About Me
I am a 6th year PhD student in the Joint Carnegie Mellon/University of Pittsburgh program for Computational Biology. I am working in Prof David Ryan Koes’s lab. My research focuses on enhancing deep learning models for drug discovery.
Research Interests:
- Drug Discovery
- Deep Learning
- Structural Biology
- Metric Learning
- Self-Supervised Learning
I graduated from Purdue University with honors in 2019 with a double major in Physics and Mathematics.
Other Interests
When I am not doing research I enjoy cooking, baking, and fermenting (Checkout my Cookbook). My other time is spent outdoors enjoying nature while climbing, hiking, and camping.
Papers and Talks
A list of the published papers and conference talks that I have given.
For a more up to date list, check out my Google Scholar page.
Duvelisib is a novel NFAT inhibitor that mitigates adalimumab-induced immunogenicity
Aboli Bhingarkar, Yuyin Wang, Keito Hoshitsuki, Katherine Marie Eichinger, Sanjay Rathod, Yin Zhu, He Lyu, Andrew McNutt, Larry W Moreland, Lee Mcdermott, David Ryan Koes, Christian Fernandez
Link to PaperSPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes
Andrew McNutt, Abhinav K. Adduri, Caleb N. Ellington, Monica T. Dayao, Hosein Mohimani, Eric P. Xing, David R. Koes
Link to Paper Link to PosterUltra-High-Throughput Virtual Screening for Antimicrobials
Caleb N. Ellington, Abhinav K. Adduri, Andrew McNutt, Monica T. Dayao, Hosein Mohimani, David R. Koes, Eric P. Xing
Condensing Molecular Docking CNNs via Knowledge Distillation
Andrew McNutt, Yanjing Li, Paul Francoeur, David Ryan Koes
Link to PaperOpen-ComBind: Harnessing unlabeled data for improved binding pose prediction
Andrew McNutt, David Ryan Koes
Link to PaperConformer Generation for Structure-Based Drug Design: How Many and How Good?
Andrew McNutt, Fatimah Bisiriyu, Sophia Song, Ananya Vyas, Geoffrey R. Hutchison, David Ryan Koes
Link to PaperImproving 𝚫𝚫G Predictions with a Multitask Convolutional Siamese Network
Andrew McNutt, David Ryan Koes
Link to PaperIntegrated cytometry with machine learning applied to high-content imaging of human kidney tissue for in-situ cell classification and neighborhood analysis
Seth Winfree, Andrew McNutt, Suraj Khochare, Tyler J. Borgard, Daria Barwinska, Angela R. Sabo, Michael J. Ferkowicz, James C. Williams Jr, James E. Lingeman, Connor J Gulbronson, Katherine J. Kelly, Timothy A. Sutton, Pierre C. Dagher, Michael T. Eadon, Kenneth W. Dunn, Tarek M. El-Achkar
Link to PaperExploring 𝚫𝚫G prediction with Siamese Networks
Andrew McNutt, David Koes
Link to TalkGNINA 1.0: Molecular docking with deep learning
Andrew McNutt, Paul Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, David Koes
Link to Paper Link to TalkIn situ classification of cell types in human kidney tissue using 3D nuclear staining
Andre Woloshuk, Suraj Khochare, Aljohara F Almulhim, Andrew McNutt, Dawson Dean, Daria Barwinska, Michael J Ferkowicz, Michael T Eadon, Katherine J Kelly, Kenneth W Dunn, Mohammad A Hasan, Tarek M El‐Achkar, Seth Winfree
Link to PaperComparison of Supervised Machine Learning and Probabilistic Approaches for Record Linkage
Andrew McNutt, Shaun J Grannis, Na Bo, Huiping Xu, Suranga N Kasthurirathne
Education & Experience
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Aug 2019 - Present
PhD Student in Koes Lab
-
Summer 2019
Student Research Assistant - Center for Biomedical Informatics
Neural Networks Hyperparameter Optimization -
Summer 2018
Student Intern
Clustering Dimensionality Reduction Github -
Summer 2017
Indiana University O'Brien Student Intern
Java -
2017 - 2019
Undergraduate Research Assistant - Department of Medicinal Chemistry & Molecular Pharmacology
Molecular Dynamics Machine Learning -
2015 - 2019
B.S. Physics & Mathematics
Minor in Chemistry