
JOHN SMITH
Associate Professor Atlantic University
jsmith@gmail.com
01323456789
517 St/Athens
About
Introduction:
John Smith IV currently works at USAA As a Research Scientist in Marketing (Member Insights), utilizing expertise in more Qualitative UX methods (Usability, Ethnography, etc.) Dr. Cook's research portfolio focuses in topics Human Factors,Cognitive Psychology, Motor Control & Coordination, Quantitative Psychology. Their most recent publication is 'Other People’s Posture: Visually induced motion sickness from naturally generated optic flow.
Skills and Expertise:
Statistical Analysis
Task Analysis
Innovation
Experimental
Design Thinking
Usability
Research Stats:
72
Publications
1,847
Citations
23
h-index
15+
Years Exp.
15
Journals
11
Proceedings
30
Conferences
Featured
PUBLICATIONS
Latest Publications
Title: "Perceptual Validation of Nonlinear Postural Predictors of Visually Induced Motion Sickness."
John Smith, Qadir
IEEE Journal of Special Topics in VR
[Impact Factor: 8.7]
Virtual reality (VR) technology has become increasingly prevalent in our society and has been used for a myriad of applications ranging from psychotherapy to training members of the military....




Title: "Perceptual Validation of Nonlinear Postural Predictors of Visually Induced Motion Sickness."




John Smith, Qadir
IEEE Journal of Special Topics in VR
[Impact Factor: 8.7]
Virtual reality (VR) technology has become increasingly prevalent in our society and has been used for a myriad of applications ranging from psychotherapy to training members of the military....
Title: 'Perceptual Validation of Nonlinear Postural Predictors of Visually Induced Motion Sickness.'
John Smith, Qadir
IEEE Journal of Special Topics in VR
[Impact Factor: 8.7]
Virtual reality (VR) technology has become increasingly prevalent in our society and has been used for a myriad of applications ranging from psychotherapy to training members of the military....




List of Publications
Peer-Reviewed Conferences
 Kim, J., Thompson, R. (2023). Efficient Adaptation of Pretrained Language Models via Gradient Pruning. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023). Read Here...
 Kim, J., Liu, Z., Patel, A. (2022). Cross-Lingual Transfer Learning with Syntactic Guidance. In Empirical Methods in Natural Language Processing (EMNLP 2022). Read Here...
 Kim, J., et al. (2021). Few-Shot Intent Detection Using Semantic Priors. In North American Chapter of the ACL (NAACL 2021). Read Here...
Workshops & Posters
 Kim, J. (2022). Ethical Challenges in Deploying Multilingual Chatbots. ACL Ethics in NLP Workshop. Read Here...
 Kim, J., Chen, L. (2020). Modeling Code-Switching in Bilingual Conversations. Workshop on Computational Modeling of Multilingualism. Read Here...
RESEARCH GALLERY
Research Projects
Active
Real-Time AI Infrastructure for Emergency Response (RAID)'
Developing a scalable AI platform to analyze live data streams (video, sensor, social media) for disaster management teams.
Funded by National Science Foundation (NSF), Portal Link
Planning
Robustness in Autonomous Systems
Investigating methods to make AI-driven systems (cars, drones) more resilient to unexpected real-world conditions and adversarial attacks.
Funded by Defense Advanced Research Projects Agency (DARPA), Portal Link
Completed
Low-Latency ML on Edge Devices
A project focused on optimizing machine learning models to run efficiently on low-power hardware for IoT applications.
Internal University Grant, Portal Link
ACADEMICS
Professional Journey
 Appointments
2015 - Present
Associate Professor & Principal Investigator
Department of Computer Science, University of Technology
Teaching graduate and undergraduate courses in AI, distributed systems, and cybersecurity. Leading the AI Systems Research Lab.
2010 - 2015
Assistant Professor
Department of Computer Science, University of Technology
Developed curriculum for AI and real-time systems courses. Established research collaborations with industry partners.
2010 - 2015
Postdoctoral Researcher
AI Research Institute, Stanford University)
Conducted research on distributed AI systems and real-time machine learning algorithms.
 Education
Ph.D. in Computer Science
2007 - 2012
Massachusetts Institute of Technology
Dissertation: "Real-time Constraints in Distributed AI Systems"
M.S. in Computer Science
2006 - 2007
Carnegie Mellon University
Dissertation: "Real-time Constraints in Distributed AI Systems"
B.S. in Computer Engineering
2001 - 2005
Carnegie Mellon University
Graduated with honors, focus on software systems and algorithms
Contact Information
kim@swarthmore.edu
Phone
+1 (555) 123-4567
Office
Computer Science Building, Room 405
University of Technology
Office Hours
Monday & Wednesday: 2:00 PM - 4:00 PM
Friday: 10:00 AM - 12:00 PM
© 2026 John Smith. All rights reserved.