Adnan Abbas

We spend about one-third of our lives at work. Given its central role in our everyday lives, it is important that our work aligns with our values and long-term goals. Achieving this alignment requires purposeful planning and self-reflection: as Will Durant once wrote, “We are what we repeatedly do. Excellence, then, is not an act, but a habit”. In today’s fast-paced and demanding work environments, cultivating such habits is more crucial than ever. My research examines how technology can meaningfully support this process.

I am a third-year PhD student in Computer Science at Virginia Tech, advised by Dr. Sang Won Lee. Within Human–Computer Interaction, I explore how technology can support self-reflection, self-regulation, and productivity. In particular, I study conversational interaction as a medium for reflection: talking through our plans can help us externalize intentions, evaluate progress, and bring new ideas - yet sustaining these practices over time is challenging. This raises key research questions:

• How can we design conversational agents that sustain engagement over time?
• In what ways can such systems foster positive behavior change?
• And, as large language models (LLMs) increasingly take proactive, agentic roles, how do people engage with these agents in personal productivity contexts?

To answer these questions, I design and build interactive human–AI systems, combining mixed-methods approaches with field studies to examine their impact in real-world settings.

Before starting graduate school, I worked as an Educational Technology Engineer, where I developed interactive courses to teach XR development, including WebXR, A-Frame and VR Applications with Unity. During my undergraduate studies at LUMS, I conducted research under the supervision of Dr. Zafar Ayyub Qazi on optimizing the design of control planes in cellular networks.