Kumar Ayush is a second year Master's student in Computer Science at Stanford University, specializing in Artificial Intelligence. Kumar’s primary research interests lie in the intersection of machine perception, learning, and reasoning, mainly from the perspective of vision. These interests have drawn him towards the following research directions: data augmentation, representation learning, and generative modeling. Kumar also enjoys eclectic applications of machine learning to areas like remote sensing, medical imaging, video-based real-world applications e.g. human activity and behavior understanding in healthcare settings.
HOW DID YOU CHOOSE WHAT YOU STUDIED IN COLLEGE? HOW DID YOU END UP STUDYING AI?
“Incorporating Artificial Intelligence into an Augmented Reality application allows it to interact with the physical environment on a multi-dimensional level. We are moving into a time when people are exploring novel approaches to storytelling with AR, and employing things like haptic technology and augmented sound to alter the environmental ambiance. I am fascinated by the recent progress in this domain which has blurred the line between the digital and real worlds. It was during my internship at Adobe when I first became captivated by the idea of using AI in Augmented Reality. Over the course of the internship, I worked on developing intelligent solutions over AR-based retail apps, and as a result, was exposed to state-of-the-art methods in machine learning and computer vision. This experience instilled the desire to pursue further research in this area and continue specializing in Artificial Intelligence. My interest in Computer Science arose from my father, who as a civil engineer, instilled in me the benefits of advanced software applications like AutoCAD, STAAD Pro, etc., in aiding him with his work. Hence, I grew up privy to the notion of how advances in computing solutions and software were going to change the world, and thus deciding to major in Computer Science during my undergraduate studies was quite a natural decision for me. Over the course of the program, I was exposed to a vast range of diverse domains, of which I particularly enjoyed the courses I took in machine learning, image processing, computer vision, probability, and statistics. My curiosity towards learning as much as possible about these domains helped me score near the top of my class.”
WHAT RESEARCH/INDUSTRY WORK WITHIN AI HAVE YOU BEEN FOCUSED ON? WHAT EXCITES YOU ABOUT THE FUTURE OF AI?
“My primary research interests now lie in the intersection of machine perception, learning, and reasoning, mainly from the perspective of vision. These interests have drawn me towards the following research directions: data augmentation, representation learning, and generative modeling. I am particularly excited about the role AI will play in the healthcare domain. I am pretty sure that AI will not replace doctors but will be able to effectively assist them with diagnosis, treatment, and prognosis.”
WHAT HAS BEEN THE HIGHLIGHT OF YOUR TEACHING EXPERIENCE IN INSPIRIT AI?
“This was one of a kind experience. The instructor-student ratio was very good. It allowed me to cater to each student. I was also pleasantly surprised by the demo ideas that students came up with for the presentation and worked it out smoothly. I saw a great level of collaboration amongst them and were always ready to help each other out.”
WHAT ADVICE WOULD YOU GIVE TO YOUNG PEOPLE WHO ARE INTERESTED IN STUDYING AI OR PURSUING A CAREER IN AI IN THE FUTURE?
“A career in AI can be led in two ways. First is the AI practitioner, where you study existing AI algorithms and apply them to your problems. So this is more of applied work. Second is AI researcher, where you actually do fundamental research to extend the boundaries and capabilities of AI. I would strongly suggest to students to dip their toes in both roles and figure out what works best for them in the long run.”
