I am a Postdoctoral Research Scientist in the Westervelt Aerosol Group at the Lamont-Doherty Earth Observatory, Columbia University. My research focuses on building machine/deep learning models to estimate air pollutants using satellite-derived features and weather reanalysis parameters, validated with ground-level sensors across sub-Saharan Africa. I further leverage these datasets to investigate health impacts of air pollution to support effective local policymaking.
I earned my Ph.D. in Mechanical Engineering from Carnegie Mellon University, where I worked with Prof. Albert Presto on developing low-cost techniques to measure atmospheric particulate matter and identifying emission sources from low-cost sensor networks. I also built a deep learning forecast model for PM2.5 over Pittsburgh using features from NASA’s GEOS-CF model and a spatially deployed low-cost sensor network.
I hold an M.Phil. and M.Sc. from the Hong Kong University of Science and Technology and a B.Tech. in Civil Engineering from the Indian Institute of Technology Delhi.
🔥 News
- 2026.03: Invited to serve on the AGU Atmospheric Science Section Early Career Committee.
- 2026.02: Selected for Jane Warren Award to present in the 2026 Health Effects Institute Annual Conference.
- 2026.01: Visited Ghana to conduct in-person workshops on geospatial datasets and satellite-remote sensing at Ghana EPA and Kintampo Health Research Center.
- 2025.12: Presented research in the NASA Health and Air Quality (HAQ) session at AGU 2025 in New Orleans, Louisiana.
- 2025.06: Presented at the CAMS-Net and SPARTAN meeting hosted at Washington University in St. Louis.
- 2025.05: Attended the WCRP Global km-Scale Hackathon at GFDL, Princeton University.
- 2025.01: Team El Ninos won 1st place at the LEAP Hackathon "Harnessing Machine Learning to Improve Subseasonal-to-Seasonal Climate Predictions" at Columbia University.
- 2024.04: Defended his Ph.D. Thesis at CMU.
- 2022.08: Awarded the prestigious Dowd Fellowship by the School of Engineering at Carnegie Mellon University.
- 2022.03: Milton Shaw Ph.D. Research Award, Department of Mechanical Engineering, CMU.
🔬 Research Interests
My research interest lies in the application of image processing and machine learning for building geospatial models to derive air pollutant concentrations using satellite remote sensing and reanalysis datasets. I am further interested in leveraging these datasets to assess health impacts and associated socioeconomic disparities in air pollution exposure.
🎓 Education
- Ph.D., Mechanical Engineering, Carnegie Mellon University, Pittsburgh (2024)
- M.Phil., Environmental Science, Policy and Management, Hong Kong University of Science and Technology (2020)
- M.Sc., Environmental Engineering and Management, Hong Kong University of Science and Technology (2017)
- B.Tech., Civil Engineering, Indian Institute of Technology Delhi, New Delhi, India (2015)
📝 Publications
* represents corresponding author
2025

[Dataset] Gridded Daily PM2.5 at 1 km x 1 km Resolution from 2005-2024: Ghana
Abhishek Anand*, Joe Amooli, Daniel Westervelt
Dataset (Zenodo) | GRASP Project
This dataset provides daily estimates of surface PM2.5 concentrations across Ghana at 1 km x 1 km resolution, integrating satellite observations, ground-level monitors, and machine learning over 20 years (2005-2024).

Assessing Causality in PM2.5 and NO2 Changes One Year After New York City’s Congestion Pricing Policy
Polina M. Goldberg, Abhishek Anand, Daniel Westervelt*
Using a difference-in-differences analysis, we assess the short-term impact of NYC’s Central Business District Tolling Program (CBDTP) on PM2.5 and NO2 across all five boroughs using NYCCAS monitors and satellite observations.

Twenty Years of High Spatiotemporal Resolution Estimates of Daily PM2.5 in West Africa Using Satellite Data, Surface Monitors, and Machine Learning
Daniel Westervelt*, Joe Adabouk Amooli, Abhishek Anand
We develop machine/deep learning models using satellite-derived and weather reanalysis parameters to estimate daily PM2.5 for Ghana at 1 km resolution over 2005-2024, validated against an extensive surface monitoring network.
2024

Combining Google Traffic Map with Deep Learning Model to Predict Street-Level Traffic-Related Air Pollutants in a Complex Urban Environment
Peng Wei, Song Hao*, Yuan Shi*, Abhishek Anand, Ya Wang, Mengyuan Chu, Zhi Ning*
We built a deep learning model to predict fine-scale NOX from traffic at street-level, combining data from mobile air quality sensors on buses with crowd-sourced Google real-time traffic status.

Low-Cost Hourly Ambient Black Carbon Measurements at Multiple Cities in Africa
Abhishek Anand, N’Datchoh Evelyne Toure, Julien Bahino, …, Albert A. Presto*
We applied the image processing method from Anand et al. (2023) to used filter tapes from Beta Attenuation Monitors (BAMs) to measure atmospheric black carbon in African cities.
2023

Estimation of Hourly Black Carbon Aerosol Concentrations from Glass Fiber Filter Tapes Using Image Reflectance-Based Method
Abhishek Anand, Suryaprakash Kompalli, Eniola Ajiboyec, Albert A. Presto*
Paper | Processing Code | Streamlit App | Instructions | Video
We deployed computer vision to build an image processing method to estimate atmospheric black carbon from particulate deposits on BAM filter tapes.
2021

Determination of Local Traffic Emission and Non-Local Background Source Contribution to On-Road Air Pollution Using Fixed-Route Mobile Air Sensor Network
Peng Wei, Peter Brimblecombe, Fenhuan Yang, Abhishek Anand, Yang Xing, Li Sun, Yuxi Sun, Mengyuan Chu, Zhi Ning*
We applied wavelet analysis and lowest percentile methods to quantify contributions of traffic-related emissions to on-road gaseous and particulate levels.
2020

Protocol Development for Real-Time Ship Fuel Sulfur Content Determination Using Drone-Based Plume Sniffing Microsensor System
Abhishek Anand, Peng Wei, Nirmal Kumar Gali, …, Zhi Ning*
We developed an innovative solution for remotely measuring sulfur content in ship fuels from stack emissions using low-cost sensors on a drone, aimed at effective SO2 emissions policy enforcement.

Development and Evaluation of a Robust Temperature Sensitive Algorithm for Long-Term NO2 Gas Sensor Network Data Correction
Peng Wei, Li Sun, Abhishek Anand, Qing Zhang, Zong Huixin, Zhiqiang Deng, Ying Wang, Zhi Ning*
We propose a novel Temperature Look-Up (TLU) model for NO2 gas sensor outputs in long-term applications, showing improved performance over existing ML and MLR correction methods.
🏆 Honors and Awards
- Winner, Hackathon on Applying Machine Learning for Subseasonal-to-Seasonal Climate Predictions, LEAP, Columbia University (2025)
- Travel Grant, American Association for Aerosol Research (AAAR) Conference (2023)
- Philip and Marsha Dowd Fellowship, Carnegie Mellon University (~$100,000 in tuition and stipend) (2022–2023)
- Milton Shaw Ph.D. Research Award, Department of Mechanical Engineering, CMU (2022)
- HKUST Awardee, 8th Global Young Scientists Summit, National Research Foundation, Prime Minister’s Office, Singapore (2020)
- University Grants Committee Research Travel Grant, HKUST (2019)
- Division of Environment and Sustainability Research Travel Grant, HKUST (2019)
- Hong Kong Government Innovation and Technology Fund Internship Award (2018)
- M.Sc. Excellent Student Scholarship, School of Engineering, HKUST (2017)
- Champion Award, BESTo Camp, HKUST Entrepreneurship Center (2017)
- Entrance Scholarship, School of Engineering, HKUST (2016)
- Ministry of Human Resources Development Scholarship, IIT Delhi (tuition for 4 years of undergraduate studies) (2011–2015)
🎤 Invited Talks
- Kintampo Health Research Center, Kintampo, Ghana (January 2026)
- Gridded Africa Surface Pollution Dataset (GRASP): Two Decades of Satellite-Derived Daily High-Resolution PM2.5 Measurements in Ghana.
- Environmental Protection Authority, Accra, Ghana (January 2026)
- Gridded Africa Surface Pollution Dataset (GRASP): Two Decades of Satellite-Derived Daily High-Resolution PM2.5 Measurements in Ghana.
- GRAPHS Manuscript Series, Columbia University, NY (December 2025)
- Mapping Two Decades of Daily High-Resolution PM2.5 Data in Ghana Using Machine Learning.
- Solutions for Pollution Seminar, Geochemistry Division, Columbia University, NY (October 2025)
- Atmospheric Black Carbon Measurements by Applying Image Processing Method on Filter Tapes.
- Department of Civil Engineering, University of Illinois Urbana-Champaign, IL (October 2025)
- Leveraging Satellite Measurements, Surface Monitors, and Machine Learning for Generating 20 Years of High-Resolution Daily PM2.5 in Ghana.
- SPARTAN & CAMS-Net Joint Meeting, Washington University in St. Louis, MO (June 2025)
- Two Decades of High-Resolution Daily PM2.5 in Ghana: A Machine Learning Approach.
- Lamont 75th Mini-Symposium: The Data Driven Discovery, Columbia University, NY (May 2025)
- Leveraging Satellite Measurements to Build Machine Learning Models for Estimating 20 Years of High-Resolution Gridded PM2.5 for Ghana.
- Air Sensors International Conference, Riverside, CA (May 2024)
- Low-cost methods for measurement of PM2.5 composition at African cities by exploiting existing Beta Attenuation Monitors.
🏫 Teaching
- Guest Lecture — Computing and Research Methods for Climate Data Science, Columbia University (February 2026)
- Introduced major climate datasets, tools to work with them, data structures, and research applications.
- Guest Lecture — Air Pollution & Measuring the Environment, Columbia University (November 2025)
- Delivered lecture on remote sensing principles and practical applications of NASA and ESA satellite-derived air pollution datasets.
- Future Faculty Career Program, Carnegie Mellon University (2020–2024)
- Designed to help early career researchers develop their teaching skills for a faculty career.
- Teaching Assistant, Carnegie Mellon University & HKUST
- Renewable Energy Engineering – CMU (Spring 2023)
- Fluid Mechanics – CMU (Spring 2022)
- GIS for Environmental Professionals – HKUST (Fall 2019)
- Carbon Emission Trading – HKUST (Spring 2019)
- Peer Tutor for Undergraduate Students, CMU (2022–2023)
- Physics I & II, Calculus, Differential Equations.
- Student Mentoring
- Undergraduate Research Mentor
- Columbia University: 2 Students (2025 - Present)
- CMU: 5 Students (2022 - 2024)
- Graduate Research Mentor
- Columbia University: 1 Student (2025)
- CMU: 2 Students (2023 - Present)
- Undergraduate Research Mentor
🤝 Service
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Session Chair, AAAR: Advancing Aerosol Science Through Data Analysis (October 2025)
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Panel Discussion, Spartan and CAMS-Net Meeting: Low-Cost Monitoring of Atmospheric Particulate Matter (June 2025)
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Coordinator, Ocean and Climate Physics Department Seminar, Columbia University (2025–2026)
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Core Representative, Postdoc/ARS Hardship Support Fund, Columbia University (2025–Present)
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President, AAAR Student Chapter, Carnegie Mellon University (2023–2024)
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Coordinator, Center for Atmospheric Particle Studies Seminar, Carnegie Mellon University (2022–2023)
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Core Committee Member, CAPS Laboratory, Carnegie Mellon University (2021–2022)
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Journal Peer-Reviewer (2023–Present)
- Geoscientific Model Development
- Environmental Science & Technology Air
- Environment International
- Scientific Reports
- Environmental Science and Pollution Research
📸 Events
December 2025 — Presented research in the NASA Health and Air Quality (HAQ) session at AGU 2025, New Orleans, Louisiana.
June 2025 — Presented at the CAMS-Net and SPARTAN meeting at Washington University in St. Louis.
May 2025 — Attended the WCRP Global km-Scale Hackathon at GFDL, Princeton University.
January 2025 — Team El Ninos won 1st place at the LEAP Hackathon "Harnessing Machine Learning to Improve Subseasonal-to-Seasonal Climate Predictions" at Columbia University.
August 2022 — Awarded the prestigious Dowd Fellowship by the School of Engineering at Carnegie Mellon University.