I am a computational chemist who builds predictive tools and studies reaction mechanisms using DFT, molecular dynamics, QM/MM, cheminformatics, and graph neural networks. I recently (February 2026) completed my Ph.D. with Prof. Peng Liu at the University of Pittsburgh. My work focuses on three main areas:
Transition-Metal and Enzyme Catalysis
Cheminformatics and Machine Learning
High-throughput MD simulations (on-going)
Ph.D. in Chemistry, 2026
University of Pittsburgh
B.S. in Chemistry, 2021
Colorado State University

Alkyl sulfonyl fluorides act as ambiphilic coupling partners in Pd(II)-catalyzed stereoselective cyclopropanation of unactivated alkenes, with the SN2-type C–SO2F oxidative addition serving as the turnover-limiting and diastereoselectivity-determining step.

De novo designed helical bundle proteins were evolved to achieve enantioselective Ge–H insertion, the first enzymatic germylation reaction, with DFT and MD simulations revealing why Ge–H is mechanistically harder to control stereoselectively than Si–H insertion.

A Pd/amino acid cocatalytic system converts ortho-alkenyl benzaldehydes into styrene derivatives exhibiting the rare phenomenon of equivalent atrop- and positional isomerism via sequential enantioselective Mizoroki–Heck 1,3-diarylation.

Directed evolution of pyridoxal decarboxylases enabled a stereoselective three-component radical C–C coupling new to both biochemistry and organic chemistry, providing six product classes with excellent stereocontrol for diversity-oriented medicinal chemistry library synthesis.

DIXAT (Directed Halogen Atom Transfer) is a new strategy that enables chemoselective activation of aryl bromides over aryl iodides through geometric directing effects, overturning the intrinsic reactivity trends of XAT and SET for Ni-catalyzed remote C(sp3)–H functionalization of aliphatic amines.

HArD is a freely accessible database of 65 DFT-computed steric and electronic descriptors for over 31,500 heteroaryl substituents, including a new Hammett-type substituent constant (σHet), designed to enable quantitative structure–activity and reactivity modeling of heteroaromatic compounds.

Novel chiral silanol ligands with a peptide-like aminoamide scaffold enable Cu-catalyzed enantioselective N–H insertion to form unnatural amino acids, with DFT and X-ray analysis revealing that H-bond-stabilized silanol–copper chelation and π–π stacking drive high selectivity.

A de novo designed minimal four-helix bundle protein incorporating synthetic porphyrin or heme cofactors achieves high efficiency and enantioselectivity in abiological carbene transfer reactions, with directed evolution and computational analysis revealing the structural basis for stereocontrol.

A combined experimental and computational study revealing how HFIP solvent induces flexibility in dirhodium catalysts to modulate enantioselectivity in cyclopropanation reactions.

A three-component coupling approach towards structurally complex dialkylsulfides is described via the nickel-catalyzed 1,2-carbosulfenylation of unactivated alkenes with organoboron nucleophiles and alkylsulfenamide (N–S) electrophiles

This study presents a mild and efficient method for synthesizing densely functionalized cyclopropanes via directed nucleopalladation of nonconjugated alkenes, yielding excellent anti-selectivity and accommodating diverse electron-withdrawing pronucleophiles, with mechanistic insights supported by DFT calculations showing key steps of α-iodination, anti-carbopalladation, and strain-release-promoted reductive elimination.

A novel resonance-assisted self-doping mechanism in ladder-type oligoaniline-derived organic conductors, enabling efficient proton transfer and enhanced stability without external dopants, as confirmed by mechanistic and computational studies.

Herein, we report a transient directing group (TDG) strategy to facilitate site-selective palladium-catalyzed reductive Heck-type hydroalkenylation and hydroalkynylation of alkenylaldehyes using alkenyl and alkynyl bromides, respectively, allowing for construction of a stereocenter at the δ-position with respect to the aldehyde.

AQME, Automated Quantum Mechanical Environments, is a free and open-source Python package for the rapid deployment of automated workflows using cheminformatics and quantum chemistry.