Hezekiah Branch, MS
Hezekiah Branch is a Data Engineer and Scientist at the MGH-MIT InBRAIN Collaboration. Hezekiah is a member of the Department of Brain and Cognitive Sciences at MIT and the Department of Functional Neurosurgery at Massachusetts General Hospital. Hezekiah hails from Roxbury, Boston and is of Trinidadian heritage. He is a speaker of Brazilian Portuguese, Spanish, and Trinidadian Creole. Hezekiah received his B.S. in Cognitive and Brain Sciences from Tufts University and M.S. in Data Science from the Tufts Graduate School of Engineering. At Tufts, Hezekiah was awarded the Presidential Award for Civic Life, the highest honor bestowed to an undergraduate student. Prior to joining InBRAIN, Hezekiah contributed to genomics research in the treatment of glioblastoma multiforme (GBM) at Tufts School of Medicine, distributional semantics at Google CSRMP, and optimal transport theory in deep triplet networks at IBM Research - Almaden. He has also developed enterprise data systems, working in the Office of the CTO at Prudential Financial. In April 2023, Hezekiah's work was cited as a foundational model in medical AI in the highly cited Nature paper by Moor et al. Most recently, he was a researcher at Tufts Medical Center and the MIT Center for Biomedical Innovation, forecasting the adoption of clinical trials for curative therapies. Hezekiah’s research interests include tensor network optimization, systems neuroscience, and the bridging of cognitive neuroscience and functional neurosurgery. Since 2018, Hezekiah has directed a free coding boot camp called Code with Hezekiah, teaching data science skills to over 150 students.
Areas of Expertise:
- Causal Discovery
- Human Intracranial Neuroscience
- Medical Artificial Intelligence
- Tensor Network Representations
Projects
- Deep Tensor Decomposition of Human Intracranial Recordings of Vision
- Modeling Health Disparities in Pediatric Epilepsy with Latent Variable Modeling
- Mulitidien Rhythms of Thalamic Epilepsy in RNS (led by Danai Sakelliadou, MD)
- MIT Human Intracranial Neuroscience Course
Teaching Experience
- Founding Instructor for Code with Hezekiah
- Guest Lecturer for DATA 0201 Machine Learning, Tufts Graduate School of Arts & Sciences
- TA for AST 151 Bayesian Methods for Astrophysics Laboratory, Professor Jane Luu
- TA for CS 10: Introduction to CS, Tufts University
Timeline
Here are a few of my highlights since joining the Brain Modulation Lab!
JUNE 2023
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June 2023: Hezekiah joins the Brain Modulation Lab (BML)
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June 2023: Creates data strategy for lab and begins building technology stack
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June 2023: Launches Jira workspace for data management and project tracking
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June 2023: Begins management of data governance and documentation for NIH Data Management and Sharing Policy
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June 2023: Launches Data Needs survey to build a backlog of all lab data needs
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June 2023: Presents dashboarding vision with Tableau and Dash at BML Lab Meeting
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June 2023: Ongoing restoration of BML Turbo in collaboration with neurosurgical resident Dr. Nathan Sisterson
JULY 2023
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July 2023: Tasked with scrubbing into operating room (OR) to build ongoing expertise of surgical procedures and protocols
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July 2023: Conducts discovery phase of functional neurosurgery data ecosystem
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July 2023: Early prototypes of Airflow clinical data pipelines and data streaming in Apache Flink
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July 2023: Creates PAS group and provisions access to Radiology Imaging and Research Patient Data Registry (RPDR)
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July 2023: Start of pediatric epilepsy racial disparity project with neurosurgery
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July 2023: Develops latent variable modeling approach to clinical neurosurgical data
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July 2023: Attends the ROH Young Investigators Meeting at MIT
AUGUST 2023
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August 2023: Launches automated review process for faster access to lab data and computational resources
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August 2023: Tasked with clinical oversight of epilepsy intake and movement disorder cases
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August 2023: Enables high-performance computing (HPC) for lab with ERIS collaboration
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August 2023: Overseeing BML Turbo Taskforce dedicated to restoring outages on BML Turbo
SEPTEMBER 2023
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September 2023: Adds new standard operating procedures (SOPs) for data management and introduction to HPC
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September 2023: Deploys new pipelines for cluster health tracking and identity access management (IAM)
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September 2023: Presents review of CEBRA AI model at Kanwisher Lab meeting
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September 2023: Appointed as lead on pediatric epilepsy disparity project by Dr. Mark Richardson
OCTOBER 2023
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October 2023: Leads BML collaboration with DABI USC for publication of human intracranial data
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October 2023: Configures private lab group on ERIS with data mapping and centralized storage for HPC
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October 2023: Creates data pipeline from REDCap API to internal patient-specific databases
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October 2023: Hezekiah gives virtual talk with University College London (UCL) Medical students
NOVEMBER 2023
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November 2023: Validation of latent variable modeling with pediatric epilepsy cohort
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November 2023: Launches the Data Warehouse Taskforce for project management
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November 2023: Finalizes cost optimization and strategy for migration to AWS
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November 2023: Implements new security protocols on all lab servers for data integrity
DECEMBER 2023
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December 2023: Deploys new policies and pipelines for intracranial data sharing with MIT
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December 2023: Begins pilot of automated data backups and derivatives to AWS
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December 2023: Launch of quarterly project tracking with Qualtrics Reporting under direction of Dr. Mark Richardson
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December 2023: Completed rebuild of remote Linux server for development of MMVT
JANUARY 2024
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January 2024: Creates InBRAIN Vision data repository for Kanwisher Lab on DABI containing human intracranial data
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January 2024: Begins cognitive neuroscience training at MIT through funding from Kanwisher Lab
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January 2024: Start of intracranial category selectivity project with Kanwisher Lab
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January 2024: Renews Epic certification, completes MGB training in interventional neurology and statistical genomics
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January 2024: Attends the iEEG Data Blitz hosted by Mass General Neurosurgery
FEBRUARY 2024
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February 2024: Major milestone in transforming lab data into BIDS format
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February 2024: Begins design of MGH-MIT graduate intracranial seminar with MIT and HMS faculty
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February 2024: Coordinates regular uploads to MGH and MIT data sharing repos on DABI
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February 2024: Populates private NoSQL databases for all patients enrolled in active research studies
MARCH 2024
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March 2024: Conducts periodic code and documentation review with follow-up facilitated by Dr. Mark Richardson
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March 2024: Expansion of pediatric epilepsy cohort for neurosurgical disparity project
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March 2024: Presents preliminary research findings from initial pediatric epilepsy cohort
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March 2024: Deploys real-time data pipelines of clinical patient data from Epic for dashboarding
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March 2024: Presents functional prototypes of real-time clinical neurosurgical dashboards in Tableau
APRIL 2024
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April 2024: Pilots new data pipelines for measuring post-op neurosurgical outcomes in DBS patients
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April 2024: Leads migration of on-prem setup to AWS On Demand for scaling clinical infrastructure
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April 2024: Acquires Azure OpenAI Studio to integrate generative AI (e.g. ChatGPT) with precision medicine
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April 2024: Brainstorming session for MGH-MIT graduate intracranial seminar course
SEPTEMBER 2024
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September 2024: Coordinating launch of InBRAIN human intracranial neuroscience course at MIT
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September 2024: Additional semester of training in deep learning and causal inference at MIT
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September 2024: Establishes longitudinal models for pediatric epilepsy outcomes data
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September 2024: Makes headway on deep matrix factorization of ventral visual stream with Kanwisher Lab
OCTOBER 2024
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October 2024: Adds new intracranial datasets to DABI for Fedorenko Lab and Kanwisher Lab
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October 2024: Meets with BCS faculty to discuss computational interface for Spring 2025 course
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October 2024: Designs infrastructure of model learning on multi-site ECoG data for component finding
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October 2024: Receives honorable mention at 2024 MIT Prize for Open Data
NOVEMBER 2024
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November 2024: Proposal of human intracranial neuroscience course to MIT Education Committee
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November 2024: SOP for preprocessing of InBRAIN human intracranial data in Brainstorm
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November 2024: Latest release of InBRAIN human intracranial repo on DABI
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November 2024: Presents DeepBreath algorithm at the highly-selective 2024 MIT Policy Hackathon
Future highlights will be posted below!