Jered Mcinerney
Data Scientist IV (LLM Researcher)
Boston, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolJered Mcinerney is a Data Scientist IV and LLM researcher who applies cutting-edge language models to healthcare problems, focusing on interpretable, minimally supervised neural systems for electronic health records. He holds a PhD in Computer Science from Northeastern University and has 11 years of experience across industry and academia, including roles at CodaMetrix, AWS, and research internships at Salesforce and Johns Hopkins. His research spans unsupervised and distantly supervised methods, multimodal representation learning, summarization with distant supervision, and techniques that bridge generative and contrastive objectives to improve clinical interpretability. Jered builds systems designed to learn from unlabeled, noisy clinical data to reduce diagnostic errors and streamline clinician workflows, while emphasizing bias monitoring and human-in-the-loop design. Unusually for an ML researcher, his background in particle physics and applied visualization informs a strong penchant for principled, data-driven engineering alongside a practical focus on deployment in regulated domains. Outside work he climbs, plays tennis, and wrestles with his dog, a reminder that he balances technical rigor with active problem-solving.
10 years of coding experience
2 years of employment as a software developer
Johns Hopkins UniversityDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Northeastern University
Github Skills (27)
transformers10
pytorch10
language-model10
python10
machine-learning10
seq2seq10
flax10
deep-learning10
tensorflow10
bert10
natural-language-processing10
transformer10
speech-recognition10
nlp10
jax10
Programming languages (4)
Github contributions (5)
dmcinerney/ehr-extraction-models
Sep 2019 - Sep 2020
This repository contains a number of models for performing conditioned extractive summarization on electronic health records.
Contributions:84 commits, 1 push in 1 year
health-recordsrecordshealthmachine-learningelectronic
dmcinerney/gloria
Nov 2021 - Feb 2023
GLoRIA: A Multimodal Global-Local Representation Learning Framework forLabel-efficient Medical Image Recognition
Contributions:33 pushes in 1 year 3 months
pytorchrepresentationimage-recognitionmedical-imagedeep-learning
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