About Me

Yuhao Wang was born in China. She's currently a Ph.D. student under the supervision of Dr. Arnab Bhattacharyya 's group, in school of computing, National University of Singapore on Artificial Intelligence and Causality. In spring 2022, she served as a visiting researcher with the Causality program at the Simons Institute, UC Berkeley . Between 2018 and 2020, funded by KPN, she worked as a researcher in Professor Mykola Pechenizkiy 's group on the Deep Learning in Core and Edge (DLCE) project at the Eindhoven University of Technology. She received her master's degree under the supervison of Dr. Ivan Wang-Hei Ho at the Hong Kong Polytechnic University, and her bachelor’s degree in Electronics Science and Technology from Northwest University in China.

Yuhao is broadly interested in discover causal structure from observational data leveraging modern machine learning methods; drawing valid causal conclusions from data is impeded by various factors, such as the presence of unmeasured confounders, missing data, and measurement error; estimating causal effects from finite samples. Her research works are available at her Google Scholar


Aug 5 , 2022 I am a program committee member for the Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23)
July 20, 2022 New paper: Learning High-dimensional Gaussians from Censored Data , code implementation is available here
Mar 22, 2022 Our paper Learning Sparse Fixed-Structure Gaussian Bayesian Networks accepted by AISTATS
Feb 18, 2022 Our paper Identifiability of AMP Chain Graph Models accepted by AAAI
Aug 20, 2021 Started as a PhD student in NUS, Singapore.

Recent Works

Learning Sparse Fixed-Structure Gaussian Bayesian Networks
Arnab Bhattacharyya, Davin Choo, Rishikesh Gajjala, Sutanu Gayen, and Yuhao Wang

[ pdf] [presentation] [code]

The 25th International Conference on Artificial Intelligence and Statistics, 2022

Identifiability of AMP Chain Graph Models
Yuhao Wang and Arnab Bhattacharyya

[ pdf] [presentation] [code] [Video demo]

The Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Causal Discovery from Incomplete Data: A Deep Learning Approach
Yuhao Wang, Vlado Menkovski, Hao Wang, Xin Du, Mykola Pechenizkiy

[pdf ] [presentation ] [poser]

AAAI StarAI Workshop, 2020.

VANET Meets Deep Learning: The Effect of Packet Loss on the Object Detection Performance
Yuhao Wang, Vlado Menkovski, Ivan Wang-Hei Ho, Mykola Pechenizkiy

[pdf ] [presentation ]

IEEE 89th Vehicular Technology Conference (VTC2019-Spring), 2019.

Joint Deep Neural Network Modelling and Statistical Analysis on Characterizing Driving Behaviors
Yuhao Wang and Ivan Wang-Hei Ho

[pdf ] [poster ]

IEEE 29th Intelligent Vehicles Symposium (IV), 2018.

On-Road Feature Detection and Fountain-Coded Data Dissemination in Vehicular Ad-hoc Networks
Yuhao Wang and Ivan Wang-Hei Ho

[pdf ] [video demo ] [presentation ]

IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017.

Get In Touch

Feel free to contact me if you are interested in my work or want to have some discussions with me.