
About
Alex Maldonado is a Teaching Assistant Professor at the University of Pittsburgh, specializing in computational chemistry and its applications in catalysis and drug discovery. Their research bridges theoretical modeling with practical chemical innovation.
Key research interests include:
- Quantum and classical molecular dynamics simulations
- Solvation modeling for reaction mechanisms
- Machine learning force fields
- Quantum alchemy in chemical bonding
- Computationally guided catalyst discovery
- Molecular docking tools (MolModa) for drug development
Recent work focuses on uncertainty quantification in solvation procedures and their implications for aqueous phase reactions and renewable chemical production.
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