ICCV CVAM Workshop, Oct 2025
Invited talk on the role of Generative AI in Advertisement and Marketing. Link
Bio
I’m a PhD student in Artificial Intelligence at Oregon State University, specializing in AI for Social Good and Applied AI/ML in Ecology. My research focuses on utilizing ML-based species distribution modeling algorithms to demonstrate better predictability with the choice of habitat characterization. Additionally, I am investigating plant-pollinator interactions over a decade of environmental change using hierarchical occupancy modeling, uncovering critical insights into the dynamics of the ecosystem.
Prior to this, I worked in the industry on multi-modal AI systems and neural network quantization techniques. I have also contributed extensively to generative models and federated learning as part of privacy-preserving initiatives in machine learning.
Invited Talks
Decentralized AI Hackathon @ Stanford, Sep 2025
Invited talk on Federated Learning for Generative Models. Link
University of Washington, May 2025
Invited talk for the graduate level course: Advanced Topics in Data Privacy.
Flower Monthly, Aug 2023
Invited talk on "Phoenix: A Federated Generative Diffusion Model." Video
Publications
Most recent publications on Google Scholar.
DECOR: Deep Embedding Clustering with Orientation Robustness
Fiona Victoria Stanley Jothiraj, Arunaggiri Pandian, Seth A. Eichmeyer
AAAI 2026 Bridge Program on Knowledge-guided Machine Learning. Also selected at AAAI 2026 Workshop on AI2ASE
Species distribution model performance improves when habitat characterizations
are centered on detected individuals instead of observers
Fang-Yu Shen, Fiona Victoria Stanley Jothiraj, Rebecca A Hutchinson, Tyler A Hallman, Jenna R Curtis, W Douglas Robinson
Ecological Indicators, 2025
Phoenix: A Federated Generative Diffusion Model
Fiona Victoria Stanley Jothiraj, Afra Mashhadi
ACM The Web Conference (WWW) 2024
Nostalgia on Twitter: Detection and Analysis of a Large-Scale Dataset
Fiona Victoria Stanley Jothiraj, Lingzi Hong, Afra Mashhadi
ASIS&T 2024
Empirical Dynamic Modelling of the Multi-Source Park Visitation Data
Vahid Shamsaddini, Fiona Victoria Stanley Jothiraj, Mandy Chen, Afra Mashhadi
Data for Policy Conference 2022
Personalized Emotion Detection using IoT and Machine Learning
Fiona Victoria Stanley Jothiraj, Afra Mashhadi
ArXiv, 2022
Time Series Prediction for Food sustainability
Fiona Victoria Stanley Jothiraj
ArXiv, 2022
Blogs
My Journey to PhD Admission in Artificial Intelligence
Untangling Azure IoT Hub and Stream Analytics
An Introduction to AWS IoT Core
Media
Featured Coverage
- Oregon State University - AI student leverages OSU's interdisciplinary strengths
- Semiconductor Engineering - Grouping Complex Wafer Defect Patterns Into Meaningful Clusters
- The Hindu - App for Plus Two Students
- Deccan Chronicle - 12th Standard Student Develops App for Engineering Aspirants
- Business Standard - School Girl Develops App for TN Engineering Aspirants
- India.com - School Girl Develops Application for Tamil Nadu Engineering Aspirants
Media Gallery
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CV
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Micron Technology June 2024/2025 - Sep 2024/2025AI Research Intern
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ML QuESt Research Lab at OSU Oct 2023 - PresentGraduate Research Assistant
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Oregon State University Sep 2023 - PresentPh.D in Artificial Intelligence
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Harvard in Tech June 2023 - Oct 2023Data Scientist
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Research Lab at UW Bothell June 2022 - Jan 2023Graduate Research Assistant
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University of Washington Bothell Sep 2021 - June 2023M.S. in Computer Science and Software Engineering
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Multicoreware Inc 2019 - 2020Machine Learning Engineer
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Multicoreware Inc 2018 - 2019Machine Learning Intern
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PSG College of Technology July 2015 - May 2019B.E. in Robotics and Automation Engineering
First Class with Distinction
Projects
Time Series Prediction for Food Sustainability
Statistical regression-based ML system to predict top-k food crops likely to endure shortages by country.
Personalized Emotion Detection using IoT and Machine Learning
Non-invasive IoT system that tracks patient emotions, including autism-focused applications.
Accelerated Image Restoration using CUDA
Designed CUDA kernels from scratch to accelerate image reconstruction.
Spatio-Temporal Forecast Modeling and Fairness of Traffic Fatality
Forecasting traffic fatality hotspots in the United States using deep learning and fairness-aware modeling.
Art
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