Hao Wu
Hao Wu
Education
- MS in Computer Science, University of Virginia
- MS in Applied Mathematics, University of Washington
- BS in Applied Mathematics, Sichuan University – China
About Me
- Hometown: Qingdao, China
- Field of Study: Machine Learning
- PhD Advisors: Jan-Willem van de Meent
Biography
Hao Wu is a PhD student in the Machine Learning program at Northeastern University, advised by Jan-Willem van de Meent. Hao’s current research is focused on variational inference, probabilistic programming, and machine learning. Prior to joining Northeastern, Hao researched computational user behavior modeling, time-dependent differential equations, and large linear systems. Hao works on mathematical and statistical models to solve abstract and practical problems. Hao earned his Bachelor’s of Science degree from Sichuan University in China, his Master’s in Applied Mathematics from the University of Washington, and his Master’s in Computer Science from the University of Virginia.
What are the specifics of your graduate education (thus far)?
Currently I focus on research work in variational inference, probabilistic programming, and machine learning. Before coming here, my main works included computational user behavior modeling, time-dependent differential equations, and large linear systems.
What are your research interests?
I have been working on mathematical and statistical models to solve abstract and practical problems. Through my previous research I became very interested in improving learning and prediction, especially how to represent uncertainty and dynamics.
What’s one problem you’d like to solve with your research/work?
I am trying to design better variational autoencoder framework for sampling and unsupervised learning.
What aspect of what you do is most interesting?
Though deep learning methods have impressive scalability, the data-driven model still needs improvement when it deals with uncertainty, unobservable information, and dynamic systems.
What are your research or career goals, going forward?
I would like to continue my research work after my PhD program.
Where did you grow up or spend your most defining years?
I grew up in my hometown in China, and since 2014 I have studied in Seattle for one year and then in Charlottesville for one and a half years.
Where did you study for your undergraduate degree?
I earned my undergraduate degree from Sichuan University in China.
Education
- MS in Computer Science, University of Virginia
- MS in Applied Mathematics, University of Washington
- BS in Applied Mathematics, Sichuan University – China
About Me
- Hometown: Qingdao, China
- Field of Study: Machine Learning
- PhD Advisors: Jan-Willem van de Meent
Biography
Hao Wu is a PhD student in the Machine Learning program at Northeastern University, advised by Jan-Willem van de Meent. Hao’s current research is focused on variational inference, probabilistic programming, and machine learning. Prior to joining Northeastern, Hao researched computational user behavior modeling, time-dependent differential equations, and large linear systems. Hao works on mathematical and statistical models to solve abstract and practical problems. Hao earned his Bachelor’s of Science degree from Sichuan University in China, his Master’s in Applied Mathematics from the University of Washington, and his Master’s in Computer Science from the University of Virginia.
What are the specifics of your graduate education (thus far)?
Currently I focus on research work in variational inference, probabilistic programming, and machine learning. Before coming here, my main works included computational user behavior modeling, time-dependent differential equations, and large linear systems.
What are your research interests?
I have been working on mathematical and statistical models to solve abstract and practical problems. Through my previous research I became very interested in improving learning and prediction, especially how to represent uncertainty and dynamics.
What’s one problem you’d like to solve with your research/work?
I am trying to design better variational autoencoder framework for sampling and unsupervised learning.
What aspect of what you do is most interesting?
Though deep learning methods have impressive scalability, the data-driven model still needs improvement when it deals with uncertainty, unobservable information, and dynamic systems.
What are your research or career goals, going forward?
I would like to continue my research work after my PhD program.
Where did you grow up or spend your most defining years?
I grew up in my hometown in China, and since 2014 I have studied in Seattle for one year and then in Charlottesville for one and a half years.
Where did you study for your undergraduate degree?
I earned my undergraduate degree from Sichuan University in China.
© 2023 Northeastern University
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
x
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...
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About
Programs
Experiential Learning
Research
Life at Khoury
Information for...
© 2023 Northeastern University
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
Khoury Social
Contact Khoury
440 Huntington Avenue, 202 West Village H
Boston, MA 02115
617.373.2462
TTY: 617.373.3768
x
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...
x
About
Programs
Experiential Learning
Research
Life at Khoury
Information for...