Reza Asadi
PhD Student
Biography
Reza Asadi is a PhD student in the Computer Science program at Northeastern University's Khoury College of Computer Sciences, advised by Professor Harriet Fell. His research interests include speech processing, speech recognition and affective computing. He has a Master of Science degree in Mechatronics from Amirkabir University of Technology, Iran, and a Bachelor of Science degree in Mechanical Engineering from Sharif University of Technology, Iran.
Education
- MS in Mechatronics, Amirkabir University of Technology - Iran
- BS in Mechanical Engineering, Sharif University of Technology - Iran
About Reza
- Hometown: Yazd, Iran
- Field of Study: Computer Science
- PhD Advisor: Harriet Fell
What are your research interests?
I am interested in using audio, speech, and natural language processing techniques to recognize the verbal and non-verbal contents of the user speech.
What’s one problem you’d like to solve with your research/work?
Recently, I have been developing and evaluating technologies that can help users with their public speech.
What aspect of what you do is most interesting?
The most interesting part of my research is the creation of intelligent virtual agents which can detect human intents and emotions and react properly to them.
What are your research or career goals, going forward?
I am currently working on my PhD dissertation.
Recent Publications
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RoboCOP: A Robotic Coach for Oral Presentations
Citation: Trinh, H., Asadi, R., Edge, D., & Bickmore, T. (2017). RoboCOP: A Robotic Coach for Oral Presentations. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. -
Virtual Agents in the Classroom: Experience Fielding a Co-presenter Agent in University Courses
Citation: Bickmore, T., Trinh, H., Hoppmann, M., & Asadi, R. (2016, September). Virtual Agents in the Classroom: Experience Fielding a Co-presenter Agent in University Courses. In International Conference on Intelligent Virtual Agents (pp. 154-163). Springer International Publishing. -
Real-Time Presentation Tracking Using Semantic Keyword Spotting
Citation: Asadi, R., Fell, H. J., Bickmore, T., & Trinh, H. (2016). Real-Time Presentation Tracking Using Semantic Keyword Spotting. Interspeech 2016, 3081-3085.