Michael R. Martin

About

• Neural and Gaussian-based representations for interactive analysis of complex volumetric data
• Mechanistic interpretability of structured signals in generative vision models
• Embodied interactive systems as experimental platforms for studying representation behavior under physical and perceptual constraints

Across these efforts, he adopts an inquiry-driven methodology in which system behavior—such as rendering dynamics, latency, perceptual stability, and failure modes—serves as a primary source of empirical evidence, enabling representational assumptions to be tested directly through execution.

Current Research

Mechanistic Interpretability of Structured Signals in Generative Vision Systems

Examining how structured perturbations propagate through generative vision models to expose internal mechanisms, feature hierarchies, and robustness properties.

Summary arXiv Presentation Proposal Code

Neural Representations for Interactive Exploration of Complex Volumetric Data

Developing neural scene and field representations that support interactive analysis and visualization of high-dimensional volumetric datasets.

Summary Proposal

Embodied XR Systems for Immersive Interaction

Designing embodied XR systems that integrate real-time graphics, spatial audio, and intelligent agents for immersive interaction and therapeutic applications.

Summary Presentation Demo Code

Education

Research & Professional Experience

Ph.D. Graduate Student Researcher, UC Davis Fellowship, Visualization & Interface Design Innovation (VIDi) Lab, University of California, Davis, CA, September 2025 – Present
Advisor: Dr. Kwan-Liu Ma

• Diffusion-based generative model interpretability: (Project Summary · Code · Proposal · Presentation · Technical Report · Video · arXiv): Designed and developed perturbation-based frameworks for robustness and feature-level interpretability of text-to-image diffusion models; first-author arXiv preprint and journal manuscript in preparation.
• ProneVR (constraint-aware, controller-free XR systems) (Project Summary · Presentation · Code · Demo): Designed and implemented an immersive therapeutic VR environment integrating real-time rendering, shader-based visual effects, spatial audio, interactive simulation, and AI-driven agent behaviors; led system evaluation at the clinical study at UC Davis Health; first-author manuscript in preparation.
• Neural and Gaussian scene representations for volumetric visualization (Project Summary): Authored and developed a research proposal for real-time VR visualization of unstructured volumetric data using Gaussian splatting and neural-guided sampling, encompassing a scalable OpenXR-based system supporting multivariate transfer-function editing and AI-accelerated rendering.
• GPU-Accelerated Time-Varying Volumetric Visualization: Implemented CUDA-based pipelines for high-performance time-varying volumetric visualization.
• Graduate Mentorship: Provided graduate-level mentorship to a master's student on XR system architecture and XAI methodologies for generative image models.

NASA Undergraduate Research Fellow – Nevada NASA Space Grant, Desert Research Institute (DRI), Reno, NV & University of Nevada, Reno, NV, May 2024 – August 2025

• Developed a NASA Space Grant-funded research proposal, "Advancing Predictive Modeling in Earth Science through Artificial Intelligence" (ResearchGate).
• Designed ensemble and deep learning models to predict wildfire and smoke dispersion.
• Analyzed large-scale NASA remote sensing data related to wildfires in western U.S.
• First author of a manuscript in preparation for peer-reviewed submission.
• Presented research at the Data Science Conference and the Nevada NASA Statewide Meeting.

Researcher & Software Developer – Science & Mathematics of AI Modeling for Research and Technology (SMART) Laboratory, Desert Research Institute, Reno, NV, May 2023 – August 2025

• Contributed to code development and experimental validation for lab publications.
• Contributed to developing detailed explainable AI (XAI) and ML tasks for proposals submitted to NOAA & CAL FIRE.
• Developed ML models for wildfire prediction as part of NASA EBSCoR Projects.
• Co-authored two peer-reviewed papers (one published and one under review.)
• Presented research as first author at the AMS national conference.

Research Assistant – Organic Analytical Lab, Desert Research Institute, NV, May 2022 – May 2023

• Developed code for data analysis and visualization for an NIH-funded research project.
• Processed large-scale datasets and contributed to analytical discussions.
• Prepared technical reports summarizing research findings.

Research Intern – Robotics Laboratory, University of Nevada, Reno, NV, October 2018 – May 2019
Advisor: Dr. Monica Nicolescu

• Assisted with C++ modules for robotic simulations.

Selected Publications & Preprints

• Martin, M. R., Chan, G., Ma, K.-L. (2025). Interpreting Structured Perturbations in Image Protection Methods for Diffusion Models. arXiv:2512.08329 (Preprint)
• Martin, M. R., Chan, G., Jung, M.J., Ma, K.-L (2025). ProneVR: A Posture-Aware Real-Time VR Rendering Architecture for Embodied Immersive Computing. (Manuscript in preparation)

Additional Peer-Reviewed Publications

• Barjeste Vaezi, R., Martin, M. R., Hosseinpour, F. E. (2025). Impacts of Wildfire Smoke Aerosols on Radiation, Clouds, Precipitation, Climate, and Air Quality. Atmospheric Environment X, Elsevier, 26, 100322. DOI (Published)
• Li, K., Martin, M. R., Wang, X. (2025). Stepwise Clustered Ensemble (SCE): An R Package for Interpretable and Robust Regression in Environmental Modeling. Manuscript Number: ENVSOFT-D-25-02742 Journal of Environmental Modelling and Software (Under Review · Manuscript #ENVSOFT-D-25-02742)
• Martin, M. R., Yang, L., Moosmüller, H. (2025). Deep Learning Framework for Predicting Wildfire Smoke Dispersion from Satellite Remote Sensing Data. In preparation (In Preparation).

Selected Talks & Presentations

• Martin, M. R., Chan, G., Ma, K.-L. (2025). Explainable AI for Analyzing the Impacts of Data Purification on Image Models. VIDi Labs, UC Davis, Nov 9, 2025. (Talk). https://doi.org/10.13140/RG.2.2.21023.42408
• Martin, M. R., Chan, G., Ma, K.-L. (2025). ProneVR: Design and Evaluation of a Controller-Free Immersive VR for Pain Management. Pain Medicine Dept., UC Davis Health, Nov 24, 2025. (Invited Talk). https://github.com/MichaelMartinTech/ProneVR-Demo, https://doi.org/10.13140/RG.2.2.17466.86729
• Martin, M. R., Chan, G., Ma, K.-L. (2025). Visualizing the Impact of Data Perturbation on Image Models using Explainable AI. VIDi Lab, UC Davis, Dec 5, 2025. (Talk). https://doi.org/10.13140/RG.2.2.32382.45126

Research Proposals

• Martin, M. R. (2025). AI for Volumetric Exploration in Reality (AIVER): Real-Time Virtual Reality Visualization of Unstructured Volumes Using Gaussian Splatting and AI-Accelerated Rendering. Independent research proposal, Nov 2025. (Active). Conceived core ideas, designed the full methodology, and authored the complete proposal. (ResearchGate)
• Martin, M. R., Chan, G. (2025). Visualizing the Impact of Data Perturbation on Text-to-Image Models using Explainable AI. Research proposal submitted to UC Davis, Oct 2025. (Active). Led the project; conceived, designed, and authored the complete proposal. (ResearchGate)
• Martin, M. R. (2024). Advancing Predictive Modeling in Earth Science through AI. NASA-funded research proposal, Jan 2024. (Completed). Principal Student Investigator; conceived, designed, and authored the full proposal. (ResearchGate)
• Martin, M. R., Yang, L., Moosmüller, H. (2024). Enhancing Wildfire Predictability with Physics-Guided AI/ML. CAL FIRE-funded research proposal. (Funded). Contributed to research development and machine learning methodology.

Other Conference Publications

• Martin, M. R. & Chan, G. (2025). Explanative AI for Analyzing the Impacts of Data Purification on Image Models , Explainable AI using Visualization, University of California, Davis (Talk). ResearchGate
• Martin, M. R., Yang, L., Moosmüller, H. (2025). Advancing Earth Science Predictive Modeling through Machine Learning and Deep Learning: A Multidisciplinary Approach 2025 Nevada NASA Space Grant Statewide Meeting NASA ResearchGate (Poster Presentation)
• Martin, M. R., Yang, L., Hosseinpour, F. (2025). Leveraging Machine Learning and NASA Satellite Data to Improve Wildfire Smoke Prediction and Environmental Insights. Data Science Conference, Reno, NV, February 18–20, 2025. ResearchGate (Poster Presentation)
• Martin, M. R., Yang, L., Hosseinpour, F. (2025). Harnessing Machine Learning and NASA Satellite Big Data for Enhanced Wildfire Smoke Prediction and Air Quality Forecasting. Data Science Conference, Reno, NV, February 18–20, 2025. ResearchGate Invited Undergraduate Speaker, Research Lightning Talk (Panel of Speakers)
• Martin, M. R., Mehdizadeh, G., Barjeste Vaezi, R., Erfani, E., Hosseinpour, F. E. (2024). Predictive Modeling in Environmental Science with Machine Learning Algorithms. American Meteorological Society (AMS) 104th Annual Meeting, Baltimore, MD, January 29, 2024. ResearchGate (Poster Presentation)
• Barjeste Vaezi, R., Martin, M. R., Hosseinpour, F. E. (2024). Machine Learning for Exploring Wildfire Smoke Emissions: A Data-Driven Approach. 2024 Nevada NASA Statewide Meeting, April 2024. ResearchGate (Talk)
• Barjeste Vaezi, R., Mehdizadeh, G., Martin, M. R., Hosseinpour, F. E. (2024). Machine Learning Approach for Enhanced Understanding of California’s Wildfire Smoke. American Meteorological Society (AMS) 104th Annual Meeting, Baltimore, MD, January 28–February 1, 2024. ResearchGate (Poster Presentation)
• Mehdizadeh, G., Hosseinpour, F. E., Martin, M. R., Barjeste Vaezi, R., Erfani, E., McDonough, F. (2024). Cloud Seeding Effects on Snowfall: Insights from Microphysical Model and Satellite Remote Sensing. American Meteorological Society (AMS) 104th Annual Meeting, Baltimore, MD, January 28–February 1, 2024. ResearchGate (Poster Presentation)
• Martin, M. R., Cao, R., Mamaril, J., Marsala, M. (2024). Development of an Innovative Mentorship Platform: Plato. Innovation Day Competition, University of Nevada, Reno, NV, May 2024. ResearchGate (Oral Presentation) Public Choice Award Winner
• Martin, M. R., Cao, R., Jones, J., Mamaril, J., Marsala, M. (2024). Innovative Mentorship Platform: Plato. Sontag Entrepreneurship Competition, University of Nevada, Reno, NV, January 2024. ResearchGate (Pitch Presentation) Round 2 Winner

Final Technical Reports

• Martin, M. R., Chan, G. (2025). Explainable AI (XAI) for Visualizing the Impact of Data Perturbation on Image Models. (ResearchGate)
• Martin, M. R. (2025). Advancing Predictive Modeling in Earth Science through Artificial Intelligence. Final Technical Report to NASA Space Grant Program.
• Martin, M. R., Cao, R., Mamaril, J., Marsala, M. (2024). Development of an Innovative Mentorship Platform: Plato. Undergraduate Capstone Project, University of Nevada, Reno, 171 pp. ResearchGate (Code)

Selected Projects & Systems

Real-Time VR Volume Rendering System — UC Davis (2025 – present)
Developing a VR volume-rendering pipeline integrating OpenXR with the OVR renderer and exploring Gaussian-splatting acceleration. Collaborator: Dr. David Bauer (Meta) • Advisor: Dr. Kwan-Liu Ma.
ProneVR Project — UC Davis (2025 – present)
Developed an immersive therapeutic VR platform integrating real-time rendering, shader-based visual effects, spatial acoustics, and AI-driven interactive simulation. Advisor: Dr. Kwan-Liu Ma.
Explainable AI for Text-to-Image Diffusion Models — UC Davis (2025 – present)
Investigating the impact of data perturbation on diffusion models using explainable-AI techniques to interpret model behavior, protection robustness, and feature-level responses to artist-focused poisoning methods. Collaborator: Garrick Chan • Advisor: Dr. Kwan-Liu Ma.

Additional Projects & Leadership

SensePhase — Independent R&D (2025 – present)
Independent R&D in AI, AR/VR, interactive media, computer graphics, and explainable AI systems.
Fire Season Simulation Project — ACM Hackathon (2025)
Developed a real-time wildfire simulation with grid-based procedural terrain, raycasting-based interaction, adaptive AI balancing, and interactive UI systems (Godot).
VR Software for Medical/Ocular Diagnosis (2024)
Developed a VR-based visual field assessment prototype in Unity (C#), integrating interface design and desktop simulation workflows to explore software-based ophthalmic diagnostics. (Patent in progress)
Plato Mentorship Platform – Capstone Project (2023 – 2024)
Designed and implemented a scalable web-based mentorship platform using Svelte/SvelteKit, Firebase, and API integrations; developed matching logic and user interface systems (GitHub)
Interactive Media & Simulation Prototypes – Independent (2016 – 2024)
• Built real-time interactive simulation systems with 2D/3D animation, rendering, procedural visuals, physics, AI behaviors, audio-visual integration, 3D acoustic feedback, lighting, raycasting, database systems, and performance-optimized pipelines using engines such as Unity and Godot.
• Created simulation prototypes, including a naval navigation system with AI pathfinding (GitHub), a Solar system model (GitHub), a Breakthrough chess variant with AI opponent (GitHub), and an 8-Puzzle solver visualizing search algorithms (GitHub).
Electronic Music, Spatial Audio & Sound Design – Independent (2016 – present)
Self-directed exploration of digital sound design, spatial audio, and aucoustics simulation acoustics simulation, with applications to interactive and immersive media, including VR environments

Grants & Fellowships

• Excellence Graduate Fellowship, Graduate Group in Computer Science (GGCS), University of California, Davis (2025 – 2026).
• NASA Space Grant Undergraduate Fellowship, Nevada NASA Programs (2024 – 2025) Awarded for an independent research proposal in AI/ML for environmental modeling..
• Merit-Based Computer Science Fellowship, University of Washington (2019 – 2020).
• Millennium Scholarship (Merit-Based), Nevada State Treasurer's office (2020 – 2024).

Honors & Awards

• ACM Hackathon Winner – Public Choice Award, University of Nevada, Reno, May 2025.
  Recognized for developing Fire Season, an interactive media project completed in under 30 hours at a highly competitive Northern Nevada hackathon with over 100 participants.
• Public Choice Award, Innovation Day Competition, University of Nevada-Reno, NV, May 2024
  Selected among 300+ engineering students from seven disciplines for an innovative capstone project.
• Round 2 Winner, Sontag Entrepreneurship Competition, University of Nevada, Reno, January 2024
  Developed and delivered a pitch presentation for Plato, an innovative mentorship platform, selected for advancement in the university’s entrepreneurship showcase.
• Best Camera Use, Programming with Animation Competition, University of Washington, March 2020.
• U.S. President’s Award for Outstanding Academic Excellence, signed by President Obama, 2016.
• Top Nevada Finalist (National Competition), MathCON Mathematics Contest, University of Chicago, 2016.
• National Honor Society Academic Excellence Award, 2018 & 2019.

Teaching Experience

• Tutor – University Tutoring Center, University of Nevada, Reno, 2020 – 2022
  
• Tutor – Robert McQueen High School, Reno, 2017 – 2019
  Subjects: AP Physics, AP Calculus, Trigonometry, Geometry, Algebra

Technical Skills

Professional Affiliations

• Member, Association for the Advancement of Artificial Intelligence (AAAI), 2024 – present.
• Member, Association for Computing Machinery (ACM), 2018 – present.
• Member, Google Developer Groups (GDG), University of Nevada, Reno, NV, 2024 – present
  Participated in meetings and technical discussions; expanded professional network with local developers.
• Member, American Meteorological Society (AMS), 2023 – present.
• Member, USA Swimming, 2015 – present.

Professional Development

• Teaching Assistant Training, University of California, Davis, September 2025.
• Machine Learning Certificate, Machine Learning in Python for Environmental Science Problems short course, American Meteorological Society (AMS) 104th Annual Meeting, Baltimore, MD, January 2024.
• American Geophysical Union (AGU) Annual Meeting, San Francisco, CA — Attended 2017, 2018, 2019.

Contact

GitHub: MichaelMartinTech

ResearchGate: M-Martin-10

Orchid: 0009-0001-1528-9965

Google Scholar: View Profile

LinkedIn: martin-portfolio

Email: csemartin[at]ucdavis[dot]edu