2021 Annual Meeting

Session: Data-Driven Design and Modeling I

Chair

Co-Chairs

He, Y., Zhejiang University (Yuquan Campus)

Presentations

12:30 PM

(118a) The Machine Learning Route to Accelerated Discovery and Inverse Design of Chemical and Materials Systems
Hachmann, J.

01:00 PM

(118b) A Universal Framework for Featurization of Atomistic Systems
Medford, A., Lei, R.

01:15 PM

(118c) Transfer Learning Using Large-Scale ML Models for Catalyst/Molecular Datasets
Kolluru, A., Shuaibi, M., Ulissi, Z.

01:30 PM

(118d) Semi-Supervised Learning Detects Safe Islands Where Density Functional Theory Is Applicable for Chemical Discovery
Duan, C., Nandy, A., Liu, F., Kulik, H.

01:45 PM

(118e) In silico discovery of Target Peptide Inhibitors for C. Diff toxins a and B
Sarma, S., Xiao, X., Menegatti, S., Crook, N., Magness, S., Hall, C.

02:00 PM

(118f) You May Not Have Noticed, but Your Neural Network Did: Machine Learning from Simulated Enzyme Variants
Burgin, T., Pfaendtner, J., Beck, D.

02:15 PM

(118g) Deep Reinforcement Machine Learning Driven Vaccine Design Against Highly Mutable Pathogens
Faris, J., Peterson, B., Faissol, D., Sprenger, K.

02:30 PM

(118h) Data-Driven Reconstruction of Molecular Folding Trajectories from Single-Molecule Experimental Measurements
Topel, M., Ferguson, A.

02:45 PM

(118i) High-Throughput Screening of Tribological Properties of Monolayer Films Using Molecular Dynamics and Machine Learning
Quach, C., Gilmer, J., Iacovella, C., Cummings, P., McCabe, C.