I am Shivvrat Arya but feel free to call me Shiv (pronounced as [ sh ih v ]). I am currently engaged in collaborative research projects under the guidance of Dr. Vibhav Gogate and Dr. Yu Xiang, funded by the DARPA Explainable Artificial Intelligence (XAI), DARPA Perceptually-Enabled Task Guidance (PTG) and DARPA Assured Neuro Symbolic Learning and Reasoning (ANSR) grants. Our goal is to develop AI technology that guides users in performing cognitively challenging physical tasks, leveraging breakthroughs in machine perception, automated reasoning, and augmented reality.
Broadly speaking, my research interests primarily focus on artificial intelligence and machine learning, with an emphasis on neuro-symbolic and graph-based methods. I aim to develop AI systems that can reason and understand in ways that are both interpretable and explainable to humans. My work involves integrating formal models of the world—typically provided by domain experts or grounded in scientific theories—with powerful function approximators like neural networks. I have developed novel neural network-based inference methods for probabilistic graphical models and explored advanced inference schemes for multi-label classification. These contributions have been recognized with best paper awards, as well as spotlight and oral presentations.
In video understanding, I developed pipelines for procedural error recognition, explainable models for activity recognition, and predictive task guidance in augmented reality. My research on explainable activity recognition integrates deep learning with dynamic conditional cutset networks, enabling interpretable models that support polynomial-time reasoning queries. Additionally, I co-developed CaptainCook4D, an egocentric 4D dataset designed to benchmark error recognition and multi-step localization in procedural tasks. My work in augmented reality focuses on dynamic, real-time task guidance systems.
During my Bachelor's thesis project at IIT Indore, I focused on developing non-iterative neural network architectures to address multi-label classification challenges across diverse datasets.
I am a Ph.D. candidate in the Department of Computer Science at The University of Texas at Dallas, where I am honing my research skills to address complex problems in Computer Science and contribute to the advancement of innovative technologies. I am always on the lookout for challenging opportunities that push the boundaries of my knowledge and allow me to acquire new skills.
In addition to my Ph.D., I am also pursuing an M.S. degree in Computer Science at UT Dallas, working closely with Dr. Vibhav Gogate and Dr. Yu Xiang. I hold a B.Tech. Degree in Computer Science and Engineering from the Indian Institute of Information Technology Vadodara.