Curriculum Vitae

Last updated September 2026.

I build deep-learning and foundation-model methods for single-cell genomics and multimodal neural data. First author on SIMS (Cell Genomics) and HIPPIE (Nature Communications); I led the single-cell analysis for the SSPSYgene consortium at ~6M cell scale, and work on AI target discovery at Genentech.

PROFESSIONAL EXPERIENCE

Graduate Student Researcher — UC Santa Cruz (Braingeneers) · 2022–present

PIs: David Haussler, Mohammed A. Mostajo-Radji

  • Built SIMS, an explainable deep-learning model for cell-type classification from single-cell RNA-seq, published in Cell Genomics and released as open-source tooling adopted by other labs.
  • Developed HIPPIE, a multimodal deep-learning model that classifies neurons from extracellular electrophysiology, published in Nature Communications.
  • Designed and validated cross-modal frameworks integrating spatial transcriptomics with electrophysiology across organoid datasets.
  • Built web applications (CytoVerse, UCSC Brain Explorer) with a scalable architecture that democratizes single-cell RNA and electrophysiology analysis, with deep-learning models at the core.
  • Provided cross-functional leadership for the joint analysis group of the SSPSYgene consortium, supporting a large-scale perturbation data resource encompassing ~6 million cells. Orchestrated cross-laboratory integration and perturbation-analysis architecture across multiple scRNA chemistries (10x v2/v3, PIPseq) and diverse perturbation modalities (CRISPR-Cas9, CRISPRi, Perturb-seq), facilitating convergence with bulk RNA-seq, organoid and primary tissue data.
  • Contributed to grant proposals to NIH, NSF, CIRM, UCOP and BBRF, supporting $50M+ in awarded funding and $60M+ under review.

AI Researcher — Genentech (gRED), South San Francisco · 2025–present

Managers: Alsu Missarova, Héctor Corrada Bravo, Jason Vander Heiden

  • Developed graph-based and machine-learning approaches built on single-cell foundation models to power drug discovery pipelines and downstream statistical frameworks for target identification, translational impact, and discovery of shared disease mechanisms across conditions.

Machine Learning Engineer / Analyst — SDG Group Iberia (Data Tech) · 2021–2022

  • Designed and built an ML framework in R used by 50+ data scientists.
  • Automated data processes in Python with Apache Airflow; migrated SAS ETL projects to SQL, saving ~€1,500 per employee.

Earlier research

Machine Learning Researcher — Universidad Complutense de Madrid · 2021. ML to study multiple sclerosis and its relationship with cognitive impairment (PI: José Luis Rodrigo Ayala).

Computer Vision Intern — VINDOO · 2021. Trained YOLOv4 vision models to help farmers optimize fruit-harvest timing.

Neuroscience Researcher — Instituto de Neurociencias, Alicante · 2019–2020. Studied ROBO and STIL in neurogenesis and cortical expansion (PI: Víctor Borrell).

EDUCATION

Ph.D., Bioinformatics & Bioengineering — UC Santa Cruz (Braingeneers) · 2022–present

M.Sc., Computational Biology — Universidad Politécnica de Madrid · 2020–2021

B.Sc., Biotechnology (High Academic Performance group) — Universidad Miguel Hernández de Elche · 2016–2020

SELECTED PUBLICATIONS

(*) denotes first or co-first authorship.

Gonzalez-Ferrer, J.*, Lehrer, J., Alvarez-Esteban, B., Moreno-Ochando, A., Schweiger, H. E., … Haussler, D. & Mostajo-Radji, M. A. (2026). HIPPIE: a generative model for electrophysiological analysis across species, technologies, and modalities. Nature Communications. doi

Vera-Choqquecota, S., Ehrlich, D., Luna-Gomez, V., Hernandez, S., Gonzalez-Ferrer, J., … & Mostajo-Radji, M. A. (2026). Cloud-connected pluripotent stem cell platform enhances scientific identity in underrepresented students. Stem Cell Reports. doi

Currie, R.*, Gonzalez-Ferrer, J.*, Mostajo-Radji, M. A. & Haussler, D. (2026). CytoVerse: Single-cell AI foundation models in the browser. bioRxiv. doi

van der Molen, T., Spaeth, A., Chini, M., Hernandez, S., Kaurala, G. A., Schweiger, H. E., … Gonzalez-Ferrer, J., … & Sharf, T. (2026). Preconfigured neuronal firing sequences in human brain organoids. Nature Neuroscience, 29(1), 123–135. doi

Zabetian, Z., Gonzalez-Ferrer, J., Lehrer, J., Jonsson, V., Teodorescu, M., Haussler, D. & Mostajo-Radji, M. A. (2025). Protocol for deep-learning-driven cell type label transfer in single-cell RNA sequencing data. STAR Protocols, 6(2), 103768. doi

Geng, J., Gonzalez-Ferrer, J., Voitiuk, K., Seiler, S. T., Schweiger, H. E., Hernandez, S., … & Teodorescu, M. (2025). Weighted graph for longitudinal tracking of neurons in cortical organoids on a high-density microelectrode array. IEEE EMBC 2025. doi

Gonzalez-Ferrer, J.* & Mostajo-Radji, M. A. (2025). Toward automated and explainable high-throughput perturbation analysis in single cells. Patterns, 6(4), 101228. doi

Mostajo-Radji, M. A., Leon, W. R. M., Breevoort, A., Gonzalez-Ferrer, J., Schweiger, H. E., Lehrer, J., … & Pollen, A. A. (2025). Fate plasticity of interneuron specification. iScience, 28(4), 112295. doi

Gonzalez-Ferrer, J.*, Lehrer, J., O’Farrell, A., Paten, B., Teodorescu, M., Haussler, D., … & Mostajo-Radji, M. A. (2024). SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis. Cell Genomics, 4(6), 100581. doi

Sano, T., Sampad, M. J. N., Gonzalez-Ferrer, J., et al. (2024). Internet-enabled lab-on-a-chip technology for education. Scientific Reports, 14, 14364. doi

AWARDS & FELLOWSHIPS

  • Dissertation-Year Fellowship — UC Santa Cruz (2026–27)
  • Honorable Mention — UCLA Emerging Genomic Scientist Symposium (2026)
  • QB3 Fellowship — UC Santa Cruz (2025)
  • SSPSYgene Travel Award (2025)

SELECTED PRESENTATIONS

  • CytoVerse: A Browser-Native Platform for Scalable, Privacy-Preserving Single-Cell Analysis — Poster, scverse Conference, Stanford (2025)
  • HIPPIE: Multimodal Electrophysiological Classification of Neurons — Poster, SSPSYgene Consortium Meeting, UCLA (2024)
  • Data Standards for Single-Cell RNA — Talk, SSPSYgene Consortium Meeting, UCLA (2024)
  • Single-Cell RNA Automated Pipeline in Terra — Talk, SSPSYgene Consortium Meeting, NIH (2023)
  • Unraveling Cell-Line-Specific Differences with Deep Learning — Flash Talk, CEGS Meeting, NYU (2023)
  • A Minimal-Code Tool for Cell-Type Classification from Single-Cell Data — Poster, Society for Neuroscience (2022)

TECHNICAL SKILLS

Single-cell & genomics — Scanpy, Seurat, Monocle, scRNA-seq/scATAC analysis, DESeq2, GWAS, Bioconductor

ML & deep learning — PyTorch, TensorFlow, Keras, scikit-learn; variational autoencoders, CNNs, foundation models, representation learning, gradient boosting; computer vision, time-series

Multimodal & neural data — Electrophysiology analysis (MaxWell HD-MEA, Neuropixels), spatial-transcriptomics integration, Braingeneerspy, pyNWB, AllenSDK

Production ML / MLOps & cloud — Docker, Kubernetes, Apache Airflow, PySpark, WDL/Dockstore, SLURM, Terra, Google Cloud, OVH; Weights & Biases, Hugging Face, ONNX

Software & web — Python (adv.), R (adv.), SQL, JavaScript, Bash; Git/GitHub/GitLab; Django, Flask, React; viz (Matplotlib, Seaborn, Plotly, D3, Bokeh, ggplot2)

Wet lab — Tissue culture, immunohistochemistry, PCR/qPCR, cDNA library prep, aseptic technique

TEACHING & OUTREACH

  • Teaching Assistant, BME 18 — Scientific Principles of Life, UC Santa Cruz
  • Small World Initiative (SWI Spain, 2018) — brought antibiotic-resistance research into high school classrooms, with students participating in the search for new antibiotics (PIs: Manuel Sánchez Angulo, Marina Torreblanca Calvo)
  • Micol & Ponce labs, Institute of Bioengineering, Universidad Miguel Hernández (2018) — splicing mechanisms in Arabidopsis thaliana (PI: María Rosa Ponce Molet)

LANGUAGES

Spanish (native) · English (C1; TOEFL iBT 110) · German (basic)