Alex Morehead

Ph.D. Candidate in Machine Learning & Computational Biology @Mizzou


Welcome! :wave:

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.


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).


I enjoy sharing thoughts on Machine Learning research and applications on Twitter and (occasionally) my blog.


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!
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 :sparkles:
Sep 27, 2021 One paper accepted by IEEE SuperComputing (MLHPC workshop)
Aug 24, 2021 Served as a reviewer for NeurIPS 2021 :sparkles:
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

  1. Low Cost Gunshot Detection using Deep Learning on the Raspberry Pi
    Morehead, Alex, Ogden, Lauren, Magee, Gabe, Hosler, Ryan, White, Bruce, and Mohler, George
    IEEE International Conference on Big Data (Big Data) 2019
  2. Geometric Transformers for Protein Interface Contact Prediction
    Morehead, Alex, Chen, Chen, and Cheng, Jianlin
    International Conference on Learning Representations (ICLR) 2022
  3. Geometry-Complete Perceptron Networks for 3D Molecular Graphs
    Morehead, Alex, and Cheng, Jianlin
    arXiv preprint arXiv:2211.02504 2022
  4. Geometry-Complete Diffusion for 3D Molecule Generation
    Morehead, Alex, and Cheng, Jianlin
    arXiv preprint arXiv:2302.04313 2023
  5. 3D-equivariant graph neural networks for protein model quality assessment
    Chen, Chen, Chen, Xiao,  Morehead, Alex, Wu, Tianqi, and Cheng, Jianlin
    Bioinformatics 2023