Sandeep Kuttal
Bio
Sandeep Kaur Kuttal is an Associate Professor in the Department of Computer Science at NC State University. She directs the Human Factors + Experience Engineering Lab [HFXE] (Discovering and Inventing for Human-Centered SE and AI). Prior to joining NC State she was an Assistant professor at the Tandy School of Computer Science at the University of Tulsa, Oklahoma. She is actively involved in diversity and inclusion through her teaching, research, and service. She is also a member of the College of Engineering AI Advisory Team.
Her research is novel and multidisciplinary. It straddles several areas – Human-Computer Interaction, Software Engineering, Artificial Intelligence, End-User Programming, Gender Studies and Empirical Evaluation. She is interested in inventing technologies by studying and modeling both human factors and software engineering factors in the context of programmers’ tasks. The primary goal of her research is to empower problem-solving professionals (experts, novice programmers, end-user programmers, and underrepresented communities) by integrating SE activities into their existing workflow without changing the nature of their work or priorities using/inventing HCI methods. Her stature is bolstered by dozens of publications, two prestigious research NSF CAREER and U.S. Air Force Young Investigator (YIP) Awards, two best paper awards (one at an international conference with 3,500+ submissions) and one honorable mention (an international conference with 4,500+ submissions), conference committee memberships, keynote/invited lectures, and nominated for teaching and mentoring excellence. She received a letter from the U.S. Senator James M. Inhofe congratulating her for receiving the YIP award.
For more information, check my personal website.
Education
Ph.D. Computer Science University of Nebraska, Lincoln 2014
M.Tech Computer Science and Engineering Punjab Technical University, India 2007
B.Tech Computer Science and Engineering Punjab Technical University, India 2001
Area(s) of Expertise
Advanced Learning Technologies
Artificial Intelligence and Intelligent Agents
Graphics, Human Computer Interaction, & User Experience
Software Engineering and Programming Languages
Publications
- Supplemental Material for Where Will They Click Next? A Social Foraging Model for Collaborating Teams , Open MIND (2026)
- Supplemental Material for Where Will They Click Next? A Social Foraging Model for Collaborating Teams , Zenodo (CERN European Organization for Nuclear Research) (2026)
- Analyzing Gender-Based Dynamics in Remote Pair Programming Interactions , 2025 IEEE/ACM SIXTH WORKSHOP ON GENDER EQUALITY, DIVERSITY, AND INCLUSION IN SOFTWARE ENGINEERING, GEICSE (2025)
- Breaking the Silos: An Actionable Framework for Recruiting Diverse Participants in SE , 2025 IEEE/ACM 47TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING: SOFTWARE ENGINEERING IN SOCIETY, ICSE-SEIS (2025)
- Metacognition in Software Teams: Investigating Individual Expertise in Cognitive Knowledge and Regulation , Communications in computer and information science (2025)
- The Hidden Burden: Insights Into Women’s Lived Experiences In Computing , (2025)
- Unveiling Value-Cost Dynamics in StackOverflow with IFT-Enhanced Clustering , Communications in computer and information science (2025)
- Bridging Perspectives: Unveiling Racial Dynamics in Remote Pair Programming Communication , Lecture notes in computer science (2024)
- Developers’ information seeking in Question & Answer websites through a gender lens , Journal of Computer Languages (2024)
- Diversity’s Double-Edged Sword: Analyzing Race’s Effect on Remote Pair Programming Interactions , ACM Transactions on Software Engineering and Methodology (2024)
Grants
The research will involve laboratory studies, interviews, surveys and case studies. An iterative approach incorporating field studies, theory development, technology design and deployment, and empirical evaluations will be employed. The continuous data collection, evaluation and refinement cycle will incrementally evolve PairBuddy functionality.
Software engineering candidates commonly participate in high-pressure technical interviews, or whiteboard interviews. Critics have argued that these types of interviews unnecessarily stress and filter out otherwise qualified candidates, yet it remains a standard hiring practice. This project proposes a series of randomized control trials to understand how these practices influence performance of candidates, identify any bias or confounding factors in the process, and develop interventions to make problem-solving assessment more equitable and inclusive.
Honors and Awards
- National Science Foundation CAREER Award - 2021
- U.S. Air Force Young Investigator Program Award - 2021
- Honorable Mention, International Conference on Human Factors in Computing Systems - 2021
- Best Paper, International Conference on Human Factors in Computing Systems - 2016
- Best Paper, International Conference on Global Software Engineering - 2016
- First Prize for User-Centered Design, Global User Experience Career Summit - 2014