August 2026 In the News
Qixin Zhang receives Best Paper Runner-Up Award at MEAS Workshop
Qixin Zhang, a PhD student in Computer Science and Engineering, received the Best Paper Runner-Up Award at the Multi-Agent Embodied Intelligent Systems (MEAS) Workshop at the 2026 Computer Vision and Pattern Recognition Conference (CVPR). Zhang's paper, titled “Multi-Agent Video Prediction: Self-Correcting Conditional Frames for Dynamic Scene Forecasting,” looks at the issue of video delays in remote driving due to uplink constraints. The paper outlines a multi-agent system solution to the problem. One agent predicts upcoming video frames, another detects new objects in the scene, and a third corrects the prediction system using sparse mask guidance. Tested under real-world 5G network traces, the approach significantly improved the system's ability to handle unexpected changes while preserving visual quality and real-time performance. Professor Zhi-Li Zhang of the Department of Computer Science and Engineering advised Zhang.
Xianyu Chen Earns Distinguished Dissertation Award
Xianyu Chen, a recent PhD graduate from Computer Science & Engineering, is the recipient of the University of Minnesota’s Distinguished Dissertation Award for Mathematics, Physical Sciences, and Engineering. The honor recognizes outstanding dissertations that represent original work and make a significant contribution to their field. The award includes a $1,000 prize and a nomination for the 2026 Council of Graduate Students/ProQuest Distinguished Dissertation Award. Chen’s dissertation, “Building Human-like Machine Intelligence: Advancing Attention by Modeling, Alignment, and Explainability,” explores visual attention as a bridge between perception and reasoning in artificial intelligence systems. His research looks at how people move their eyes when answering visual questions, enabling AI systems to learn how humans prioritize task-relevant information. He also created a large-scale dataset of real-world how-to scenarios, such as assembling furniture or cooking a recipe. In the dataset, the images are paired with language and include complex steps, helping the AI system to generate step-by-step visual solutions. Additionally, Chen developed a system that predicts where a person would look and provides short explanations for each instance, linking decisions to evidence. Professor Catherine Zhao of the Department of Computer Science and Engineering advised Chen.
Rajamani Appointed Chair of ASME Honors & Awards Committee
Rajesh Rajamani, Professor in Mechanical Engineering, has been appointed the Chair of the Honors & Awards Committee by the ASME Dynamic Systems and Control Division. The appointment is for the 2026 – 2029 period. This committee makes decisions on major honors awarded by the ASME control systems community, including the Rufus Oldenburger Medal, the Henry Paynter Outstanding Investigator Award, the Charles Stark Draper Innovative Practice Award, and the Michael Rabins Leadership Award.
Aryan Deshwal Selected for the IJCAI-ECAI Early Career Spotlights Program
Aryan Deshwal, Assistant Professor in Computer Science and Engineering, has been selected to the IJCAI-ECAI Early Career Spotlights Program. The IJCAI-ECAI Early Career Spotlights (ECS) is an invited speaker program that recognizes early career researchers who have already made significant research contributions to AI and who show great promise for future impactful contributions. Awardees are assigned a presentation slot at the IJCAI conference in Bremen, Germany, on August 21, 2026, and a talk abstract in the IJCAI-ECAI 2026 proceedings. Deshwal will present a talk on the paper abstract, “Artificial Intelligence (AI) and Machine Learning hold immense potential to accelerate scientific discovery and engineering design.” A fundamental challenge in these domains involves efficiently exploring a large space of designs or hypotheses using expensive experiments in a resource-efficient manner. This paper surveys novel adaptive experimental design methods to address this broad challenge. Specifically, it discusses new probabilistic modeling and decision-making techniques applicable in small-data settings. These approaches have shown substantial improvements in sample efficiency, particularly for black-box optimization over high-dimensional combinatorial spaces (e.g., sequences and graphs) and a variety of goals ranging from multiobjective to multi-fidelity optimization. This paper outlines key methods and their real-world sustainability applications in areas such as nanoporous materials discovery, hardware design, surfactant design, and additive manufacturing.
Samad Presents Keynote Talk at the 2026 Engineering Management Conference
Tariq Samad, from the Technological Leadership Institute, gave a keynote lecture titled "The Technology-Markets-Policy Nexus for Energy Sustainability" at the Engineering Management 2026 conference in Jinan, China, in July, organized by the Chinese Academy of Engineering. His was the only non-Chinese keynote at the conference. Dr. Samad’s talk analyzed the interplay of technology, markets, and policy in advancing energy sustainability, extending the often-referenced “technology-push” – “market-pull” coupling with “policy pump” as an additional forcing function. In some cases, alignment of the nexus elements has driven progress globally, while misalignment has stalled progress in others. In addition to outlining global trends, his presentation adduced examples from several countries, including China, the U.K., Australia, and Pakistan. Implications for technology innovators arising from the analysis of the nexus were also presented.