CV

Curriculum vitae outlining academic and professional background, qualifications, publications, awards, and research interests.

Contact Information

Name Marlan McInnes-Taylor
Professional Title AI/ML Researcher & Engineer
Email mmcinnestaylor@gmail.com
Location Austin, Texas

Professional Summary

AI/ML researcher and engineer with an M.S. in Computer Science from The University of Texas at Austin and experience in continual learning, biologically inspired machine learning, generative modeling, deep learning, and computer vision. Research focuses on developing adaptable, data-efficient learning systems, complemented by engineering experience in model training, performance optimization, and cross-platform deployment.

Experience

  • 2020 - 2025

    Tallahassee, FL

    Software Engineer / Infrastructure Lead
    Association for Computing Machinery FSU Student Chapter
    Built and operated the production platform and infrastructure for ACM at FSU’s semesterly programming contests, leading full-stack development, deployment, and multi-year maintenance.
    • Architected and maintained a containerized, multi-site production environment supporting the contest registration and management platform, two DOMjudge instances, and other chapter web properties.
    • Restored and provisioned a Dell PowerEdge 2900, installed it in the FSU Computer Science server room, and configured it as a Docker Swarm manager for production workloads.
    • Implemented container orchestration, reverse proxying, automated HTTPS, and cluster administration using Docker Swarm, nginx-proxy-manager, acme-companion, and Portainer.
    • Developed centralized logging and archival workflows using Docker Ingress Routing Daemon, Logspout, and Papertail, preserving production logs in AWS S3 for long-term analysis.
    • Authored a comprehensive LaTeX technical manual covering system architecture, deployment, maintenance, and contest operations; mentored contributors and trained the next primary maintainer to ensure a sustainable handoff.
  • 2022 - 2025

    Austin, TX

    Graduate Researcher
    Neural Networks Research Group, UT Austin
    • Advisor: Risto Miikkulainen
  • 2022 - 2025

    Austin, TX

    Graduate Researcher
    Brain-Behavior-Computation Lab, UT Austin
    • Advisor: Xue-Xin Wei
  • 2023 - 2023

    Austin, TX

    M.S. Admissions Committee Student Reviewer
    UT Austin Department of Computer Science
    Reviewed of applications to the on-campus MSCS program for the Fall 2023 admissions cycle.
  • 2021 - 2022

    Tallahassee, FL

    Application Engineer - Computer Vision
    i2x Solutions
    Led the upgrade of the computer vision pipeline for a cross-platform mobile golf putt analysis application built with Xamarin, C#, and Swift.
    • Diagnosed a critical iOS inference bottleneck by identifying that the existing quantized TensorFlow object detection model could not use GPU acceleration on iPhone and instead fell back to CPU execution, resulting in substantially higher latency than on Android.
    • Reduced iPhone per-frame inference time from the tens of seconds to under 1–2 seconds by selecting, tuning, and deploying a MobileNetV2-based object detection model that supported efficient GPU inference across both iOS and Android, improving platform compatibility and deployment viability.
    • Cut end-to-end iPhone video processing time from multiple minutes to approximately 30–45 seconds, substantially improving usability on iOS devices.
    • Built a reusable Jupyter-based training pipeline with the TensorFlow Object Detection API, enabling future model retraining and experimentation.
    • Documented the end-to-end training workflow to make continued model development accessible to team members without deep ML experience.
    • Updated Swift and C# inference code to support the revised model outputs and deployment pipeline.
    • Improved Android inference performance by enabling NPU-based model execution where supported by device hardware.
    • Increased dataset quality by correcting bounding box and image label annotation errors used in model tuning.
    • Delivered a comprehensive technical handoff for management documenting system changes, tooling, and recommendations for future development.
  • 2018 - 2021

    Tallahassee, FL

    Undergraduate Teaching Assistant
    Florida State University
    Supported instruction for multiple computer science courses across 7 semesters through weekly discussion sections, office hours, grading, and student mentorship.
    • Guided students in understanding technical concepts, debugging assignments, improving problem-solving skills, and exam preparation.
    • Created weekly discussion review materials, including example programs and PowerPoint slides, and developed exam preparation resources to reinforce key course concepts and support student learning.
  • 2020 - 2021

    Tallahassee, FL

    President Emeritus
    Association for Computing Machinery FSU Student Chapter
    Primary advisor to the incoming executive board on chapter operations, including paperwork deadlines, event planning, and organizational continuity.
    • Supported the chapter president as a deputy to help manage leadership workload and maintain execution across initiatives.
    • Documented and helped standardize annual executive board transitions to create a more sustainable leadership handoff process.
  • 2020 - 2021

    Tallahassee, FL

    Undergraduate Researcher
    USER Lab, Florida State University
    Investigated machine learning methods for automating software traceability link recovery between requirements, use cases, and source code, reducing the manual effort needed to connect related development artifacts.
    • Built and evaluated a shallow neural network using word embeddings to classify valid and invalid traceability links across 6 benchmark datasets.
    • Developed an end-to-end preprocessing and modeling pipeline using Python, TensorFlow, NLTK, and scikit-learn, including tokenization, stemming, feature preparation, training, and validation.
    • Improved robustness on imbalanced datasets through SMOTE-based class balancing and repeated 10-fold cross-validation across 50 trials.
    • Achieved consistently strong precision, recall, and F1 scores across the evaluated datasets, demonstrating the potential of machine learning for software traceability recovery.
    • Co-authored a research paper with faculty mentor Dr. Chris Mills and submitted it to the student research competition at the CCSC Southeastern Conference.
  • 2019 - 2020

    Tallahassee, FL

    Chapter President
    Association for Computing Machinery FSU Student Chapter
    Led the student ACM chapter and served as the primary speaker at chapter meetings.
    • Expanded chapter programming to include AI, research, and academically oriented events while maintaining strong career-focused programming.
    • Rebuilt the chapter website in WordPress to improve the chapter’s digital presence and communication with members.
    • Negotiated the merger of ACM with the university’s Women in Computer Science (WiCS) chapter, reducing event conflicts and redundant programming while helping both organizations better align around their core missions and strengths.
    • Developed partnerships with other computer science, cybersecurity, and IT-related student organizations to increase collaboration and broaden member opportunities.
    • Diversified event offerings, secured new sponsorship support, and helped increase turnout at chapter events.
  • 2018 - 2019

    Tallahassee, FL

    Treasurer
    Association for Computing Machinery FSU Student Chapter
    Managed chapter budgets and handled financial coordination for the organization.
    • Oversaw reimbursement requests and financial submissions to the FSU Department of Computer Science.
    • Supported chapter operations by maintaining budget-related administrative processes.
  • 2017 - 2018

    Tallahassee, FL

    Social Chair
    Association for Computing Machinery FSU Student Chapter
    Managed the chapter’s social media presence and communications.
    • Increased member engagement through consistent, approachable, and community-focused messaging.
    • Contributed to improved event attendance by strengthening chapter visibility and outreach.
  • 2012 - 2016

    Jacksonville, FL

    Information Technology Support Contractor
    Northeast Florida Regional Council
    Provided IT support for a regional government agency, including hardware and software maintenance, troubleshooting, and repair.
  • 2009 - 2016

    Jacksonville, FL

    Quality Control Analyst
    First Florida Credit Union
    Consumer loan documentation auditor responsible for ensuring compliance with internal guidelines and applicable state and federal regulations.

Education

  • 2021 - 2025

    Austin, TX

    M.S.
    The University of Texas at Austin
    Computer Science
    • Thesis: Deep Generative Similarity-Weighted Learning (DGSWIL)
    • Advisors: Risto Miikkulainen, Xue-Xin Wei
    • Minor: Neuroscience
    • Involvement: Center for Theoretical and Computational Neuroscience Journal Club
  • 2016 - 2021

    Tallahassee, FL

    B.S.
    Florida State University
    Computer Science
    • Thesis: Skin Cancer Detection and Classification Using an Artificial Neural Network
    • Advisors: Sonia Haiduc, Sharanya Jayaraman
    • Minor: Physics
    • Involvement: Association for Computing Machinery Student Chapter, ACM at FSU Programming Contest, Honors in the Major Program
  • 2016 - 2021

    Tallahassee, FL

    B.S.
    Florida State University
    Applied & Computational Mathematics
    • Minor: Statistics
  • 2006 - 2009

    Gainesville, FL

    B.A.
    University of Florida
    Philosophy
    • Minor: Business
  • 2001 - 2005

    Jacksonville, FL

    I.B.
    Stanton College Preparatory School
    International Baccalaureate Program

Awards

Publications

  • 2025
    Deep Generative Similarity-Weighted Interleaved Learning
    M.S. thesis, The University of Texas at Austin

    Developed DGSWIL, a reproducible continual-learning framework combining class-conditional generative replay with feature-space similarity-weighted rehearsal to avoid retaining raw training data. Experiments on Fashion-MNIST and CIFAR-10 found no consistent improvement over strong replay baselines and traced the shortfall to representation drift, generator-classifier optimization trade-offs, and generator-target mismatch, clarifying key limitations of similarity-guided synthetic replay.

  • 2020
    Automating Software Traceability Link Recovery and Maintenance Using Word Embeddings Within a Shallow Neural Network
    Addendum to Proceedings of the 34th CCSC Southeastern Conference, vol. 34, pp. 14–16

    Developed and evaluated a shallow neural network using word embeddings to automate the recovery of traceability links between text-based software artifacts. Across six benchmark datasets and 50 trials of 10-fold cross-validation, the model achieved F1 scores ranging from 0.85 to 0.97, demonstrating the feasibility of machine-learning-based traceability recovery.

  • 2020
    Skin Cancer Detection and Classification Using an Artificial Neural Network
    B.S. thesis, Florida State University

    Developed an end-to-end, seven-class skin-lesion classification system using transfer learning with Inception v3 on 10,015 dermoscopic images from the ISIC 2018 HAM10000 dataset. Trained and evaluated the model with five-fold cross-validation on an NVIDIA Jetson Nano, and deployed it as a containerized Flask application for portable, low-power inference.

Skills

Languages: Python, C/C++, C#, Swift
AI/ML: PyTorch, TensorFlow, numpy, scikit-learn
Tools: Docker, Jupyter, Git, Linux, LaTeX
Web: Django, Flask, Jekyll, Bootstrap

Interests

Learning & Adaptation: Continual Learning, Lifelong Learning, Deep Learning, Transfer Learning, Catastrophic Forgetting, Data-Efficient Learning Systems, Deep Learning
Generative & Perceptual Modeling: Generative Modeling, Computer Vision
Biologically Inspired Intelligence: Biologically Inspired Machine Learning, Computational Neuroscience, Human Learning & Memory, Complementary Learning Systems

Certificates

  • Computational Neuroscience - Neuromatch Academy (2022)

Languages

English : Native speaker
Spanish : Elementary speaker