CV
Education
Massachusetts Institute of Technology (MIT), Cambridge, MA
Ph.D. Candidate, Brain and Cognitive Sciences (currently on hold)
Sept 2021 – Present
Master’s Thesis: C. elegans as a Platform for Multimodal Neural Data Integration
B.S. in Computation and Cognition, Minor in Statistics and Data Science
Sept 2017 – June 2021
Professional Experience
Numenta, Inc., Cambridge, MA
Machine Learning Research Intern
June 2025 – September 2025
- Developed reverse distillation methods for transferring sparsity patterns from large teacher models to smaller student models
- Designed sparse stack selector mechanisms for selectively activating submodules in stacked architectures
- Contributed to external collaboration exploring LLM inference on new efficient computing hardware, focusing on scaling sparse models and activation routing
Research Experience
Graduate Research Assistant, McGovern Institute for Brain Research, MIT
March 2022 – Present
- Developed large-scale data pipelines for processing multimodal C. elegans neural datasets
- Modeled neural population dynamics using graph-based architectures and self-supervised learning
- Integrated transcriptomic and anatomical data for neuron identity prediction tasks
- Mentored junior students in computational neuroscience methods and data wrangling
Graduate Rotation Student, Brain and Cognitive Sciences, MIT
Oct 2021 – Feb 2022
Summer Course Participant, Methods in Computational Neuroscience, MBL
July 2023 – Aug 2023
Summer Course Participant, Neurophysics of Locomotion, KITP
July 2022 – Aug 2022
ELO Intern, MIT International Science and Technology Initiatives, Remote
June 2020 – Aug 2020
Undergraduate Researcher, UROP, McGovern Institute, MIT
June 2018 – Dec 2020
Work Experience
Triplet Therapeutics, Cambridge, MA
Bioinformatics Intern
Jan 2021 – March 2021
Software Development Intern
July 2019 – Sept 2019
Saint Lucia Distillers Group of Companies, Castries, St. Lucia
Quality Assurance Analyst
July 2016 — June 2017
Teaching Experience
Teaching Assistant, MIT, Cambridge, MA
Principles of Neural Computation in Brains and Machines
Feb 2023 – May 2023
Emergent Computations in Distributed Neural Circuits
Sept 2023 – Dec 2023
Tutor/Lab Assistant, MIT, Cambridge, MA
Fundamentals of Programming
Sept 2018 – Dec 2018
Introduction to Neural Computation
Feb 2019 – May 2019
MIT Global Teaching Labs
Instructor - Cardiff, Wales
Jan 2020
Instructor - Johannesburg, ZAF
Jan 2019
Publications
Preprints:
- Simeon et al. (2024). “Scaling Properties For ANN Models of a Small Nervous System.” IEEE Xplore
- Haspel et al. (2023). “To Reverse Engineer an Entire Nervous System.” arXiv
Acknowledged In:
- Verbe et al. (2024). “Flies Tune the Sensitivity of Their Multifunctional Gyroscope.” bioRxiv
- Friedman et al. (2020). “Striosomes Mediate Value-Based Learning Vulnerable in Age ….” Cell
Technical Skills
Programming: Python, Julia, C++, SQL, MATLAB
ML Frameworks: PyTorch, PyTorch Geometric, Hugging Face, Scikit-learn
Data Tools: NumPy, pandas, Matplotlib, OpenAI API, TensorBoard
Scientific Tools: NEURON, NetworkX, Graphviz, SciPy
DevOps / HPC: SLURM, Conda, AWS, Docker, Git, CI/CD
Soft Skills: Cross-disciplinary collaboration, mentoring, reproducible research, technical writing
Coursework
AI & ML, Statistics & Data Science, Statistical Learning, Discrete Math & Linear Algebra, Neural Circuits & Computational Neuroscience, Developmental Biology, Molecular & Cellular Neuroscience
Leadership and Honors
Leadership:
- President, IEEE-HKN (Eta Kappa Nu) Honor Society — MIT Chapter
- Secretary, Fraternity Leadership Role
- Mentor and advocate for open science, data transparency, and interdisciplinary education
Honors:
- Oxford Rhodes Finalist, Commonwealth Caribbean
- Instructor, SPISE 2020 Computer Programming
- Beta Chapter of Theta Chi at MIT