Reflections on Successful Research in Artificial Intelligence: An Interview with Yolanda Gil

AI Magazine ◽  
2019 ◽  
Vol 40 (4) ◽  
pp. 6-8
Author(s):  
Yolanda Gil ◽  
Biplav Srivastava ◽  
Ching-Hua Chen ◽  
Oshani Seneviratne
Keyword(s):  
Artificial Intelligence ◽  
Southern California ◽  
Rensselaer Polytechnic Institute ◽  
Polytechnic Institute ◽  
Editorial Team ◽  
University Of Southern California ◽  
The University ◽  
Information Sciences

This article contains the observations of Yolanda Gil, director of knowledge technologies and research professor at the Information Sciences Institute of the University of Southern California, USA, and president of Association for Advancement of Artificial Intelligence who was recently interviewed about the factors that could influence successful AI research. The editorial team interviewers included members of the special track editorial team from IBM Research (Biplav Srivastava, Ching-Hua Chen) and Rensselaer Polytechnic Institute (Oshani Seneviratne).

scholarly journals Research in Progress at the Information Sciences Institute, University of Southern California

AI Magazine ◽  
2017 ◽  
Vol 1 (1) ◽  
pp. 22
Author(s):  
Robert Balzer ◽  
Lee Erman ◽  
Martin Feather ◽  
Neil Goldman ◽  
Philip London ◽  
...  
Keyword(s):  
Southern California ◽  
Research Center ◽  
University Of Southern California ◽  
New Concepts ◽  
The University ◽  
Computer Facility ◽  
Information Sciences

ISI is an off-campus research center in the University of Southern California's School of Engineering. The Institute engages in a broad set of research and application oriented projects in the computer sciences, ranging from advanced research efforts aimed at producing new concepts to operation of a major Arpanet computer facility.

scholarly journals What I Wish I Had Known Early in Graduate School but Didn’t

AI Magazine ◽  
2020 ◽  
Vol 41 (1) ◽  
pp. 90-100
Author(s):  
Sven Koenig
Keyword(s):  
Artificial Intelligence ◽  
Computer Science ◽  
Nobel Prize ◽  
Graduate School ◽  
Southern California ◽  
University Of Southern California ◽  
The University ◽  
Turing Award

Begin with the end in mind!1 PhD students in artificial intelligence can start to prepare for their career after their PhD degree immediately when joining graduate school, and probably in many more ways than they think. To help them with that, I asked current PhD students and recent PhD computer-science graduates from the University of Southern California and my own PhD students to recount the important lessons they learned (perhaps too late) and added the advice of Nobel Prize and Turing Award winners and many other researchers (including my own reflections), to create this article.

scholarly journals Teaching Undergraduate Artificial Intelligence Classes: An Experiment with an Attendance Requirement

2020 ◽  
Vol 34 (09) ◽  
pp. 13374-13380
Author(s):  
Sven Koenig ◽  
Tansel Uras ◽  
Liron Cohen
Keyword(s):  
Artificial Intelligence ◽  
Southern California ◽  
Course Evaluation ◽  
Large Impact ◽  
University Of Southern California ◽  
The University

We report on an experiment that we performed when we taught the undergraduate artificial intelligence class at the University of Southern California. We taught it – under very similar conditions – once with and once without an attendance requirement. The attendance requirement substantially increased the attendance of the students. It did not substantially affect their performance but decreased their course ratings across all categories in the official course evaluation, whose results happened to be biased toward the opinions of the students attending the lectures. For example, the overall rating of the instructor was 0.89 lower (on a 1-5 scale) with the attendance requirement and the overall rating of the class was 0.85 lower. Thus, the attendance requirement, combined with the policy for administering the course evaluation, had a large impact on the course ratings, which is a problem if the course ratings influence decisions on promotions, tenure, and salary increments for the instructors but also demonstrates the potential for the manipulation of course ratings.

Reflections on the Ingredients for Success in AI Research: An Interview with Arvind Gupta

AI Magazine ◽  
2019 ◽  
Vol 40 (4) ◽  
pp. 24-27
Author(s):  
Arvind Gupta ◽  
Biplav Srivastava ◽  
Daby Sow ◽  
Ching-Hua Chen ◽  
Oshani Seneviratne
Keyword(s):  
Artificial Intelligence ◽  
Chief Executive Officer ◽  
Silicon Valley ◽  
Chief Executive ◽  
Rensselaer Polytechnic Institute ◽  
Polytechnic Institute ◽  
Editorial Team ◽  
Business And Society ◽  
Artificial Intelligence Research ◽  
Leadership Policy

This article contains the observations of Arvind Gupta, who has over 22 years of experience in leadership, policy, and entrepreneurial roles, in both the Silicon Valley and India. Gupta was recently interviewed about the factors that could influence successful artificial intelligence research. At the time of the interview, Gupta was the chief executive officer of MyGov, India. During our interview, he shared with the editorial team his perspectives on investing in artificial intelligence innovations for business and society, in India. The interviewers included members of the special track edito­rial team from IBM (Biplav Srivastava, Daby Sow, and Ching-Hua Chen) and Rensselaer Polytechnic Institute (Oshani Seneviratne).

The Effects of Presentation on Noise and Dental Appliances on Speech

1981 ◽  
Vol 24 (1) ◽  
pp. 151-151
Author(s):  
Lillian Glass ◽  
Sharon R. Garber ◽  
T. Michael Speidel ◽  
Gerald M. Siegel ◽  
Edward Miller
Keyword(s):  
Southern California ◽  
University Of Southern California ◽  
University Of Minnesota ◽  
School Of Medicine ◽  
Southern California School ◽  
School Of Dentistry ◽  
The University

An omission in the Table of Contents, December JSHR, has occurred. Lillian Glass, Ph.D., at the University of Southern California School of Medicine and School of Dentistry, was a co-author of the article "The Effects of Presentation on Noise and Dental Appliances on Speech" along with Sharon R. Garber, T. Michael Speidel, Gerald M. Siegel, and Edward Miller of the University of Minnesota, Minneapolis.

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