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Tuan-Vu Cao

Senior Scientist

+47 63 89 80 26

Digital Technologies
Kjeller

tvc@nilu.no


Cristin   Google Scholar   OrcID  

Anonymous

TUAN-VU CAO received the PhD degree in electronics engineering from the University of Oslo in 2011 with the topic of micro-power sensor interface in nanometer CMOS technology.  During his PhD, he stayed at ISN Lab at UC San Diego in a year to implement a frequency adaptive BFSK MICS band (402-405 MHz) transmitter Chip for biomedical application. He has a long experience in both Academia and Industry.

From 2011 to 2012, he worked as a Postdoctoral Fellow at NTNU (Norwegian University of Science and Technology) to design a Delta-Sigma Analog to Digital converter at 65nm CMOS technology.

From 2012-2018, he worked in Industry as Senior Engineer at WINS Instrumentation AS and Prediktor AS for various projects, such as monitoring nutrient food content, and wireless DST real time instrumentation. Since 2018, he has come back Academia by joining NILU where he is currently a Senior Scientist.

Tuan-Vu Cao has been running several national and EU projects at NILU:

Horizon Europe project MISO – Autonomous Multi-Format In-Situ Observation Platform for Atmospheric Carbon Dioxide and Methane Monitoring in Permafrost & Wetlands; (2023-2026) (The PI and project coordinator)

EEA Grant project—HAPADS – a novel air mobile monitoring system enables end-users to make information-driven decisions to mitigate air pollution exposure; (2020-2023) (Co-PI and WP leader)

EEA Grant project SmartFood project “Engaging citizens in food diversity in cities”; (2021-2024) (Co-PI and WP leader)

NFR IKTPLUSS project: AirQMan: Low Latency Air Quality Management (2021-2025) (WP leader)

NFR 273394- ‘‘Leopard-Wearable particle detector enabling safer working environments’’ (2018–2020) (Key Designer and Technical Coordinator)

His research interests include enabling technologies (advanced sensors, edge intelligence, IoT, etc…) and other autonomous systems for environmental monitoring and management.

Tuan-Vu Cao has 7 publications at NILU:

Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors

Jørstad, Per Martin; Wojcikowski, Marek; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Wojtkiewicz, Krystian; Ha, Hoai Phuong

2023

Automatic Correction of Non-Anechoic Antenna Measurements using Low-Pass Filters

Bekasiewicz, Adrian; Waladi, Vorya; Wojcikowski, Marek; Cao, Tuan-Vu

2023

Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors

Jørstad, Per Martin; Wojcikowski, Marek; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Wojtkiewicz, Krystian; Ha, Hoai Phuong

2023

Comparative Analysis of Deep Learning and Statistical Models for Air Pollutants Prediction in Urban Areas

Naz, Fareena; McCann, Conor; Fadim, Muhammad; Cao, Tuan-Vu; Hunter, Ruth; Nguyen, Trung Viet; Nguyen, Long D.; Duong, Trung Q.

2023

An NO2 sensor based on WO3 thin films for automotive applications in the microwave frequency range

Paleczek, Anna; Grochala, D.; Staszek, K.; Gruszczynski, S.; Maciak, Erwin; Opilski, Zbigniew; Kaluzynski, Piotr; Wojcikowski, Marek; Cao, Tuan-Vu; Rydosz, A.

2022

A surrogate-assisted measurement correction method for accurate and low-cost monitoring of particulate matter pollutants

Wojcikowski, Marek; Pankiewicz, Bogdan; Bekasiewicz, Adrian; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Vallejo, Islen; Ødegård, Rune Åvar; Ha, Hoai Phuong

2022

Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines

Fahim, Muhammad; Sharma, Vishal; Cao, Tuan-Vu; Canberk, Berk; Duong, Trung Q.

2022

Autonomous Multi-Format In-Situ Observation Platform for Atmospheric Carbon Dioxide and Methane Monitoring in Permafrost & Wetlands (MISO)

Climate warming is driven by increased concentrations of greenhouse gasses (GHGs) e.g., CO2 and CH4, in the atmosphere. Existing observatories are able to capture GHG information for large-scale global assessments, […]

Project period: 2023 – 2026

Ongoing

Low Latency Air Quality Management (AirQMAN)

Existing air quality (AQ) monitoring and management (AQMS) methods and evolving modelling practices across Norwegian and European cities have achieved significant improvements of AQ but further progress is needed due […]

Project period: 2021 – 2025

Ongoing

Engaging citizens in food diversity in cities (SmartFood)

“Grow your own food in the corridor of your building, reduce GHG (greenhouse gas) emission, the waste of food and energy and transportation costs! Improve your physical health by changing […]

Project period: 2021 – 2024

Ongoing

Highly Accurate and Autonomous Programmable Platform for Providing Air Pollution Data Services to Drivers and the Public (HAPADS)

HAPADS is an ambitious project that will custom design and build a novel air mobile monitoring system (devices, data acquisition, analysis, and user interface), which will enable end-users (drivers, transport […]

Project period: 2020 – 2023

Ongoing

HAPADS is an ambitious project that will custom design and build a novel air mobile monitoring system (devices, data acquisition, analysis, and user interface), which will enable end-users (drivers, transport companies, municipalities, and the at-large public) to make information-driven decisions to mitigate air pollution exposure. The project aims to develop:

  • detector design (microwave-based NO2 sensor and time-delay-integration (TDI) image-based particulate matter (PM) sensor)
  • programmable multiprocessor hardware for data acquisition and signal processing with parallel edge computing and deep learning algorithms support.

embedded software for calibration and optimization of sensors.

Tuan-Vu Cao has 7 publications at NILU:

Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors

Jørstad, Per Martin; Wojcikowski, Marek; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Wojtkiewicz, Krystian; Ha, Hoai Phuong

2023

Automatic Correction of Non-Anechoic Antenna Measurements using Low-Pass Filters

Bekasiewicz, Adrian; Waladi, Vorya; Wojcikowski, Marek; Cao, Tuan-Vu

2023

Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors

Jørstad, Per Martin; Wojcikowski, Marek; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Wojtkiewicz, Krystian; Ha, Hoai Phuong

2023

Comparative Analysis of Deep Learning and Statistical Models for Air Pollutants Prediction in Urban Areas

Naz, Fareena; McCann, Conor; Fadim, Muhammad; Cao, Tuan-Vu; Hunter, Ruth; Nguyen, Trung Viet; Nguyen, Long D.; Duong, Trung Q.

2023

An NO2 sensor based on WO3 thin films for automotive applications in the microwave frequency range

Paleczek, Anna; Grochala, D.; Staszek, K.; Gruszczynski, S.; Maciak, Erwin; Opilski, Zbigniew; Kaluzynski, Piotr; Wojcikowski, Marek; Cao, Tuan-Vu; Rydosz, A.

2022

A surrogate-assisted measurement correction method for accurate and low-cost monitoring of particulate matter pollutants

Wojcikowski, Marek; Pankiewicz, Bogdan; Bekasiewicz, Adrian; Cao, Tuan-Vu; Lepioufle, Jean-Marie; Vallejo, Islen; Ødegård, Rune Åvar; Ha, Hoai Phuong

2022

Machine Learning-Based Digital Twin for Predictive Modeling in Wind Turbines

Fahim, Muhammad; Sharma, Vishal; Cao, Tuan-Vu; Canberk, Berk; Duong, Trung Q.

2022

Autonomous Multi-Format In-Situ Observation Platform for Atmospheric Carbon Dioxide and Methane Monitoring in Permafrost & Wetlands (MISO)

Climate warming is driven by increased concentrations of greenhouse gasses (GHGs) e.g., CO2 and CH4, in the atmosphere. Existing observatories are able to capture GHG information for large-scale global assessments, […]

Project period: 2023 – 2026

Ongoing

Low Latency Air Quality Management (AirQMAN)

Existing air quality (AQ) monitoring and management (AQMS) methods and evolving modelling practices across Norwegian and European cities have achieved significant improvements of AQ but further progress is needed due […]

Project period: 2021 – 2025

Ongoing

Engaging citizens in food diversity in cities (SmartFood)

“Grow your own food in the corridor of your building, reduce GHG (greenhouse gas) emission, the waste of food and energy and transportation costs! Improve your physical health by changing […]

Project period: 2021 – 2024

Ongoing

Highly Accurate and Autonomous Programmable Platform for Providing Air Pollution Data Services to Drivers and the Public (HAPADS)

HAPADS is an ambitious project that will custom design and build a novel air mobile monitoring system (devices, data acquisition, analysis, and user interface), which will enable end-users (drivers, transport […]

Project period: 2020 – 2023

Ongoing