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Hire Dr. Casey J. M.

United States

USD 80 /hr

Mathematics PhD, MBA | Dynamic Modeling, Astrodynamics, Project Management | Java, Python, MATLAB

Profile Summary

As a highly skilled mathematician, researcher, and project manager, I bring a unique and analytical perspective to complex problems. With expertise in algorithm development and a passion for problem-solving, I am dedicated to finding efficient solutions that streamline processes and enhance functionality. As a collaborative team-builder, I strive to foster cross-functional communication and drive innovative ideas to fruition. Technical Skills: ▪ Languages: Java, Python, MATLAB, Kotlin, Julia, C++ ▪ Packages: Orekit/Hipparchus/Lang/Utils (Java), NumPy/Pandas (Python) ▪ Source Control, Documentation, Operating Systems: Git/GitHub, LaTeX/Overleaf, MS Office Suite, Google Workspace, Adobe Acrobat, MacOS, Windows, Linux Education: ▪ Doctor of Philosophy, Mathematics, Emphasis on Modeling, 12/2021 ▪ Master of Science, Mathematics, Emphasis on Time Scales, 12/2019 ▪ Master of Business Administration, General Business, xxxxxxx ▪ Bachelor of Science, Mathematics, Minor in Physics, xxxxxxx Experience: Principal Investigator, SpyDar Sensors Inc. (04/2024 – 07/2025) ▪ Served as Principal Investigator for Phase I Navy SBIR Topic N242-083, spearheading the design of a novel launch and recovery system for sea-based operations under real-world constraints. ▪ Successfully secured a $1.4M Phase II contract award by delivering compelling technical results, strategic alignment with Navy needs, and demonstrating program viability to stakeholders. ▪ Produced comprehensive technical reports and delivered live presentations to Navy leadership showcasing system-level modeling, simulation results, and conceptual validation. Research Scientist (Contract), OurSky AI (xxxxxxxxxxxx/2024) ▪ Conducted astrodynamics research exploring the use of models, including Kalman filters and multiple hypothesis tracking, to reduce object misidentification in space surveillance. ▪ Developed software tools to automate the ingestion of satellite ephemeris data for sensor calibration, improving empirical assessment of optical tracking accuracy. ▪ Authored comprehensive technical reports and implementation proposals detailing algorithmic improvements, code architecture, and system integration strategies, with forward-compatible pathways for machine learning augmentation. Research Scientist II, Slingshot Aerospace (xxxxxxxxxxxx/2023) ▪ Researched and developed advanced mathematical theories for applications to space domain awareness to determine functionality in relation to the goals of the company. ▪ Contributed to research and expansion of estimation and optimal control for dynamical systems, enhancing model accuracy and effectiveness. ▪ Built probabilistic and possibilistic frameworks applied to risk assessment and quantification associated with space object tracking to determine the method best suited for product needs. ▪ Applied fundamentals of astrodynamics to satellite orbital motion modeling, prediction, and estimation. ▪ Prototyped algorithms and core astrodynamics libraries for development of stochastic filtering algorithms to be used in the development of core capabilities. ▪ Published internal technical memos on applications of state-of-the-art mathematical advancements and their applications to communicate complex results across the company. Graduate Research, Texas Tech University Department of Mathematics (08/2017 -12/2021) ▪ Created a new approach to modeling a treatment for prostate cancer using dynamic equations to improve the representation of time-data and explore potential alternatives to prior methods. ▪ Unified the theories of discrete fractional calculus and time scale calculus to improve modeling capabilities by over 10%. ▪ Developed a Python-based data cleaning algorithm and a MATLAB-based model analysis algorithm to better understand and represent oncological data. Graduate Part-Time Instructor, Texas Tech University Department of Mathematics (08/2017 -12/2021) ▪ Developed course curriculum and taught non-STEM students in a virtual and classroom setting. Team Lead and Research Assistant, Texas Tech University Department of Physics (xxxxxxxxxxxx/2016) ▪ Acted as the team leader of the High Energy Llano Estacado Detector Collaboration, facilitating weekly meetings and overseeing the installation and use of data acquisition hardware. ▪ Automated the data acquisition pipeline to collect samples of Cherenkov radiation. Developed a C++ algorithm to detect the size, shape, and location of high energy particles using a Monte Carlo simulation.

Subject Matter Expertise

• ☆ Mathematical Biology
• ☆ Statistics
• ☆ Mathematical Statistics
• ☆ Applied Mathematics
• ☆ Mathematical Models
• ☆ Mathematics Education
• ☆ Pure Mathematics
• ☆ Calculus
• ☆ Mathematical Analysis
• ☆ Discrete Mathematics
• ☆ Curriculum Planning & Development
• ☆ Python
• ☆ Matlab
• ☆ Java
• ☆ LaTex
• ☆ Technical & Scientific Writing
• ☆ Manuscript & Journal Article Writing
• ☆ Science Communication
• ☆ Project Management

Services

• Writing
• Research
• Consulting

Writing Technical Writing, General Proofreading & Editing

Research Scientific and Technical Research

Consulting Scientific and Technical Consulting

Work Experience

Principal Investigator

SpyDar Sensors, Inc.

April 2024 - July 2025

Research Scientist (contract)

OurSky AI

March 2024 - October 2024

Research Scientist II

Slingshot Aerospace

February 2022 - May 2023

Graduate Research and Teaching Assistant

Texas Tech University

2017 - 2021

Education

Doctor of Philosophy in Mathematics (Mathematics and Statistics)

Texas Tech University

2019 - 2021

Master of Business Administration (Rawl College of Business)

Texas Tech University

2017 - 2018

Certifications

• Certification details not provided.

Publications

JOURNAL ARTICLE

Casey J. Mills (2022). An Exploration of Discrete Fractional Calculus with Applications to Intermittent Oncological Modeling. Progress in Fractional Differentiation and Applications.

Casey J. Mills (2020). A Time Scales Approach for Modeling Intermittent Hormone Therapy for Prostate Cancer . Bulletin of Mathematical Biology.