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Alex Spaeth

Employment

Machine Learning Consultant
Hargrave & Associates
October 2021–present

Partnered with a business-facing founder to deliver end-to-end machine learning solutions for clients in healthcare, insurance, and SaaS, taking full technical ownership from scoping through production deployment. Projects include a full-stack agentic tool for SaaS procurement, a fraud detection pipeline, and an explainable disease risk stratification model.

ML Research Engineer (Graduate Student Researcher)
U.C. Santa Cruz Genomics Institute
September 2017–March 2025

Built production-ready deep learning models (RNNs, autoencoders, transformers) for diverse scientific datasets, partnering with domain experts to translate research questions into scalable ML workflows and impactful publications.

Skills
Programming Python, PyTorch, Scikit-learn, C++, Typescript
ML & DL time-series modeling, transformers, LLMs, RL
Infra & Ops AWS, Docker, Kubernetes, Linux, CI/CD, SQL

Education

Ph.D. in Computer Engineering
University of California, Santa Cruz (February 2025)
Computational Modeling of Neuromorphic and Neuronal Systems

B.S. in Electrical Engineering and Computer Science
University of California, Berkeley (May 2017)

Publications

  1. van der Molen, Spaeth, et al. (2025) “Protosequences in human cortical organoids model intrinsic states in the developing cortex” in press at Nature Neuroscience (preprint).
  2. Hargrave, Spaeth, et al. (2024) “EpiCare: a reinforcement learning benchmark for dynamic treatment regimes” at NeurIPS.
  3. Robbins et al. (2024) “Goal-directed learning in cortical organoids” (preprint)
  4. Spaeth et al. (2024) “Model-agnostic neural mean field with a data-driven transfer function” in Neuromorphic Computing and Engineering.
  5. Andrews et al. (2024) “Optogenetic modulation of epileptiform activity in human brain tissue” in Nature Neuroscience.
  6. Elliott et al. (2024) “Pathological microcircuits initiate epileptiform events in patient hippocampal slices” (preprint).
  7. Geng et al. (2024) “Multiscale cloud-based pipeline for neuronal electrophysiology analysis and visualization” (preprint).
  8. Zare, Spaeth, et al. (2023) “Three-dimensionally printed self-lock origami: design, fabrication, and simulation to improve the performance of a rotational joint” in Micromachines.
  9. Zare, Spaeth, et al. (2023) “Modular self-lock origami” in Proceedings of the Institution of Mechanical Engineers, Part K: Journal of Multi-body Dynamics.
  10. Tebyani, Spaeth, et al. (2022) “A geometric kinematic model for flexible voxel-based robots” in Soft Robotics.
  11. Spaeth et al. (2020) “Spiking neural state machine for gait frequency entrainment in a flexible modular robot” in PLOS One.
  12. Spaeth & Hargrave (2020) “A polyaddition model for the prebiotic polymerization of RNA and RNA-like polymers” in Life.
  13. Spaeth et al. (2020) “Neuromorphic closed-loop control of a flexible modular robot by a simulated spiking central pattern generator” in Proceedings of the 3rd IEEE International Conference on Soft Robotics.