Virginia Tech® home

CHCI Welcomes Chris Brown, Dawei Zhou and Sunwook Kim

CHCI welcomes three new members: Chris Brown, Dawei Zhou and Sunwook Kim.

Chris Brown
Chris Brown

Chris Brown is an Assistant Professor in the Department of Computer Science. His research interests span software engineering (SE) , digital education, and human-computer interaction (HCI), with the goal of improving the behavior, productivity, and decision-making of software engineers. Brown leads the Code World, No Blanket software engineering research group.

Some of his current and former projects include:

  • Implementing and empirically analyzing development tools – evaluating their effectiveness, practicality, and usability – to support SE work; 

  • Using interdisciplinary concepts, such as nudge theory, to design recommendations and bots to encourage the adoption of useful behaviors and tools;

  • Investigating ways to prevent unethical programming decisions that affect users, such as dark patterns and unauthorized data privacy usage; and

  • Exploring resources and interventions to improve candidate experiences in SE hiring processes and technical interviews.

In future research, Dr. Brown aims to continue to improve software quality that enhances user experiences and to examine situations in which software developers are end users of SE tools.

Dawei Zhou
Dawei Zhou

Dawei Zhou is an Assistant Professor in the Department of Computer Science and the director of the VirginiaTech Learning on Graphs (VLOG) Lab. Zhou’s prior research on novelty detection, graph mining, curriculum learning, and algorithmic fairness, with applications in financial fraud detection, cyber security, financial forecasting, social media analysis, and healthcare. He obtained his Ph.D. degree from the Computer Science Department of UIUC. He has authored more than 30 publications in premier academic venues across AI, data mining, and information retrieval (e.g., AAAI, IJCAI, KDD, ICDM, SDM, TKDD, DMKD, WWW, CIKM) and has served as Senior Program Committee and Session Chairs in various top ML and AI conferences (e.g., NeurIPS, ICML, KDD, WWW, SIGIR, ICLR, AAAI, IJCAI, etc.). He has been the key contributor and team leader in several DARPA projects. His work on rare category detection with human-AI intelligence has been selected by Computing Research Association (CRA) to showcase at the 24th CNSF Capitol Hill Science Exhibition.

One of his current research areas lies in human-AI intelligence and HCI. In online learning platforms, for example, he aims to develop a human-AI interactive curriculum generation framework for labor-optimized and trustworthy online learning platforms, which relies on interaction with human experts.  The curriculum generation framework is composed of: 

  • Human Interaction Comprehension which aims to automatically comprehend human interactions (e.g., teachers' evaluations and students' feedback) for further improving online learning platforms; 

  • Personalized Machine Teaching that generates a personalized curriculum for various students by leveraging the existing human-developed curriculum and comprehending the users' interactions; 

  • Curriculum Auditing that allows educators to supervise and audit the curriculum generation process to ensure a secure online learning experience.

Sunwook Kim
Sunwook Kim

Sunwook Kim is a Research Assistant Professor in the Department of Industrial and Systems Engineering. Sunwook’s research centers around interactions between humans and agents (such as exoskeletons, robots, and AI systems) in the workplace. Agents in the workplace are evolving fast, and work tasks often assume some forms of human-computer (or more generally agent) interactions/collaboration. 

For the past several years, he has focused on the interaction between humans and a wearable robot (or exoskeleton) in terms of work safety, human performance, and motor adaptation. With this research experience, he has been able to start pilot or funded studies on other interactive technologies in the workplace such as collaborative robots, artificial intelligence-based work agents for special populations (e.g., individuals on the autism spectrum). Other research interests include postural control and balance assessment, occupational biomechanics and exposure assessment. 

Sunwook’s current projects include:

  • Validation and application of wearable sensors for capturing kinematic responses to real-world losses of balance among balance-impaired older adults. 

  • Workplace fall prevention through slip recovery training.

  • Development of machine learning methods to support collaboration in a neurodiverse team at work.

  • Occupational Exoskeletons and the Human-Technology Partnership: Achieving Scale and Integration into the Future of Work