Hello, my name is

Jack

I bring value from every level of the enterprise.

I am an AI and Software Engineering Manager with skills in best leadership practices.

About Me




I seek to improve your organization’s ability to create value by synthesizing software engineering and data science skills with Lean-Agile paradigms. I apply my technical and value-production skills to bridge the communication gap throughout the entire development chain.

Projects

NYPD Shooting Incidents Analysis
R Modelling Data Cleaning Statistical Analysis
NYPD Shooting Incidents Analysis

Analysis of NYPD Shooting Incidents with the following Data Science techniques

○ Importing ○ Cleaning
○ Transformation ○ Analysis
○ Visualization ○ Bias identification


along with a summary and conclusion.

Simulation of Random Walks
Python Modelling Biology
Simulation of Random Walks

Animal movement predictions through a random walk simulation. Implementation and assessment of the performance of several of movement schemes in two dimensions

  • Biased Random Walks (BRW)
  • Correlated Random Walks (CRW)
  • Biased Correlated Random Walks (BCRW)
Coarse-Grained Simulation of a Protein
Python Modelling Biology
Coarse-Grained Simulation of a Protein

Protein structure prediction through a dynamics simulation through a two dimensional coarse-grained model of a protein which consists of a chain of N amino acids. Each amino acid is represented by a circle connected to amino acids via an harmonic spring potential.

Simulation of Flocks
Python Modelling Biology Swarm Intelligence
Simulation of Flocks

Illustration of swarm intelligence through a flocking example utilizing coherent emergent behavior (flocking) of a swarm, when each agent is

  • Attracted to other agents
  • Repulsed when too close to other agents
  • Performing velocity alignment with other agents

Examination of this behavior in 2D; the swarm will be composed of N agents; each agent will be defined by its position (p) and velocity (v).

Shakespeare or not Shakespeare: that is the question
R Support Vector Machines (SVM) Nearest Shrunken Centroids (NSC) Natural Language Processing (NLP) Authorship attribution Principle Components Analysis (PCA) Bootstrap Concensus Tree (BCT) Theater
Shakespeare or not Shakespeare: that is the question

Authorship verification analysis of William Shakespeare and Thomas Middleton’s collaboration with the stylometric “rolling classification” method from the package ‘Stylo’ in the R language, utilizing supervised machine-learning classification” along with “sequential analysis” in order to inspect texts’ “stylometric signals.” Results support the hypotheses of Middleton's varying degree of contribution to "Shakespearean" plays.

How can the bees, be?
Modelling Biology Population
How can the bees, be?

Test the correlation between honeybee hive population and temperature range experienced throughout the year. Full data science cycle of

  • aggregating,
  • cleaning,
  • transforming, and
  • analyzing

the population and weather data with time series and scatter plots. The study suggests that there is a weak correlation between honeybee colony population loss and three-month temperature ranges. Further studies can contribute additional insight on the correlation between temperature and honeybee colony populations.

TinyML for Efficiency
TinyML Intelligent Computing at the Edge (IC@E)
TinyML for Efficiency

A comparison of status quo machine learning (ML) with intelligent computing at the edge (IC@E) including

  • identification of shortcomings
  • characterization of disparity
  • analysis of impacting factors


and discussion of enterprise strategies to approach the TinyML sub-industry.

Lean-Agile for Phase-Gate
Lean manufacturing Agile development Phase-Gate/Stage-Gate® Defense industry
Lean-Agile for Phase-Gate

Analysis of how Lean-Agile methodologies can increase value production in Phase-Gate-heavy industries. Leaders evaluated include

  • General Dynamics
  • Australian Institute for Regional Security
  • Siemsens
  • CIMData


and proposal of adaptation of Phase-Gate with Lean-Agile paradigms to match Digitally Transformed market rhythms.

Digital Twin Simulation
Digital Twin
Digital Twin Simulation

Capability for developing a digital representation of vehicles in digital versions of their environment.


Supported development at Lockheed Martin Co.
Fire Intelligence
Firefighting Intelligence Joint All Domain Command and Control (JADC2) 5G
Fire Intelligence

Capability for comprehensively fighting wildfires with

  • AI/ML
  • 5G
  • Joint All Domain Command and Control (JADC2).

Supporting development at Lockheed Martin Co.

Firefox Password Obfuscator
Python Obfuscation Cybersecurity Authentication Mozilla Firefox Pandas Numpy Data engineering Forward compatibility Extensibility (software)
Firefox Password Obfuscator

A program executable on an exported Mozilla Firefox browser password export to obfuscate authentication credentials. Features include

  • domain name extraction
  • selected obfuscation of username and password credentials
  • versioned output in .csv format.

Applications include further reference and lower-risk digital/physical backup.

Education

2022 - present
Masters of Engineering in Engineering Management
University of Colorado, Boulder
GPA: 4.00 / 4.00
○ Lean & Agile Management   ○ Resilience Engineering     ○ Entrepreneurship for Engineers
○ Finance for Engineering Mgrs.   ○ Digital Transformation   ○ Sustainbility Principles for Engr. Mgrs.
○ Engineering Communication     ○ Systems Engineering ○ NeuroLeadership
2021 - present
Masters of Science in Data Science
University of Colorado, Boulder
GPA: 4.00 / 4.00
○ Data Science as a Field       ○ Cybersecurity for Datascience         ○ Ethical Issues in Data Science
- 2020
Bachelors in Computer Science
University of Colorado, Boulder
GPA: 3.60 / 4.00
○ Data Structures       ○ Software Dev. Tools/Methodologies     ○ Human-Computer Interaction
○ Discrete Structures       ○ Human-Centered Computing     ○ Algorithms
○ Cognitive Science       ○ Principles of Programming Languages       ○ Computer Systems
○ Linear Algebra       ○ Dynamic Models in Biology    

Experience

Research and Development Engineer - INRIA Rennes
2025 - present

Test the correlation between honeybee hive population and temperature range experienced throughout the year. Full data science cycle of

  • analyze applicability of Data Prep Kit (lead by IBM Inc.) for applicability for programming language detection capability in software files
  • configure, test, and benchmark StarCoder LLM for programming language detection capability in software filesSupport
AI/ML Research Engineer Sr. - Lockheed Martin Co
2024 - 2025

Acting engineering mgr, architect, product owner, lead for framework for testing AI model efficiency at edge; software, DevSecOps, CI/CD, syst. eng. on satellite config. mgt. effort; systems eng., Agile transformation, Digital Transformation (DTx)

Efficient AI IRAD

  • Solicit, awarded $210k funding with IGNITE, ATC, and LM Ventures (LMV)
  • Lead, architect concept, prototype, to maturity via hybrid Waterfall/Agile, Lean Startup
  • Lead cross-org. interfaces between Space, Aero, RMS, EO business areas
  • Introduce 8+ engs. to 6+ inner-/open-source technologies from AI Factory
  • Demo savings of $10 – 24k (70 – 150 hrs) per use case, hardware in the loop (HWIL)
  • Exhibit results at DoD Maintenance Symposium 2024, 25 to military customers Present, demo to Code.LM; AI Summit
  • Co-lead, consult Michigan State U. academic engagement
  • Co-lead (with LM cyber Fellows), present, win 1/15 teams for feasible 1LMx strategy for program integration

Software Factory (SWF) & Next Generation Geo (NGG) programs

  • Lead cross-team interface with external teams to establish initial SE and ConOps protocols for configuration mgt.
  • Establish versioning protocol for SE protocols to co-habitate software-systems eng. efforts

SDA Wildfire program

  • Streamline Systems Engineering, Integration & Testing (SEIT) functions via SME input and persistent-scalable Confluence hierarchy, issue-tracking function via Jira-Agile Hive
  • Establish Source of Truth (SoT) practices/tracking-mechanisms for 15+ teams, 2 tranches
AI/ML Research Engineer - Lockheed Martin Co
2022 - 2024

Develop, consult, and lead AI-integration and fundamental Digital Transformation projects with the Advanced Technology Center; contributing to the Cognitive Mission Manager, contributed to the Cognitive Modules.

  • Leading multiple ‘seedling’ R&D to develop an architectural runway for MLOps model efficiency testing
  • Leading collaboration with Latent AI, a Lockheed Martin ventures portfolio company
  • Lead and consult multiple university collaborations
  • Wrote and submitted 5 proposals for internal R&D; received acceptance for 3; propose to government R&D sponsors
  • Identifying, mastering, and harnessing novel/state-of-the-art AI algorithms for enterprise introduction; delivering at complete tech. readiness level for injection into production
  • Leading/coaching teams on Agile processes, Scrum master alignment, and facilitated JIRA, Slack adoption
  • Developing DataOps Kubeflow pipelines for AI/ML for cleaning, munging, preprocessing, and translation
  • Increase algorithm efficiency, develop/scale containerized orchestration with Kubernetes/Kafka/Docker in AWS, database communication in MongoDB/LakeFS
Software Engineer - Lockheed Martin Co
2021 - 2022

Developed AI/ML-powered software and customer documentation in an Agile environment in support of the Digital Twin simulator at LM Space

  • Develop aircraft simulation software in C++, Python and Docker
  • Develop customer-facing documentation/training in GitLab Markdown/Confluence
  • Utilize Agile, Kanban development methodologies with JIRA, Confluence, and Slack
  • Integrated AI/ML model powering to increase model accuracy and efficacy
  • Aligned stakeholder requirements, defined problem and delivered complete implementation
  • Mentored Data Science interns from onboarding through development to project completion

Get in Touch

My inbox is always open, whether you have a question or would like to say hello!