CV

Summary

Computational neuroscientist and neural engineer building real-time models of neural dynamics. Experienced in Jupyter-to-production workflows, JAX-based modeling, large-scale dataset integration, and infrastructure-aware experimentation for next-generation neurotechnology and brain-computer interfaces.

Education

• Ph.D. in Neurobiology, Duke University, expected May 2026
  • Dissertation: OSPLAT: A Method for Uncovering Latent Oscillatory Neural Signals Across Time
• M.S. in Biomedical Engineering, Northwestern University, June 2019
  • GPA: 3.5
• B.S. in Biomedical Engineering, Rutgers University, May 2017
  • Minor: Chemistry
  • GPA: 3.7, Summa Cum Laude

Research Experience

• PhD Student, Pearson Lab, Duke University (Jun 2020 - Present)
  • Led a multi-year research project on real-time inference of population neural dynamics
  • Built end-to-end modeling workflows from notebook prototypes to reproducible script-based experiments
  • Integrated large-scale public neural datasets for cross-condition benchmarking
  • Used Git/GitHub and Linux-first tooling for reproducible experimentation
• Master’s Student, Hartmann Lab, Northwestern University (May 2018 - May 2019)
  • Led electrophysiology research investigating whisker-based encoding in rat SpVi region
  • Constructed acquisition systems, performed surgeries, and analyzed firing-rate data
• Selected Doctoral Rotations, Duke University (Sept 2019 - May 2020)
  • Brunel Lab: Prototype cerebellar circuit model development with BRIAN
  • Gong Lab: Whisker stimulation device development for optogenetic experiments
• Research Intern, CAMP, Ann and Robert H. Lurie Children’s Hospital (Summer 2017 - Spring 2018)
  • Developed synchronized audio-cue methods aligned with EEG recordings for early neurodevelopmental risk analysis

Professional Experience

• Automation Engineer Intern, Genentech (Jun 2019 - Aug 2019)
  • Collaborated with scientists to identify lab automation opportunities with liquid-handling robotics
  • Built robot control logic and user-facing GUI tooling for adaptive automated pipetting
  • Designed and 3D-printed parametric fixtures to improve robotic insertion reliability

Entrepreneurial and Translational Experience

• Product Engineer, MIT SUD Venture Program (Jan 2025)
  • Participated in team-based health-technology venture development focused on substance use disorder innovation
• Product Engineer, Nuventure Program, Northwestern University (Sep 2017 - Jun 2018)
  • Contributed to development of a medical robotics concept for radiology-guided insertion trajectory isolation

Leadership and Service

• Founder/Co-Chair, Duke University Neuroscience Experiences (DUNE) (Aug 2020 - Aug 2023)
  • Founded and launched a pilot neuroscience outreach program for underrepresented high school students
  • Coordinated school partnerships, admissions rubric, and mentor matching
  • Supported placement of 25+ students into paid research roles in Duke Neuroscience labs

Awards and Honors

• MIT SUD Venture Program (2025)
• IMPACT Neuroscience Program (2024)
• NWB-DANDI Hackathon Travel Award (2024)
• Neural Conference Travel Award (2024, 2023)
• Center for Cognitive Neuroscience Data Blitz Award (2024)
• NSF Supplement (2023)
• NEURAL Shark Tank, 3rd Place (2023)

Skills

• Programming and Modeling: Python, JAX, Linux, Git/GitHub, statistical modeling, machine learning
• Infrastructure and Deployment: Docker, NAS administration, RAID configuration, local AI deployment
• Experimental and Neurophysiology: Electrophysiology acquisition, rodent surgery, optogenetic workflows
• Systems and Prototyping: Fusion 360, 3D prototyping, Arduino/Teensy, Raspberry Pi, lab automation systems

Selected Publications and Presentations

• Schnaude Dorizan K, Kleczka KJ, Resulaj A, Alston T, Bresee CS, Hartmann MJ. A novel stimulator to investigate the tuning of multi-whisker responsive neurons for speed and direction of global motion. Journal of Neuroscience Methods (2021).
• A Generative Approach to Derive Neural Ensembles across Multiple DANDI Datasets. NWB-DANDI Hackathon (2024).
• O-SPLAT: Uncovering Latent Sources from Oscillatory Data. SFN (2024), NEURAL Conference (2024).
• Decomposing Neural Data with SPLAT. BMES (2022), Triangle SFN (2022).

Selected Engineering Projects

• Self-Hosted Infrastructure and Local AI Services
  • Built local LLM and embedding services integrated with private media/file indexing
  • Implemented resilient storage and backup workflows (RAID, snapshots, remote sync)
• NWB-DANDI Hackathon, Janelia Research Campus (Jul 2024)
  • Extended SPLAT tooling for neural-ensemble extraction across multiple NWB datasets via DANDI workflows