Postdoctoral Research Associate · Northeastern University

Khanh Do

Computational atmospheric scientist building the models that tell us what we breathe — and who breathes the worst of it.

I fuse machine learning, GPU computing, and deterministic chemical transport models to make air quality prediction faster, sharper, and more equitable — from CUDA kernels inside CMAQ to 1 km climate downscaling and cumulative environmental justice scoring for Greater Boston.

Download CV Browse 18 publications Get in touch

0: Peer-reviewed
publications
0: Conference
presentations
0: Ph.D. students
mentored
0: Supercomputing
CPU hours awarded

Funded by
NSF
NOAA
EPA
CARB
SCAQMD
Sloan Foundation
iSUPER

01 — About

Large datasets, hard physics, and the people downstream

My research focuses on predicting and investigating air quality using machine learning methods and deterministic models.

I work with large datasets to recognize patterns and explore the relationships between meteorology, emissions, and exposure — then apply machine learning and technological advances such as GPU computing to make deterministic models dramatically more efficient. The through-line: a model is only as valuable as the decision it enables, and the community it protects.

That has meant replacing the slowest module of a regulatory chemical transport model with CUDA kernels, downscaling 30 years of future climate to 1 km, training convolutional networks that predict PM_2.5 exceedances where monitors are sparse, and building a cumulative environmental justice score system for disadvantaged neighborhoods in Greater Boston.

Air quality modelingMachine learningComputer visionPersonal exposureData assimilationHigh-performance computingGPU computingClimateModel developmentDownscalingBias correction

Education

2023
Ph.D., Chemical & Environmental Engineering University of California, Riverside Dissertation: “Computational and Geospatial Approaches to Investigate Multi-scale Air Quality Trends in Southern California”
Advisor: Prof. Cesunica E. Ivey
2023
M.S., Electrical Engineering University of California, Riverside Specialization: Robotics & Computer Vision
2015
B.S., Chemical Engineering University of California, Berkeley

Awards & honors

Outstanding Teaching Assistant Award2023 · Chemical & Environmental Engineering, UC Riverside
GAANN Fellowship2019 – 2022
Esther F. Hays Graduate Fellowship2020 – 2021
Salim Khan Graduate Award2019 – 2020

02 — Research

Four programs, one question: how do we predict air quality well enough to act on it?

NSF CDS&ENOAAiSUPER

Chemical transport model enhancement

Making regulatory-grade atmospheric chemistry fast enough to be useful.

Implemented GPU computing in the CMAQ gas-phase solver, exploiting thousands of CUDA cores to lift the computational efficiency of the model's most expensive module.
Used machine learning to accelerate chemical transport models by substituting their most time-consuming modules, and to bias-correct their output for higher accuracy.
Contributed to development of the early version of NOAA's UFS-SRW App.

Published in Environmental Science & Technology Air · presented at CMAS 2022–2024

iSUPERSloan FoundationCARB

Environmental justice & health assessment

Quantifying who carries the pollution burden — and what would relieve it.

Built a new cumulative environmental justice score system for Greater Boston, mapping highly impacted areas and the correlation between personal exposure and household income.
Investigated personal PM_2.5 exposure in the Inland Empire, explaining how habits, income, and communities of color shape exposure at personal resolution.
Quantified how mobility and housing characteristics drive daily PM_2.5 exposure and well-being in West San Bernardino, delivering individualized resilience plans to community collaborators.

Published in Environmental Research Letters, Journal of Aerosol Science

iSUPERSCAQMD

Machine-learning-assisted air quality prediction

Better predictions from fewer sensors and messier data.

Optimized low-cost sensor placement — minimizing the number of sensors needed to cover the most land area while maximizing ML prediction accuracy.
Determined the meteorological drivers of ground-level ozone and PM_2.5, building empirical models from historical records to project air quality trends.
Assembled and operated BAM 1020 reference monitors and ran collocation calibration for low-cost sensor networks.

Published in Environmental Science: Atmospheres, Atmospheric Environment, GMD

NCAR/NWSCDownscaling

High-resolution SSP climate downscaling

Thirty years of future climate, resolved down to the neighborhood.

Dynamically downscaled 2060–2089 climate projections with the Pseudo Global Warming method and WRF across Shared Socio-Economic Pathways.
Delivered nested meteorological products at 36 km (CONUS), 6 km (Eastern US), and 1 km (North Carolina & Virginia).
Outputs feed directly into downstream health assessment studies.

Supported by 500,000 CPU hours + 1,500 GPU hours, NCAR-Wyoming Supercomputing Center

Toolbelt

Models

CMAQ · WRF · WRF-Chem · UFS-SRW · RRFS-CMAQ

Methods

Deep learning & CNNs · Generalized additive models · Bias correction · Data assimilation · Spatial interpolation · Pseudo global warming downscaling

Computing

CUDA / GPU acceleration · MPI & HPC workflows · Cheyenne · Derecho · NERSC · Anvil · Discovery

Measurement

BAM 1020 · Low-cost sensor networks & collocation calibration · UAV vertical profiling · Personal exposure monitoring

Vision & other

GPU-assisted image processing for high-resolution traffic footage · Vehicular detection, counting & classification · Vehicular emission detection · Atmospheric dispersion modeling · M/M/1 & M/G/1 queueing analysis

03 — Publications

18 peer-reviewed papers, preprints & training manuals

Plus three technical reports for NOAA, the National Center for Sustainable Transportation, and SCAQMD.

2025

Do K, Yang Zhang, Siqi Ma, Daniel Tong. “Assessing Air Pollution Exposure Disparities in Disadvantaged Communities of Greater Boston: A New Cumulative Environmental Justice Score System.”

Environmental Research Letters
10.1088/1748-9326/adb16c ↗
2025

Duncan Quevedo, Do K, Jose Rodriguez Borbon, Bryan M. Wong, Cesunica E. Ivey. “GPU Implementation of a Gas-Phase Chemistry Solver in the CMAQ Chemical Transport Model.”

Environmental Science & Technology Air
10.1021/acsestair.4c00181 ↗
Under
revision

Do K, Yang Zhang. “Assessing Health Risks and Disparities in Air Pollution and Socioeconomic Status across the United States.”

Environmental Pollution — under revision
2024

Do K, George Delic, Jose Rodriguez Borbon, Duncan Quevedo, Bryan M. Wong, Cesunica E. Ivey. “Graphics Processing Unit Assisted Computation for a Gas-Phase Chemical Solver in a Regulatory Chemical Transport Model.”

EarthArXiv preprint
eartharxiv.org/repository/view/6323 ↗
2024

Torres I, Do K, Delgado A, Mourad C, Ivey CE. “Indoor and Ambient Influences on PM_2.5 Exposure and Well-being for a Rail Impacted Community and Implications for Personal Protections.”

Environmental Research Letters
10.1088/1748-9326/ad90f5 ↗
2024

Do K, Daniel Schuch, Yang Zhang. “Practice Instruction for Online-Coupled WRF-Chem Version 4.6.0 — Training Manual for the Hands-on Training Session on WRF-Chem.”

World Meteorological Organization · E-learning & Training Resources Portal
etrp.wmo.int ↗
2024

Zihan Zhu, Do K, Cesunica E. Ivey, Don R. Collins. “Assessing CMAQ Model Discrepancies in a Heavily Polluted Air Basin Using UAV Vertical Profiles and Sensitivity Analyses.”

Environmental Science: Atmospheres
10.1039/d4ea00004h ↗
2024

Do K, Yeganeh AK, Gao Z, Ivey CE. “Performance of Machine Learning for Ozone Modeling in Southern California during the COVID-19 Shutdown.”

Environmental Science: Atmospheres
10.1039/D3EA00159H ↗
2024

Ziqi Gao, Do K, Zongrun Li, Xiangyu Jiang, Kamal J. Maji, Cesunica E. Ivey, Armistead G. Russell. “Predicting PM_2.5 Levels and Exceedance Days Using Machine Learning Methods.”

Atmospheric Environment
10.1016/j.atmosenv.2024.120396 ↗
2024

Duncan Quevedo, Ziqi Gao, Do K, Roya Bahreini, Don Collins, Cesunica Ivey. “Multidecadal Analysis of Meteorological and Emissions Regimes for PM_2.5 Across California.”

Environmental Science & Technology Air
10.1021/acsestair.3c00019 ↗
2023

Ziqi Gao, Cesunica E. Ivey, Charles L. Blanchard, Do K, Sang-Mi Lee, Armistead G. Russell. “Emissions and Meteorological Impacts on PM_2.5 Species Concentrations in Southern California Using Generalized Additive Modeling.”

Science of the Total Environment
10.2139/ssrn.4377297 ↗
2023

Ziqi Gao, Cesunica E. Ivey, Charles L. Blanchard, Do K, Sang-Mi Lee, Armistead G. Russell. “Emissions, Meteorological and Climate Impacts on PM_2.5 Levels in Southern California Using a Generalized Additive Model: Historic Trends and Future Estimates.”

Chemosphere
10.1016/j.chemosphere.2023.138385 ↗
2023

Do K, Mahish M, Kashfi Yeganeh A, Gao Z, Blanchard CL, Ivey CE. “A Machine Learning Approach to Quantify the Impact of Meteorology on Tropospheric Ozone in the Inland Empire, CA.”

Environmental Science: Atmospheres
10.1039/D2EA00077F ↗
2023

Md Hasibul Hasan, Haofei Yu, Cesunica Ivey, Ajay Pillarisetti, Ziyang Yuan, Do K, Yi Li. “Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal.”

ACS Omega
10.1021/acsomega.2c07734 ↗
2022

Gao Z, Ivey CE, Blanchard CL, Do K, Lee S-M, Russell AG. “Separating Emissions and Meteorological Impacts on Peak Ozone Concentrations in Southern California Using Generalized Additive Modeling.”

Environmental Pollution, 119503
10.1016/j.envpol.2022.119503 ↗
2022

Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Do K, Armistead G. Russell. “Predicting Peak Daily Maximum 8-h Ozone and Linkages to Emissions and Meteorology in Southern California Using Machine Learning Methods.”

Geoscientific Model Development
10.5194/gmd-15-9015-2022 ↗
2021

Do K, Yu H, Velasquez J, Grell-Brisk M, Smith H, Ivey CE. “A Data-Driven Approach for Characterizing Community-Scale Air Pollution Exposure Disparities in Inland Southern California.”

Journal of Aerosol Science, Article 105704
10.1016/j.jaerosci.2020.105704 ↗
2020

Ivey CE, Gao Z, Do K, Kashfi Yeganeh A, Russell AG, Blanchard CL, Lee S-M. “Impacts of the 2020 COVID-19 Shutdown Measures on Ozone Production in the Los Angeles Basin.”

ChemRxiv preprint
10.26434/chemrxiv.12805367.v1 ↗

Technical reports

Do K, Yang Zhang. “NOAA Semi-annual Report for UFS-SRW App.” Grant No. NA22OAR4590515.
Ivey CE, Nguyen A, Xu RM, Do K, Hao P, Barth M. “Hyperlocal Monitoring of Traffic-Related Air Pollution to Assess Near-Term Impacts of Sustainable Transportation Interventions.” National Center for Sustainable Transportation, Contract No. DOT 69A3551747114, Feb 2023.
Ivey CE, Blanchard CL, Russell AG, Gao Z, Do K. “Ozone Meteorology Study, final report.” South Coast Air Quality Management District, Contract No. 20058, January 2022.

04 — Talks & teaching abroad

20 conference presentations across CMAS, AGU, AAAR, AEESP & more

WMO

Instructor — “Training Course on Seamless Prediction of Air Pollution in Africa”

Delivered a specialized training course at the Egyptian Meteorological Authority in Egypt, organized by the World Meteorological Organization, instructing participants on running and evaluating the WRF-Chem model over the African domain.

As presenter (9)

Poster
“Assessing Health Risks and Disparities in Air Pollution and Socioeconomic Status across the United States”
23rd Annual CMAS Conference · Chapel Hill, NC · Oct 2024
Poster
“Quantify the Impacts of Air Pollution on Disadvantaged Communities in Greater Boston with a New Cumulative Environmental Justice Score System”
BARI 2024 · Boston, MA · Apr 2024
Oral
“GPU-Assisted Computation for a Gas-Phase Chemical Solver in CMAQ”
22nd Annual CMAS Conference · Chapel Hill, NC · Oct 2023
Oral
“Machine Learning with Spatial Interpolation Techniques for Constructing 2-Dimensional Ozone Concentrations in Southern California during the COVID-19 Shutdown”
22nd Annual CMAS Conference · Chapel Hill, NC · Oct 2023
Poster
“Superior Performance of Convolutional Neural Network for Predicting PM_2.5 Concentrations and Exceedances under Sparse Data Availability”
AEESP 2023 · Boston, MA · Jun 2023
Oral
“A Machine Learning Approach to Quantify the Impact of Meteorology on Tropospheric Ozone in the Inland Empire, CA”
21st Annual CMAS Conference · Chapel Hill, NC · Oct 2022
Oral
“GPU-Assisted CMAQ Simulations”
21st Annual CMAS Conference · Chapel Hill, NC · Oct 2022
Poster
“Applying Machine Learning and Chemical Transport Model to Investigate the Influences of Meteorology on PM_2.5 and Ozone”
38th AAAR Meeting · Oct 2020
Poster
“High-Resolution Personal Exposure Monitoring of PM_2.5 in Inland Southern California”
37th AAAR Meeting · Portland, OR · Oct 2019

As co-author (11)

“Multi-Scale Air Quality Modeling Using WRF-Chem-GHG over Northeastern Africa”
Oral · 23rd CMAS · Oct 2024
“GPU Implementation of a Gas-Phase Chemistry Solver in the CMAQ Chemical Transport Model”
Oral · 23rd CMAS · Oct 2024
“Graphics Processing Unit Assisted Computation for a Gas-Phase Chemical Solver in a Regulatory Chemical Transport Model”
Poster · BASC Symposium, UC Berkeley · Mar 2024
“Compounding Risks in Disparately Impacted Communities: California Case Studies and Future Recommendations”
Oral · AGU Fall Meeting · San Francisco, CA · Dec 2023
“UAV Measurements in a Heavily Burdened Air Basin to Understand Meteorological and Emissions Uncertainties in CMAQ”
Poster · MAC-MAQ 2023 · Davis, CA · Sep 2023
“Air Pollution Exposure Mitigation for the Protection of Impacted Communities”
Oral · AEESP 2023 · Boston, MA · Jun 2023
“Vertical Ozone Profiles Measurement in Riverside, CA”
Poster · AGU Fall Meeting · Dec 2021
“Application of Machine Learning for Future Air Quality Predictions in Southern California”
Poster · 38th AAAR Meeting · Oct 2020
“High-Temporal Resolution Personal Exposure Pilot Study in Inland Southern California”
Poster · Air Sensors International Conference · Pasadena, CA · May 2020
“CMAQ-Enhanced Estimates of Personal Exposure to Diesel Particulates”
Poster · CMAS Meeting · Chapel Hill, NC · Oct 2019
“Field Evaluation and Calibration of a Six-Parameter Low-Cost Sensor System in Northwestern and Southeastern US”
Poster · 37th AAAR Meeting · Oct 2019

05 — Teaching, mentorship & service

Building the next cohort, and the proposals that fund them

Mentorship & leadership

Academic mentor to six Ph.D. students — overseeing progress and guiding research projects
Assist Principal Investigators in developing and preparing proposals for NSF, NOAA, and EPA funding opportunities
Technical advisor to the Center for Community Action and Environmental Justice (Jurupa Valley, CA) and The Air I Breathe (Colton, CA)
Community outreach in San Bernardino, CA

Teaching

WMO training instructor — WRF-Chem for the African domain, Egyptian Meteorological Authority
Guest lecture, Carnegie Mellon University (2023)
Invited talk, Northeastern University CEE Graduate Expo (2024)
Teaching Assistant, CHE 117 Separation Processes (enrollment 49), UC Riverside (2022) — Outstanding TA Award

Peer review & service

Poster evaluation committee, CMAS 2023 & 2024
Journal reviewer: Environmental Science & Technology, Nature Sustainability, GeoHealth, Atmosphere, Applied Sciences, Environmental Research Letters
Student assistance, 2019 AAAR conference

Computational allocations

NCAR-Wyoming Supercomputing Center — repository UNTE0007, “SSP Downscaling and RRFS-CMAQ Development”: 500,000 CPU hours + 1,500 GPU hours
NERSC — 1,500 CPU node hours
Production experience on Cheyenne, Derecho, NERSC, Anvil, and Discovery

06 — Contact

Let's model something that matters.

Open to collaborations on air quality modeling, ML-accelerated chemical transport, climate downscaling, and environmental health — and to faculty and research-scientist opportunities.

kh.do@northeastern.edu Boston, MA 02118

Download full CV (PDF)

Khanh Do

Large datasets, hard physics, and the people downstream

Four programs, one question: how do we predict air quality well enough to act on it?

Chemical transport model enhancement

Environmental justice & health assessment

Machine-learning-assisted air quality prediction

High-resolution SSP climate downscaling

Toolbelt

Models

Methods

Computing

Measurement

Vision & other

18 peer-reviewed papers, preprints & training manuals

Do K, Yang Zhang, Siqi Ma, Daniel Tong. “Assessing Air Pollution Exposure Disparities in Disadvantaged Communities of Greater Boston: A New Cumulative Environmental Justice Score System.”

Duncan Quevedo, Do K, Jose Rodriguez Borbon, Bryan M. Wong, Cesunica E. Ivey. “GPU Implementation of a Gas-Phase Chemistry Solver in the CMAQ Chemical Transport Model.”

Do K, Yang Zhang. “Assessing Health Risks and Disparities in Air Pollution and Socioeconomic Status across the United States.”

Do K, George Delic, Jose Rodriguez Borbon, Duncan Quevedo, Bryan M. Wong, Cesunica E. Ivey. “Graphics Processing Unit Assisted Computation for a Gas-Phase Chemical Solver in a Regulatory Chemical Transport Model.”

Torres I, Do K, Delgado A, Mourad C, Ivey CE. “Indoor and Ambient Influences on PM2.5 Exposure and Well-being for a Rail Impacted Community and Implications for Personal Protections.”

Do K, Daniel Schuch, Yang Zhang. “Practice Instruction for Online-Coupled WRF-Chem Version 4.6.0 — Training Manual for the Hands-on Training Session on WRF-Chem.”

Zihan Zhu, Do K, Cesunica E. Ivey, Don R. Collins. “Assessing CMAQ Model Discrepancies in a Heavily Polluted Air Basin Using UAV Vertical Profiles and Sensitivity Analyses.”

Do K, Yeganeh AK, Gao Z, Ivey CE. “Performance of Machine Learning for Ozone Modeling in Southern California during the COVID-19 Shutdown.”

Ziqi Gao, Do K, Zongrun Li, Xiangyu Jiang, Kamal J. Maji, Cesunica E. Ivey, Armistead G. Russell. “Predicting PM2.5 Levels and Exceedance Days Using Machine Learning Methods.”

Duncan Quevedo, Ziqi Gao, Do K, Roya Bahreini, Don Collins, Cesunica Ivey. “Multidecadal Analysis of Meteorological and Emissions Regimes for PM2.5 Across California.”

Ziqi Gao, Cesunica E. Ivey, Charles L. Blanchard, Do K, Sang-Mi Lee, Armistead G. Russell. “Emissions and Meteorological Impacts on PM2.5 Species Concentrations in Southern California Using Generalized Additive Modeling.”

Ziqi Gao, Cesunica E. Ivey, Charles L. Blanchard, Do K, Sang-Mi Lee, Armistead G. Russell. “Emissions, Meteorological and Climate Impacts on PM2.5 Levels in Southern California Using a Generalized Additive Model: Historic Trends and Future Estimates.”

Do K, Mahish M, Kashfi Yeganeh A, Gao Z, Blanchard CL, Ivey CE. “A Machine Learning Approach to Quantify the Impact of Meteorology on Tropospheric Ozone in the Inland Empire, CA.”

Md Hasibul Hasan, Haofei Yu, Cesunica Ivey, Ajay Pillarisetti, Ziyang Yuan, Do K, Yi Li. “Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal.”

Gao Z, Ivey CE, Blanchard CL, Do K, Lee S-M, Russell AG. “Separating Emissions and Meteorological Impacts on Peak Ozone Concentrations in Southern California Using Generalized Additive Modeling.”

Ziqi Gao, Yifeng Wang, Petros Vasilakos, Cesunica E. Ivey, Do K, Armistead G. Russell. “Predicting Peak Daily Maximum 8-h Ozone and Linkages to Emissions and Meteorology in Southern California Using Machine Learning Methods.”

Do K, Yu H, Velasquez J, Grell-Brisk M, Smith H, Ivey CE. “A Data-Driven Approach for Characterizing Community-Scale Air Pollution Exposure Disparities in Inland Southern California.”

Ivey CE, Gao Z, Do K, Kashfi Yeganeh A, Russell AG, Blanchard CL, Lee S-M. “Impacts of the 2020 COVID-19 Shutdown Measures on Ozone Production in the Los Angeles Basin.”

Technical reports

20 conference presentations across CMAS, AGU, AAAR, AEESP & more

Instructor — “Training Course on Seamless Prediction of Air Pollution in Africa”

As presenter (9)

As co-author (11)

Building the next cohort, and the proposals that fund them

Mentorship & leadership

Teaching

Peer review & service

Computational allocations

Let's model something that matters.

Torres I, Do K, Delgado A, Mourad C, Ivey CE. “Indoor and Ambient Influences on PM_2.5 Exposure and Well-being for a Rail Impacted Community and Implications for Personal Protections.”

Ziqi Gao, Do K, Zongrun Li, Xiangyu Jiang, Kamal J. Maji, Cesunica E. Ivey, Armistead G. Russell. “Predicting PM_2.5 Levels and Exceedance Days Using Machine Learning Methods.”

Duncan Quevedo, Ziqi Gao, Do K, Roya Bahreini, Don Collins, Cesunica Ivey. “Multidecadal Analysis of Meteorological and Emissions Regimes for PM_2.5 Across California.”

Ziqi Gao, Cesunica E. Ivey, Charles L. Blanchard, Do K, Sang-Mi Lee, Armistead G. Russell. “Emissions and Meteorological Impacts on PM_2.5 Species Concentrations in Southern California Using Generalized Additive Modeling.”

Ziqi Gao, Cesunica E. Ivey, Charles L. Blanchard, Do K, Sang-Mi Lee, Armistead G. Russell. “Emissions, Meteorological and Climate Impacts on PM_2.5 Levels in Southern California Using a Generalized Additive Model: Historic Trends and Future Estimates.”