Alex C. Morehead

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

About

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.

Research

My current research interests include machine learning, deep learning, computational biology, and generative modeling. In particular, I have developed new geometric graph neural network architectures such as GCPNet and the Geometric Transformer for modeling biomolecules of various sizes (e.g., proteins), introduced GCDM for diffusion generative modeling of 3D molecules, and assembled PoseBench, the first deep learning benchmark for practical protein-ligand docking.

Writing

I enjoy sharing thoughts on literature, research, and applications on my blog.


news

Jul 03, 2024 One paper accepted by Nature CommsChem :dna:
Jun 17, 2024 Two ICML workshop papers selected for spotlight presentations :sparkles:
Feb 19, 2024 One paper accepted by Bioinformatics :dna:
Jan 16, 2024 One paper accepted by ICLR :sparkles:
Jul 25, 2023 Published and presented one paper at ISMB :dna:
Jan 20, 2022 One paper accepted by ICLR :sparkles:

latest posts

selected publications

  1. Geometric Transformers for Protein Interface Contact Prediction
    Alex Morehead, Chen Chen, and Jianlin Cheng
    In The Tenth International Conference on Learning Representations (ICLR) , 2022
  2. Geometry-Complete Perceptron Networks for 3D Molecular Graphs
    Alex Morehead, and Jianlin Cheng
    Bioinformatics, 2024
    Also presented at the AAAI 2023 DLG (poster) and AI2ASE (oral presentation) workshops
  3. Geometry-Complete Diffusion for 3D Molecule Generation
    Alex Morehead, and Jianlin Cheng
    Nature Communications Chemistry, 2024
    Also presented at the ICLR 2023 MLDD workshop
  4. Towards Joint Sequence-Structure Generation of Nucleic Acid and Protein Complexes
    Alex Morehead, Aadyot Bhatnagar, Jeffrey A. Ruffolo, and 1 more author
    In NeurIPS Machine Learning in Structural Biology (MLSB) Workshop , 2023
  5. Evaluating Representation Learning on the Protein Structure Universe
    Arian R. Jamasb*, Alex Morehead*, Zuobai Zhang*, and 8 more authors
    In The Twelth International Conference on Learning Representations (ICLR) , 2024
    Also presented at the NeurIPS 2023 MLSB workshop
  6. Deep Learning for Protein-Ligand Docking: Are We There Yet?
    Alex Morehead, Nabin Giri, Jian Liu, and 1 more author
    In ICML AI4Science Workshop , 2024
    Selected as a spotlight presentation (top 20% - 30/159)
  7. RNA-FrameFlow for de novo 3D RNA Backbone Design
    Rishabh Anand*, Chaitanya K Joshi*, Alex Morehead, and 6 more authors
    In ICML AI4Science & SPIGM Workshops , 2024
    Selected as a SPIGM (AI4Science) oral (spotlight) presentation