging Graph Invariant Networks, Limited Data, and Transfer Learning
ChemRxiv · 2025
- Uncertainty-Aware Learning of Multiple Conditions as a Framework for Streamlined Retention Time Prediction to Accelerate Method Development
ChemRxiv · 2025
- Machine learning models and performance dependency on 2D chemical descriptor space for retention time prediction of pharmaceuticals
Journal of Chromatography A · 2024
- Structure Based Machine Learning Prediction of Retention Times for LC Method Development of Pharmaceuticals
Pharmaceutical Research · 2024
- Paddy: Evolutionary Optimization Algorithm for Chemical Systems and Spaces
arXiv (Cornell University) · 2024
- Dedenser: a Python command line tool for clustering and downsampling chemical libraries
ChemRxiv · 2024
- Of Pots and Plato’s Aesthetics
The British Journal of Aesthetics · 2024
- Nitrosamine acceptable intakes should consider variation in molecular weight: The implication of stoichiometric DNA damage
Regulatory Toxicology and Pharmacology · 2023
- Portable capillary LC for in‐line UV monitoring and MS detection: Comparable sensitivity and much lower solvent consumption
Journal of Separation Science · 2023
- Accurate Prediction of Inhibitor Binding to HIV-1 Protease Using CANDOCK
Frontiers in Chemistry · 2022
- ChemRxiv×20
- TUGboat×7
- bioRxiv (Cold Spring Harbor Laboratory)×6
- arXiv (Cornell University)×4
- Journal of Chemical Information and Modeling×3
- Armen G. Beck
Computer Science · Purdue University West Lafayette
- Gaurav Chopra
Computer Science · Purdue University West Lafayette
- Jianwen Chen
Computer Science · The Ohio State University
- Anton V. Sinitskiy
Computer Science · Purdue University West Lafayette
- Woong‐Hee Shin
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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