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Software development is undergoing a major shift from human coding to AI generation. While the rise of “vibe coding” promises massive productivity gains, it introduces severe security risks. This talk provides a clear demonstration of AI coding risks, practical approaches to train secure agents, and insights into the future of autonomous security defense.

Modern machine learning remains dependent on a paradigm in which considerable up-front effort produces models that are monolithic, opaque, and costly to change once trained. In this talk, I will discuss three active lines of research from the AI Division at the Software Engineering Institute that aim to make ML models easier to maintain.

SCI’s undergraduate computer science program ranked No. 49 (tie) in the U.S. News & world Report’s 2027 Best College rankings, a 14-spot jump from the previous year’s list and the highest the program has ever been ranked in the U.S. News’ rankings.

In this talk, I argue that NLP is experiencing an identity crisis: it is increasingly subsumed under machine learning (ML), optimizing for predictive performance while neglecting its core scientific objective—the study of language as a system of meaning embedded in dynamic social, cultural, and epistemic contexts. We need to move beyond benchmark Illusions and establish sciences of annotation, evaluation, and veracity that embrace pluralism coupled with responsible thinking.

This talk will discuss both the method and data foundations to scale AI models for large-scale geospatial applications and science questions, covering new frameworks for spatially-explicit learning, knowledge-guided learning, task-aligned pretraining, as well as new benchmark datasets and data generation methods.

By unifying LLMs with agent-based modeling, this talk offers a forward-looking methodology for analyzing digital influence, testing intervention strategies, and understanding how automated bot agents can shape the cognitive terrain of online societies.

This talk will highlight over a decade of research at the intersection of industrial engineering, mechanical engineering, human-computer interaction, and medicine. It will showcase how a team of engineers and medical professionals are transforming the way we prepare and assess the clinical competence of medical residents through advances in simulation technology.