The International Conference on Affective Computing and Intelligent Interaction (ACII) is the premier international forum for interdisciplinary research on the design of systems that can recognize, interpret, and simulate human emotions and related affective phenomena. Its broad scope includes: multi-modal recognition or synthesis of human affect, psychological, cognitive, and neurological affect modeling, affective computing for social and behavioral sciences, and affective interactions for social robotics and virtual agents. The conference presents latest research in these and related areas and it plays an important role in shaping related scientific, academic, and educational programs. ACII 2019 is based around the theme of Affective Computing for ALL (AC4ALL) and will focus on inclusive technology, inclusive design principles and inclusive user interfaces which consider the full range of human diversity with respect to ability, language, culture, gender, age and other forms of human difference. Besides the main conference program, the conference will also feature workshops, tutorials, exhibitions, and a doctoral consortium. This project is to support the travel of approximately 8 U.S. Ph.D. students to attend the 8th ACII conference to be held from October 3rd to 6th, 2019 in Cambridge, UK. Besides attending the main conference program, the Ph.D. students will also attend the Doctoral Consortium, where they will share their research results with the community and receive feedback from senior researchers in the field. This will help the students not only learn the state of the art in affective computing research but also have an opportunity to present their own work to, and receive feedback from, an invited committee of faculty and industry researchers along with other students working in related areas. The event organizers will make a particular effort to engage underrepresented students (in particular, women and minorities) to maximize the benefits of the NSF support.

The specific goals of the doctoral consortium are to provide an opportunity for face-to-face interaction and constructive feedback for doctoral research of student participants; to promote networks among Ph.D. students working in the related area; to promote networks between Ph.D. students and researchers from academia and industry working in the related area; to develop a supportive community of scholars in the affective computing field; to support the next generation of researchers and provide advice on academic, research, industrial, and non-traditional career paths in the field; and to support technical and culture interactions between American students and their counterparts from other countries. The Doctoral Consortium solicits extended abstract (4 pages, plus 1 page for references) from students from any U.S. Ph.D. granting institution whose research falls within the Affective Computing field. Students are expected to be the sole authors on their submission. For student selection, the DC committee is committed to student and research diversity. The event organizers will make a particular effort to achieve a diversity of research topics, disciplinary backgrounds, methodological approaches, and home institutions in ACII 2019 Doctoral Consortium cohort. Each student participant will be assigned a mentor based upon similarity of research interests and experience, and have a one-one-one meeting to discuss the work. There will be a Doctoral Consortium poster session, in which all participants will present their doctoral work or a recent paper that is part of their doctoral work.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

National Science Foundation (NSF)
Division of Information and Intelligent Systems (IIS)
Standard Grant (Standard)
Application #
Program Officer
Tatiana Korelsky
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Texas A&M Engineering Experiment Station
College Station
United States
Zip Code