Alex Morehead
Ph.D. Candidate in Machine Learning & Computational Biology @Mizzou
About
Welcome!
I am a Computer Science Ph.D. candidate at the University of Missouri. I work as a graduate research assistant in Dr. Jianlin Cheng’s Bioinformatics & Machine Learning Lab. Prior to my Ph.D., I completed my B.S. in Computer Science at Missouri Western State University. My interests in computer science and machine learning began through many fun experiences building and experimenting with bleeding-edge software early on, and competing in mathematics Olympiads in high school.
Research
My current research interests include machine learning, deep learning, computational biology, and high-performance computing. In particular, I have developed new 3D graph neural network architectures such as the Geometric Transformer for modeling large biomolecules (e.g., proteins) and curated large open-source molecular datasets (e.g., DIPS-Plus).
Writing
I enjoy sharing thoughts on Machine Learning research and applications on Twitter and (occasionally) my blog.
news
Feb 14, 2023 | Presented GCPNet and GCDM at AAAI 2023’s Deep Learning on Graphs (DLG-AAAI’23) workshop as well as the AI to Accelerate Science and Engineering (AI2ASE-AAAI’23) workshop! |
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Feb 10, 2023 | Served as a reviewer for both Nature Machine Intelligence and IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)! |
Dec 20, 2022 | Published GCPNet at AAAI 2023’s Deep Learning on Graphs (DLG-AAAI) and AI to Accelerate Science & Engineering (AI2ASE-AAAI) workshops! |
Aug 20, 2022 | Finished my summer internship with Absci as an AI Scientist 🧬 |
Apr 11, 2022 | Passed my Ph.D. qualifying exam. Cheers! |
Apr 9, 2022 | Won 4th place at the 2022 CVPR AI City Challenge, Task 4 |
Jan 20, 2022 |
One paper accepted by ICLR ![]() |
Sep 27, 2021 | One paper accepted by IEEE SuperComputing (MLHPC workshop) |
Aug 24, 2021 |
Served as a reviewer for NeurIPS 2021 ![]() |
Dec 5, 2020 | Attended NeurIPS 2020 virtually |
Nov 30, 2020 | Attended CASP14 virtually |
Jun 11, 2020 | One paper accepted by AJUR |
Nov 9, 2019 | One paper accepted by IEEE BigData |
selected publications
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Low Cost Gunshot Detection using Deep Learning on the Raspberry PiIEEE International Conference on Big Data (Big Data) 2019
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Geometric Transformers for Protein Interface Contact PredictionInternational Conference on Learning Representations (ICLR) 2022
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Geometry-Complete Perceptron Networks for 3D Molecular GraphsarXiv preprint arXiv:2211.02504 2022
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Geometry-Complete Diffusion for 3D Molecule GenerationarXiv preprint arXiv:2302.04313 2023
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3D-equivariant graph neural networks for protein model quality assessmentBioinformatics 2023