Trieu Hai Vo — PhD Student, Florida International University

About

I am a PhD Student in Computer Science at Florida International University in Miami, Florida, conducting research at the intersection of deep learning and environmental monitoring. My doctoral work is advised by Prof. Leonardo Bobadilla (Associate Professor, Knight Foundation School of Computing and Information Sciences, Florida International University) and Prof. Cuong V. Nguyen (Assistant Professor, Department of Mathematical Sciences, Durham University, United Kingdom).

I develop deep-learning methods for environmental time series, with applications to water-quality monitoring and climate observation — infrastructure that U.S. agencies, water utilities, and federal Earth-system research increasingly depend on. I published peer-reviewed work at the ICLR 2025 Workshop on Tackling Climate Change with Machine Learning (the dedicated climate-AI workshop co-located with the International Conference on Learning Representations) and submitted my current research to ACM SIGKDD 2026, currently under peer review.

Two NSF-funded research centers at Florida International University fund my doctoral research. The NSF CREST Center for Aquatic Chemistry and Environment (CACHE) anchors the aquatic-environment domain — water-quality monitoring, lake stratification, coastal chemistry — and tracks my annual research outputs in NSF program reports. The NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) via the FIU–AI2ES ExpandAI partnership anchors the trustworthy-AI methodology behind Earth-system and climate-resilience applications. I co-presented “Learning and Planning for Water Quality Monitoring” with Prof. Bobadilla at the AI2ES collaboration meeting at FIU in June 2024 and report progress at monthly AI2ES coordination meetings. I am also a graduate researcher in Prof. Bobadilla’s Motion, Robotics and Automation Lab at the Knight Foundation School of Computing and Information Sciences.

I hold an M.S. in Artificial Intelligence from Northeastern University (2023, GPA 3.91 / 4.00) and a B.S. in Computer Science (Advanced Program) from Vietnam National University — University of Science (2018, GPA 3.65 / 4.00), where I received the Rector’s Merit Award and Medal for top academic standing. Prior to my PhD, I worked as an AI Engineer at Breathing.ai (New York; remote), deploying real-time physiological-sensing systems on Amazon Web Services. I passed the PhD Qualifying Examination at Florida International University in April 2026.

Research Focus: I develop deep-learning methods for environmental time series — specifically, structured attention architectures that encode the physical structure of stratified aquatic systems along three axes: depth, feature, and time. My research uses the climate and water-monitoring data that U.S. federal programs depend on — including the U.S. Environmental Protection Agency's Safe Drinking Water Act monitoring, the National Oceanic and Atmospheric Administration's coastal-resilience initiatives, and the U.S. Geological Survey's National Water Information System — covering lake-temperature records, multi-depth water-quality measurements, and long-horizon environmental forecasts. Depth-wise Multivariate Imputation (DMI) gives depth its own attention axis rather than collapsing it into the feature dimension, and outperforms standard multivariate-imputation baselines on the LakeBeD-US and Miami-WQ benchmarks. Immediate applications include drinking-water reservoirs, coastal-resilience monitoring, and the climate-change-attribution datasets underlying U.S. federal Earth-system research.

Research interests: time-series imputation and forecasting · structured attention architectures · diffusion and generative models for scientific data · physics-informed machine learning · foundation models for environmental applications.

News

Apr 16, 2026	Passed the PhD Qualifying Examination at Florida International University in Computer Science. Committee: Prof. Leonardo Bobadilla (chair), Prof. Jayantha T. Obeysekera (Director, FIU Sea Level Solutions Center), and Prof. Agoritsa Polyzou (Knight Foundation School of Computing and Information Sciences).
Apr 01, 2026	Submitted new research to ACM SIGKDD 2026 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining): Depth-wise Multivariate Imputation for Environmental Time Series — currently under peer review.
Apr 28, 2025	Presented peer-reviewed research in person at the ICLR 2025 Workshop on Tackling Climate Change with Machine Learning in Singapore: Lake Water Temperature Modeling Using Physics-Informed Neural Networks.
Mar 06, 2025	Research paper accepted at the ICLR 2025 Workshop on Tackling Climate Change with Machine Learning, the dedicated climate-AI workshop co-located with the International Conference on Learning Representations: Lake Water Temperature Modeling Using Physics-Informed Neural Networks.
Jun 19, 2024	Co-presented an in-person talk, “Learning and Planning for Water Quality Monitoring,” with Prof. Leonardo Bobadilla at the FIU AI/ML and Modeling Collaboration Meeting (June 19–20, 2024, FIU International Center for Tropical Botany, Coconut Grove, FL), hosted under the NSF AI2ES ExpandAI partnership. The two-day program brought together AI2ES researchers and external partners — including the South Florida Water Management District (SFWMD) and Texas A&M–Corpus Christi — for talks on AI for sea-level, water-quality, and climate-downscaling research, and a Day-2 field visit to flood-monitoring sites in Hallandale Beach and a coastal-resilience tour at South Pointe Park, Miami Beach. AI2ES collaboration meeting at FIU — in-person presentation with Prof. Leonardo Bobadilla, June 19, 2024 (FIU International Center for Tropical Botany, Coconut Grove, FL).
May 01, 2024	Started PhD in Computer Science at Florida International University, advised by Prof. Leonardo Bobadilla and Prof. Cuong V. Nguyen. Doctoral research supported in part by the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) via the FIU–AI2ES ExpandAI partnership.

Publications

2026

KDD
Depth-wise Multivariate Imputation for Environmental Time Series

Trieu H. Vo, Cuong V. Nguyen, Ana Sophia Cavalcanti, and Leonardo Bobadilla

2026

Manuscript under peer review at ACM SIGKDD 2026

Abs Bib

Time series data from environmental monitoring systems often contain missing values caused by sensor failures, transmission errors, or maintenance interruptions. While existing imputation methods perform well in many cases, they often fail to account for the unique vertical correlations between adjacent depth layers in stratified environments such as lakes or oceans. To address this limitation, we propose Depth-wise Multivariate Imputation, a time series imputation method that can simultaneously model dependencies across depth, feature, and temporal dimensions, ensuring the imputation process explicitly accounts for the complex physical interactions within stratified environmental systems. We demonstrate the effectiveness of our method through experiments on several datasets, including a newly collected multi-depth water quality dataset from Miami, USA.
@unpublished{vo2026dmi, title = {Depth-wise Multivariate Imputation for Environmental Time Series}, author = {Vo, Trieu H. and Nguyen, Cuong V. and Cavalcanti, Ana Sophia and Bobadilla, Leonardo}, note = {Manuscript under peer review at ACM SIGKDD 2026}, year = {2026}, }

2025

ICLR-W
Lake Water Temperature Modeling Using Physics-Informed Neural Networks

Trieu H. Vo, Cuong V. Nguyen, Dongsheng Luo, and Leonardo Bobadilla

In ICLR 2025 Workshop on Tackling Climate Change with Machine Learning, 2025

Abs Bib HTML PDF Slides Poster

Assessing water quality in bodies of water is important in evaluating the effects of climate change and its anthropogenic impacts. Such assessments often require good models of key indices such as water temperature, pH, or oxygen levels. In this work, we investigate time series models for lake water temperatures at multiple depths and develop a physics-informed neural network based on Koopman embeddings and LSTM that is capable of forecasting water temperatures in the long term. Experiment results show that our model can achieve a good performance and significantly outperforms the conventional LSTM model for this time series forecasting problem.
@inproceedings{vo2025lake, title = {Lake Water Temperature Modeling Using Physics-Informed Neural Networks}, author = {Vo, Trieu H. and Nguyen, Cuong V. and Luo, Dongsheng and Bobadilla, Leonardo}, booktitle = {ICLR 2025 Workshop on Tackling Climate Change with Machine Learning}, year = {2025}, url = {https://www.climatechange.ai/papers/iclr2025/48}, }

Education

2024 - present

Miami, FL
Doctor of Philosophy (Ph.D.)

Florida International University

Computer Science
- Advisors: Prof. Leonardo Bobadilla (Florida International University) and Prof. Cuong V. Nguyen (Durham University, United Kingdom)
- Research: Deep learning for environmental time series; axis-factored attention architectures; water-quality imputation and forecasting
- Passed PhD Qualifying Examination (April 2026)
2021 - 2023

Boston, MA
Master of Science (M.S.)

Northeastern University

Artificial Intelligence
- GPA: 3.91 / 4.00
- Concentration: Artificial Intelligence
- Coursework: Artificial Intelligence, Machine Learning, Data Science, Data Mining, Big Data, Predictive Analytics, Healthcare Information Processing
2014 - 2018

Ho Chi Minh City, Vietnam
Bachelor of Science (B.S.)

Vietnam National University — University of Science

Computer Science (Advanced Program)
- GPA: 3.65 / 4.00 (Advanced Program, instruction in English)
- Honors thesis: “Brain Tumor Segmentation in MRI Images Using Convolutional Neural Networks” — advised by Dr. Tien B. Dinh (Dean of the Faculty of Information Technology, VNU-HCMUS)
- Rector’s Merit Award and Medal for outstanding academic achievement (2018)

Talks and Presentations

“Learning and Planning for Water Quality Monitoring” — co-presented with Prof. Leonardo Bobadilla at the FIU AI/ML and Modeling Collaboration Meeting (June 19–20, 2024, FIU International Center for Tropical Botany, Coconut Grove, FL), hosted under the NSF AI2ES ExpandAI partnership with external partners including the South Florida Water Management District (SFWMD) and Texas A&M–Corpus Christi.

Poster: “Lake Water Temperature Modeling Using Physics-Informed Neural Networks” — peer-reviewed poster presentation at the ICLR 2025 Workshop on Tackling Climate Change with Machine Learning (April 28, 2025, Singapore).

Experience

2024 - present

Miami, FL
PhD Research Assistant

Florida International University
- The NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES) funds my doctoral research via the FIU–AI2ES ExpandAI partnership
- Developing Depth-wise Multivariate Imputation (DMI) — a deep-learning architecture with axis-factored attention for imputing missing measurements across multi-depth environmental sensor networks (see Publications)
- Designed and implemented a physics-informed neural network combining Koopman operator theory with LSTM recurrent networks for long-horizon lake water-temperature forecasting; published at ICLR 2025 Workshop on Tackling Climate Change with Machine Learning
- Conducting empirical studies on real-world water-quality datasets, including the LakeBeD-US benchmark and a newly collected multi-depth dataset from Miami, FL
2023 - 2024

New York, NY (Remote)
AI Engineer

Breathing.ai
- Engineered webcam-based heart-rate and stress detection using remote photoplethysmography (rPPG), integrating MTTS-CAN, CHROM, and POS signal-processing methods
- Deployed a real-time contact-free physiological-sensing pipeline on Amazon Web Services, distributed as a Chrome extension for continuous wellbeing monitoring
2022 - 2022

Boston, MA (Remote)
AI Intern

Breathing.ai
- Developed machine-learning models (XGBoost, Random Forest, Convolutional Neural Networks) to predict physiological state from wearable-device and facial-video data
- Achieved 95% accuracy on real-time drowsiness detection using a CNN-based vision model
2019 - 2021

Ho Chi Minh City, Vietnam
Private Tutor

Self-employed
- Private tutoring during the COVID-19 period while preparing for U.S. graduate study; ranked first in the VietAI Machine Learning Foundation Course (June 2019) and earned IELTS Academic 7.5 (January 2021).
2017 - 2018

Ho Chi Minh City, Vietnam
AI Intern

KMS Technology, Inc.
- Built a production Résumé Parsing System for enterprise hiring, combining NLP classification with named-entity extraction (title-recognition F1 = 0.92; paragraph-classification F1 = 0.99)

Awards

Jun 2019

VietAI Machine Learning Foundation Course — Top Student (full tuition refund)

VietAI (Vietnam AI Initiative)

Ranked first in a selective nationwide cohort of the VietAI (Vietnam AI Initiative) Machine Learning Foundation Course and received a full tuition refund for top-student standing.
Nov 2018

Rector's Merit Award and Medal

Vietnam National University — University of Science (VNU-HCMUS)

The Rector of Vietnam National University — University of Science (VNU-HCMUS) conferred this top academic honor for outstanding achievement across the Computer Science (Advanced Program) undergraduate curriculum.
2014

Academic Merit Scholarships — 4-year continuous recipient

Vietnam National University — University of Science

Merit-based academic scholarships awarded each semester by Vietnam National University — University of Science for sustained academic excellence in the Advanced Program (2014–2018).

Skills

Primary tools: Python, PyTorch, LaTeX, Git

Methods: Deep learning, time-series modelling, structured attention, physics-informed neural networks, diffusion models, Koopman operator methods

Domains: Environmental AI, water-quality monitoring, medical and physiological sensing

Certificates

Mathematics for Machine Learning & Data Science: DeepLearning.AI — Calculus + Linear Algebra (February 2024)

Understanding Research Methods: University of London (April 2024)

Algorithms — Elementary + Intermediate: Big-O Coding (selective Vietnamese coding program; August + November 2023)

Python — Skill Assessment: HackerRank (April 2021)

IELTS Academic 7.5: IDP Education (January 2021)

Languages

Vietnamese: Native speaker

English: Fluent (see IELTS certificate above)

About

Publications

2026

2025

Education

Doctor of Philosophy (Ph.D.)

Computer Science

Master of Science (M.S.)

Artificial Intelligence

Bachelor of Science (B.S.)

Computer Science (Advanced Program)

Talks and Presentations

Experience

PhD Research Assistant

AI Engineer

AI Intern

Private Tutor

Self-employed

AI Intern

Awards

VietAI Machine Learning Foundation Course — Top Student (full tuition refund)

VietAI (Vietnam AI Initiative)

Rector's Merit Award and Medal

Vietnam National University — University of Science (VNU-HCMUS)

Academic Merit Scholarships — 4-year continuous recipient

Vietnam National University — University of Science

Skills

Certificates

Languages