What should we measure?
I build task-grounded benchmarks and agentic quality graders for Copilot, including Today. EmailBench evaluates whether agents complete enterprise email and productivity tasks, beyond whether their tool calls succeed.
Human-agent interaction · Evaluation · Post-training
Hyeonsu B. Kang
I focus on human-agent interaction, agent evaluation, and post-training for Microsoft Copilot. I build task-grounded benchmarks, agentic quality graders, and synthetic training data for tool use, multimodal reasoning, and adversarial robustness -- connecting model improvements to product quality, cost, and latency.
My research combines controlled experiments, behavioral measurement, and production evaluation to align agents with how people actually work. Previously, I developed learning tools at MIT and deployed scholarly discovery systems with AI2. With Conservation X Labs, I built team-formation algorithms for global innovation contests offering over $2M in prize funding.
I earned my Ph.D. in Human-Computer Interaction at Carnegie Mellon.
Research
How can evaluations improve agents?
I connect evaluation to synthetic data and post-training. VLM-SlideEval studies slide comprehension and perturbation sensitivity; my synthetic red-teaming work pairs everyday tasks with adversarial variants to test prompt-injection defenses and their effects on legitimate task performance.
What do people actually want?
I study how behavior can inform better objectives for AI. Users Mispredict examines where stated preferences diverge from choices; my Semantic Scholar work tests interventions with real users.
Publications
Google Scholar2026
Users Mispredict What Drives Their Preferences for AI Writing Assistance
* Equal contribution: Zana Buçinca and Hyeonsu B. Kang.
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EmailBench: A Benchmark for Evaluating LLM Agents on Enterprise Email and Productivity Tasks
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From Everyday Tasks to Red-Team Cases: Synthetic Generation and Practical Defenses for AI Agents
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PIKE: Graph-Enhanced Email Retrieval via Critic-Guided Expansion
2025
VLM-SlideEval: Evaluating VLMs on Structured Comprehension and Perturbation Sensitivity in PPT
BioSpark: Beyond Analogical Inspiration to LLM-augmented Transfer
Best Paper Honorable Mention
Inkspire: Supporting Design Exploration with Generative AI through Analogical Sketching
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Hypoveil: A Privacy-Utility Trade-off Aware Framework for Collaborative Multi-Agent Reasoning
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Investigating Explainability with Privacy-Preserving Multi-agent Systems
2024
Mitigating Barriers to Public Social Interaction with Meronymous Communication
Best Paper Award
PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers
The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces
Imitation of Life: A Search Engine for Biologically Inspired Design
2023
2022
Augmenting Scientific Creativity with an Analogical Search Engine
Threddy: An Interactive System for Personalized Thread-based Exploration and Organization of Scientific Literature
From Who You Know to What You Read: Augmenting Scientific Recommendations with Implicit Social Networks
Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas
Augmenting Scientific Creativity with Retrieval across Knowledge Domains
Earlier publications · 2017–2019
2019
Matching Open Innovation Projects for Analogical Feedback Exchange
2018
Paragon: An Online Gallery for Enhancing Design Feedback with Visual Examples
Custom Blocks in StarLogo Nova: A Template-Based Approach to Abstraction for Improved Ease of Use and Expressive Power