TY - GEN
T1 - The ASU-DCU International Research and Workforce Development Program on Sensors and Machine Learning
AU - Spanias, Andreas
AU - Narayanaswamy, Vivek
AU - Forzani, Erica
AU - Raupp, Greg
AU - Kellam, Nadia
AU - O'Donnell, Megan
AU - Barnard, Wendy
AU - Larson, Jean
AU - O'Connor, Noel
AU - Dunne, Nicholas
AU - Daniels, Stephen
AU - Little, Suzanne
N1 - Funding Information:
ACKNOWLEDGEMENT The IRES program is sponsored by NSF Award 2107439. Logistical support was provided by the ASU SenSIP Center and the DCU Insight Centre. The authors would like to thank DCU student mentors: Stephen Behan, Úna Britton, Julia Dietlmeier, Margaret McCaul, Aoife Morrin, Michael Scriney and ASU student mentors Vivek Narayanaswamy and Deep Pujara. Special thanks to Robina Sayed (ASU) and Breda Kiernan (DCU) for all the logistics of the program.
Funding Information:
Abstract— The Arizona State University (ASU) – Dublin City University (DCU) International Research Experiences for Students (IRES) project is a summer workforce development program that embeds students in machine learning and sensor research. This collaborative IRES program, funded by the National Science Foundation (NSF), engages faculty mentors from the Sensor, Signal, Information Processing (SenSIP) Center at ASU, and the Insight SFI Research Centre for Data Analytics and Biodesign Europe at DCU to train students in sensor design, analytics, and machine learning algorithm development. Sensor and machine learning research addresses engineering and computing problems in health care and other related applications. IRES participants are tasked with studying hardware, algorithms and software for various tasks including activity detection, gait modeling, imaging, hemochromatosis prediction, and health care analytics. Crosscutting efforts include training in international research presentations, research documentation and building awareness of international policies and standards. The program includes weekly research updates by the students, participation in workshops and continued engagement after the summer experience. This paper describes the various components of IRES sensor and machine learning research through ongoing center projects at ASU and DCU.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The Arizona State University (ASU) - Dublin City University (DCU) International Research Experiences for Students (IRES) project is a summer workforce development program that embeds students in machine learning and sensor research. This collaborative IRES program, funded by the National Science Foundation (NSF), engages faculty mentors from the Sensor, Signal, Information Processing (SenSIP) Center at ASU, and the Insight SFI Research Centre for Data Analytics and Biodesign Europe at DCU to train students in sensor design, analytics, and machine learning algorithm development. Sensor and machine learning research addresses engineering and computing problems in health care and other related applications. IRES participants are tasked with studying hardware, algorithms and software for various tasks including activity detection, gait modeling, imaging, hemochromatosis prediction, and health care analytics. Crosscutting efforts include training in international research presentations, research documentation and building awareness of international policies and standards. The program includes weekly research updates by the students, participation in workshops and continued engagement after the summer experience. This paper describes the various components of IRES sensor and machine learning research through ongoing center projects at ASU and DCU.
AB - The Arizona State University (ASU) - Dublin City University (DCU) International Research Experiences for Students (IRES) project is a summer workforce development program that embeds students in machine learning and sensor research. This collaborative IRES program, funded by the National Science Foundation (NSF), engages faculty mentors from the Sensor, Signal, Information Processing (SenSIP) Center at ASU, and the Insight SFI Research Centre for Data Analytics and Biodesign Europe at DCU to train students in sensor design, analytics, and machine learning algorithm development. Sensor and machine learning research addresses engineering and computing problems in health care and other related applications. IRES participants are tasked with studying hardware, algorithms and software for various tasks including activity detection, gait modeling, imaging, hemochromatosis prediction, and health care analytics. Crosscutting efforts include training in international research presentations, research documentation and building awareness of international policies and standards. The program includes weekly research updates by the students, participation in workshops and continued engagement after the summer experience. This paper describes the various components of IRES sensor and machine learning research through ongoing center projects at ASU and DCU.
KW - health care
KW - machine learning
KW - sensors
KW - wearables
UR - http://www.scopus.com/inward/record.url?scp=85141084333&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85141084333&partnerID=8YFLogxK
U2 - 10.1109/IISA56318.2022.9904409
DO - 10.1109/IISA56318.2022.9904409
M3 - Conference contribution
AN - SCOPUS:85141084333
T3 - 13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022
BT - 13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022
Y2 - 18 July 2022 through 20 July 2022
ER -