talks.tex

\begin{rubric}{Talks}
\entry*[\hspace{1.05cm}2023] \textbf{Boltzmann distributions from explicit solvation to protein dynamics}, UCT\&IOCB Theoretical Chemistry seminars
\entry*[\hspace{1.05cm}2023] \textbf{Bridging the explicit solvation experiment-calculation divide with machine learning and high-throughput simulation}, EuChemS CompChem
\entry*[\hspace{1.05cm}2023] \textbf{Larger datasets of ground truth chemistry explanations}, $@$XAI\_Research
\entry*[\hspace{1.05cm}2022] \textbf{Ground truth explainabilities for explainable artificial intelligence}, ACS Fall
\entry*[\hspace{1.05cm}2022] \textbf{AutoSolvate: Open source high-throughput generation of explicitly solvated systems and microsolvated clusters}, ACS Fall
\entry*[\hspace{1.05cm}2021] \textbf{Benchmarking the accuracy of free energy landscapes generated by adaptive sampling strategies}, CECAM, Mixed-gen Session 6: Activated Events
\entry*[\hspace{1.05cm}2021] \textbf{Reducing the error of redox potential calculations in implicit and explicit solvents with machine learning}, ACS Fall
\entry*[\hspace{1.05cm}2020] \textbf{Deep learning of molecular dynamics representations}, Emory Machine Learning in Chemistry Journal Club
\end{rubric}