Announcing Capital One's 2026 UIUC AI Awardees

Announcing the Center for Generative AI Safety, Knowledge Systems, and Cybersecurity (ASKS) 2026–2027 Capital One Research Awardees from the University of Illinois

As we look toward the 2026–2027 academic year, we continue to partner with institutions that lead the global conversation on the future of intelligence. We are thrilled to announce this year’s cohort of research and fellowship awardees from the University of Illinois, whose pioneering work addresses the most critical frontier in technology today: Agentic AI.

From the way machines “think” and “imagine” to the hardware that powers them and the safety protocols that govern them, these five projects represent Capital One’s holistic push toward AI that is not only powerful but also faithful, safe, and creative.

The 2026–2027 Research Awardees

1. Ensuring Intellectual Honesty

Advancing LLM Reasoning Faithfulness without Faithfulness Rewards
Faculty: Hao Peng

Professor Peng is tackling the “hallucination” problem at its core. By developing methods to ensure large language models (LLMs) follow a logical, faithful reasoning path—without relying on traditional, often biased, reward systems—this work ensures that when an AI gives an answer, the “why” behind it is actually true, a critical component for trustworthy financial applications.

TrACE-Contrast: Faithful & Consistent Code Reasoning via Trace-Aware Contrastive Learning
Faculty: Talia Ringer and Reyhan Jabaarvand

Writing code is one thing; understanding how it executes is another. Professor Ringer’s project uses contrastive learning to align a model’s code generation with its actual execution “trace.” This ensures that AI-generated software is verified and logically sound, which is vital for maintaining the integrity of our core technology systems.

2. Bridging the Gap: Agency & Imagination

Creative LLM Agents based on Thinking with Imagination
Faculty: Heng Ji

Moving beyond rote instruction-following, Professor Ji is exploring how AI can “think with imagination.” By allowing agents to visualize multiple potential outcomes and creative paths before acting, this research opens new doors for AI in design, complex problem-solving, and human-AI collaboration across Capital One’s product development life cycle.

3. Defining the Safety Guardrails

SafeAgency: Safety Guaranteed Agentic AI
Faculty: Sava Misailovic and Gagandeep Singh

As we grant AI the agency to act in physical and digital environments, safety cannot be an afterthought. Professor Misailovic is developing frameworks for “Safety Guaranteed” AI, using formal verification to ensure that autonomous agents operate within strictly defined, mathematically proven safety boundaries. This work directly supports Capital One’s commitment to responsible AI deployment.

When Magic Goes Wrong: Identifying and Understanding Failures of Agentic AI Systems in Multi-Turn and Sequential Tasks
Faculty: Katherine Driggs-Campbell

In complex, multistep tasks, even a small error can snowball into a catastrophic failure. Professor Driggs-Campbell is investigating exactly where and why these “agentic” systems break down. By diagnosing these magic-gone-wrong moments, her team is building the resilience needed for AI to operate in the unpredictable real world, ensuring stability for our customers.

The 2026-2027 Fellowship Awardees

These Ph.D. students are receiving fellowship awards to support their breakthrough research in multimodal foundation models, visual perception and privacy-preserving data analytics.

Hyeonjeong Ha
Hyeonjeong Ha is a second-year Ph.D. student at UIUC, advised by Professor Heng Ji. Her research enhances the visual perception of multimodal LLMs through fine-grained, structured understanding, aiming to bridge human-like perception and trustworthy reasoning for more reliable real-world applications. She has published as first author in top-tier conferences including ACL and NeurIPS, and actively contributes to the research community as a reviewer for leading venues.

Jeonghwan Kim
Jeonghwan Kim is a Ph.D. candidate in computer science at the University of Illinois Urbana-Champaign, advised by Professor Heng Ji. His research focuses on multimodal foundation models that bridge fine-grained visual perception, reasoning, and embodied intelligence. Prior to his work on multimodal AI, he conducted research in natural language processing, including multi-hop question answering, retrieval-augmented generation, and numerical reasoning. His work has appeared in leading venues such as NeurIPS, ICLR, ACL, EMNLP, NAACL, and CVPR, including a NeurIPS 2025 Spotlight paper on part-level visual understanding in large multimodal models.

Yizhuo Chen
Yizhuo Chen is a Ph.D. candidate in computer science at the University of Illinois
Urbana-Champaign, advised by Prof. Tarek Abdelzaher. His research centers on
trustworthy machine learning and foundation models for sensing, with a particular focus on privacy-preserving data analytics and the safe use of sensitive data in generative AI. His work has appeared at venues including ICML and CVPR, and he has collaborated with industry research labs at JPMorgan Chase and Amazon. He received his B.Sc. from Zhejiang University in 2021.

A Vision for the Future

These awards provide the essential resources from research stipends to dedicated time that allow faculty at the University of Illinois to turn these ambitious theories into tangible breakthroughs. Throughout the 2026–2027 year, these scholars will present their findings in a series of collaborative seminars, inviting the Capital One community to witness the next evolution of AI.

Congratulations to the ASKS 2026–2027 awardees! We look forward to a year of discovery and breakthrough innovation born from these multisector collaborations..

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