プロフィール詳細

プロジェクトを作成

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Dr. Connor M.に依頼

United States

PhD-trained ML scientist with 8+ years in fundamental research and building production ML/CV systems.

プロフィール概要

I am a PhD-trained machine learning scientist with 8+ years of experience designing, deploying, and operationalizing production ML and computer vision systems across industry, research, and government applications. My expertise spans deep learning, weakly supervised and noisy-label learning, object detection, segmentation, and multimodal sensing, with a strong emphasis on taking models from research to reliable production via MLOps best practices (AWS, Docker, CI/CD, monitoring). I have delivered mission-critical models for commercial satellite platforms and U.S. defense agencies, led end-to-end model development with measurable impact, and collaborate effectively with engineers, product teams, and stakeholders to translate ambiguous problems into scalable, high-value ML solutions.

専門分野

• ☆ Remote Sensing
• ☆ Data Analysis
• ☆ Image Processing
• ☆ Computer Simulation/Computational Modeling
• ☆ Algorithm Design
• ☆ Predictive Modeling & Analytics
• ☆ Data Processing
• ☆ Data Exploration
• ☆ Cluster Analysis
• ☆ Data Visualization
• ☆ Data Manipulation
• ☆ Machine Learning
• ☆ Data Cleaning
• ☆ Neural Networks
• ☆ Pattern Recognition
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Computer Vision
• ☆ Fuzzy Logic
• ☆ Python
• ☆ Matlab
• ☆ SQL
• ☆ Tensorflow
• ☆ Scikit-learn
• ☆ Hypothesis
• ☆ Peer Review
• ☆ Research Methodology
• ☆ Literature Search
• ☆ Instructional Webinars
• ☆ Skills Training
• ☆ Technical & Scientific Writing
• ☆ Manuscript & Journal Article Writing
• ☆ Instructional Materials
• ☆ Textbook Content Writing
• ☆ Science Communication
• ☆ Literature Review
• ☆ Traditional/Narrative Literature Review
• ☆ Systematic Literature Review
• ☆ Scientific Proofreading & Editing

サービス

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing Technical Writing

Research Scientific and Technical Research, Systematic Literature Review

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

Product Development Prototyping

職務経験

Sr. Machine Learning Scientist

Orbital Sidekick

8月 2022 - 現在

Graduate Research Assistant

University of Florida

8月 2017 - 8月 2032

Sr. Machine Learning Scientist

Orbital Sidekick

8月 2022 - 1月 2026

Doctoral Dissertation Researcher

University of Florida

8月 2020 - 8月 2022

Graduate Research Staff

Office of Naval Research

8月 2020 - 8月 2022

Graduate Teacher

University of Florida

8月 2018 - 8月 2022

Graduate Research Staff

Army Research Office

8月 2017 - 8月 2020

学歴

Doctor of Philosophy (Electrical and Computer Engineering)

University of Florida

8月 2017 - 8月 2032

Ph.D.

University of Florida

8月 2017 - 8月 2022

Bachelor of Science (Electrical and Computer Engineering)

Oklahoma State University

1月 2015 - 5月 2017

Minor (Mathematics)

Oklahoma State University

1月 2015 - 5月 2017

Bachelors

Oklahoma State University

8月 2013 - 5月 2017

Bachelor of Science (Did not Complete) (Electrical and Computer Engineering)

Missouri University of Science and Technology

8月 2013 - 12月 2014

認定資格

• Certification in Machine Learning

  University of Florida

  8月 2022 - 現在

出版物

JOURNAL ARTICLE

Connor H. McCurley, Alina Zare (2024). Segmentation Pseudolabel Generation Using the Multiple Instance Learning Choquet Integral . IEEE Transactions on Fuzzy Systems.

Joshua Peeples, Sarah Walker, Connor Mccurley, Alina Zare, James Keller, Weihuang Xu(2022). Divergence Regulated Encoder Network for Joint Dimensionality Reduction and Classification . IEEE Geoscience and Remote Sensing Letters. 19. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1--5. Institute of Electrical and Electronics Engineers ({IEEE})

(2019). Comparison of Hand-held WEMI Target Detection Algorithms. Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV.

(2019). Developing Spectral Libraries Using Multiple Target Multiple Instance Adaptive Cosine/Coherence Estimator. 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1-5.

(2019). Investigation of Initialization Strategies for the Multiple Instance Adaptive Cosine Estimator. Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV.

Multi-Target Multiple Instance Learning for Hyperspectral Target Detection. IEEE TGRS.

CONFERENCE PAPER

C.H. McCurley and J. Bocinsky and A. Zare(2019). Comparison of Hand-held WEMI Target Detection Algorithms.

S. Zou and C.H. McCurley and A. Zare and C. Jiao and S. Meerdink and J. Bocinsky and N. Kroeger and P. Gader(2019). Target Detection Given Uncertain Training Data.