Campus Directory

Division Baskin School of Engineering

Department/ College/ Unit Electrical and Computer Engineering

Title Doctoral Researcher

Graduate Major Electrical Engineering

Affiliation Graduate

Other UCSC Campus Affiliation Genomics Institute

Web Site

Primary Office Location UC Santa Cruz Westside Research Park
B290

Office Hours for Students/ Office Hours Monday Through Friday, 9am to 5pm

Mail Stop WRP Facilities

Biography, Education and Training

I'm a Ph.D. student in Electrical and Computer Engineering at UC Santa Cruz and a member of the Braingeneers group at the UCSC Genomics Institute. I did my undergrad here too, finishing a B.S. in Robotics Engineering with a minor in Electrical Engineering in 2023. I've since earned an M.S. in Electrical and Computer Engineering on the way to the Ph.D., concentrating in machine learning, robotics, controls, and cyber-physical systems.

My research right now is mostly computational. One part of it is forecasting: I build models that predict the next moments of spiking activity across large populations of recorded neurons. I led SpikeProphecy, a benchmark for this problem built from about 90,000 neurons in public Neuropixels recordings, and a follow-up showing that the same forecasts can be read out to decode what the animal is doing. The other part is connectome simulation. I turned the adult fly brain-and-nerve-cord connectome into a spiking network of about 172,000 neurons and ran it inside a simulated body to see how much behavior the wiring produces on its own, with no training.

I came to this from the experimental side of the lab. For about two years I designed and fabricated microfluidic devices for human brain organoids, wrote the computer vision code to track how the organoids grew in them, and helped build a modular microscope that images cultures from inside the incubator. One of those devices, BioNets, holds organoids in place on microelectrode arrays and is now provisionally patented through UCSC.

During undergrad I spent most of 2021 working for the USGS as a drone pilot and sensor engineer, flying magnetic and thermal surveys over volcanic systems at Mammoth Lakes, California and Krafla, Iceland.

Summary of Expertise

• Neural population modeling and spike forecasting with state space models, Transformers, LSTMs, and spiking neural networks (PyTorch, snnTorch)

• Connectome-constrained spiking network simulation

• Image analysis for long-term live-cell microscopy: registration, drift correction, cell and organoid tracking, morphology (OpenCV, scikit-image)

• Microfluidic device design and fabrication: photolithography, PDMS soft lithography, parylene deposition, SEM, optical profilometry

• Brain organoid electrophysiology on high-density microelectrode arrays

• Embedded systems, robotics, and control

• Large-scale GPU training on Kubernetes (National Research Platform), Docker, AWS S3

Research Interests

• Forecasting neural population activity, and using those forecasts in closed-loop brain-computer interfaces

• What a connectome can and can't tell us about behavior

• Spiking neural networks and low-power neuromorphic hardware

• Brain organoids as models of developing human neural circuits

• Automated microscopy and lab automation

Teaching Interests

I tutored math at Santa Barbara City College for two years, covering everything from college algebra through multivariable calculus, linear algebra, and differential equations. I'd like to teach or TA:

• Embedded systems and microcontroller programming

• Mechatronics and introductory robotics

• Machine learning for neuroscience

• Engineering math (calculus, linear algebra, differential equations)

Awards, Honors and Grants

• Finalist, Young Professional Paper Competition, IEEE EMBC 2025, Copenhagen, Denmark (2025)

• Dean's Award for Outstanding Undergraduate Research in Engineering, UC Santa Cruz (2024)

• Honors in the Major, B.S. Robotics Engineering, UC Santa Cruz (2023)

• First Place, UC Santa Cruz Mechatronics Competition (2022)

Grant Contributions

• California Institute for Regenerative Medicine (CIRM), ReMIND Program (2024). $4.1M UCSC portion of a $12.3M award. PIs: S. Salama, M. Mostajo-Radji, M. Teodorescu, D. Haussler. Contributed microfluidic devices, computer vision pipelines, and connectoid analysis.

• University of California Office of the President (UCOP) MRPI, ASD Brain Organoid Modeling, via QB3 (2024). $1.8M. Lead PI: H. Bateup (UC Berkeley); UCSC PIs: S. Salama, M. Teodorescu, M. Mostajo-Radji. Contributed microfluidic, computer vision, and organoid analysis platforms.

Selected Presentations

• Minnick, J., Ehrlich, D., Moarefian, M., Sevetson, J., Geng, J., Voitiuk, K., Rosen, Y., Salama, S. R., Haussler, D., & Teodorescu, M. (2025). Microfluidic Topography Biases Neural Organoid Morphogenesis. Oral presentation at the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2025), July 14–18, Copenhagen, Denmark. Young Professional Paper Competition finalist.

• Geng, J., ..., Minnick, J., et al. (2025). Weighted Graph for Longitudinal Tracking of Neurons in Cortical Organoids on a High-Density Microelectrode Array. Oral presentation at the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2025), July 14–18, Copenhagen, Denmark.

• Minnick, J., Geng, J., Nguyen, C., Sevetson, J., Salama, S. R., Haussler, D., & Teodorescu, M. (2025). BioNets: An Alternative to Gels and Grids for Immobilizing 3D Neural Samples on MEAs. Oral presentation at MEA 2025: 13th Meeting on Neural and Electrogenic Cell Interfacing, July 2025, Vienna, Austria.

• Moarefian, M., Cisneros, A., Minnick, J., Hernandez, S., Mostajo-Radji, M., Sharf, T., & Teodorescu, M. (2024). Integrating Microfluidic and Multi-Electrode Array (MEA) Systems for Live Migration of Inhibitory Interneurons and Excitatory Cortical Neurons Using Chemical and Electrical Stimuli. Poster presented at the Biomedical Engineering Society (BMES) Annual Meeting 2024, October 23–26, Baltimore, MD. Abstract No. 2865884.

• Minnick, J., Moarefian, M., Sevetson, J., Salama, S., & Teodorescu, M. (2024). Unlocking Optimal Micro-Macro Fabrication Methodology for Neural Engineering: Comparative Analysis of Polydimethylsiloxane (PDMS) Molds in Neurite Outgrowth Studies. Poster presented at the Society for Neuroscience (SfN) Annual Meeting 2024, October 5–9, Chicago, IL. Abstract No. 13694.

• Anderson, J., Glen, J. M. G., Earney, T., Rea-Downing, G., Zielinski, L., Kelly, P. J., Dean, B., Keller, G., Bouligand, C., Minnick, J., & Tarkany, S. (2023). Ground and Airborne-based Geophysical Mapping and Monitoring of Volcanic and Hydrothermal Systems at Mammoth Lakes, California. Poster presented at the AGU Fall Meeting 2023, December 11–15, San Francisco, CA. Poster No. GP33C-0572. Bibcode: 2023AGUFMGP33C0572A

Selected Publications

• Minnick, J. R., Gonzalez-Ferrer, J., Geng, J., Eshraghian, J. K., Mostajo-Radji, M. A., Haussler, D., & Teodorescu, M. (2026). Sensorimotor behaviour from an untrained brain-and-nerve-cord connectome. arXiv preprint arXiv:2610.33881. https://doi.org/10.48550/arXiv.2610.33881

• Gonzalez-Ferrer, J., Moreno-Ochando, A., Minnick, J. R., Schneider, A., Teodorescu, M., Haussler, D., & Mostajo-Radji, M. A. (2026). Decoding brain anatomy from neuronal neighborhoods with MYCEL. bioRxiv. https://doi.org/10.64898/2026.09.26.754562

• Minnick, J. R., Geng, J., Hussain, K., Gonzalez-Ferrer, J., Robbins, A., Mostajo-Radji, M. A., Haussler, D., Eshraghian, J. K., & Teodorescu, M. (2026). SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting. arXiv preprint arXiv:2605.12992. https://doi.org/10.48550/arXiv.2605.12992

• Minnick, J. R., Gonzalez-Ferrer, J., Hussain, K., Geng, J., Robbins, A., Mostajo-Radji, M. A., Haussler, D., Eshraghian, J. K., & Teodorescu, M. (2026). Implicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale. arXiv preprint arXiv:2605.12999. https://doi.org/10.48550/arXiv.2605.12999

• Ehrlich, D., Rosen, Y., Arul, S., Minnick, J., Nicholson, S., Voitiuk, K., Seiler, S., Toledo, A., Vera-Choqqueccota, S., Doherty, N., Sevetson, J., McGlynn, M., Doganyigit, K., Moarefian, M., Kurniawan, S., Mostajo-Radji, M. A., Salama, S. R., Winkler, E., Haussler, D., & Teodorescu, M. (2026). A Modular In-Incubator Microscope for Longitudinal Live Cell Microscopy. bioRxiv. https://doi.org/10.64898/2026.01.20.699789

• Minnick, J., Ehrlich, D., Moarefian, M., Sevetson, J., Geng, J., Voitiuk, K., Rosen, Y., Salama, S. R., Haussler, D., & Teodorescu, M. (2025). Microfluidic Topography Biases Neural Organoid Morphogenesis. In 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1–7). IEEE. https://doi.org/10.1109/EMBC58623.2025.11254219

• Minnick, J., Geng, J., Nguyen, C., Sevetson, J., Salama, S. R., Haussler, D., & Teodorescu, M. (2025). BioNets: An Alternative to Gels and Grids for Immobilizing 3D Neural Samples on MEAs. In MEA 2025: 13th Meeting on Neural and Electrogenic Cell Interfacing (pp. 136–137). Institute of Biomedical Electronics, TU Wien.

• Lindhout, F. W., Szafranska, H. M., Guglielmi, L., Imaz-Rosshandler, I., Boulanger, J., Moarefian, M., Voitiuk, K., Zernicka-Glover, N. K., Schulze, U., Minnick, J., Lloyd-Davies Sánchez, D. J., Chiaradia, I., Pellegrini, L., Teodorescu, M., & Lancaster, M. A. (2024). Calcium dynamics tune timing of developmental transitions to generate evolutionarily divergent axon tract lengths. bioRxiv. https://doi.org/10.1101/2024.12.28.630576

• Minnick, J. (2024). Microfluidic PDMS Chip for Unidirectional Recurrent Neural Networks (Version 1.x). NIH 3D. https://doi.org/10.60705/3DPX/21595.1

• Minnick, J. R. (2023). Automated Tools for Accurate and Precise Dosing of Granular Solids. Bachelor's Thesis, University of California, Santa Cruz. Available at: https://dca.ue.ucsc.edu/dca/winners/2024/1615.pdf