About me

Greetings, I’m Sid. I’m currently a PhD student with the computer science department at Boston University. I currently work under the advisement of Kate Saenko, as a part of her research group, which is a part of the Image and Video Computing (IVC) group at BU.

Before starting my PhD at BU in the Fall of 2017, I worked for a year as a research assistant under Kostas Daniilidis at the University of Pennsylvania (Penn), as a part the GRASP Lab, where I had also completed my MSE in Robotics in 2016. Prior to joining Penn, I obtained a MEng in Mechatronic Engineering from the University of Nottingham, in 2014.

Current Research

My current research looks into exploiting the graphics and physics capabilities of game engines for improved visual realism in simulated environments. We want to be able to learn to more closely visually model the real-world in simulation. This would tentatively allow for the construction of better sandbox environments such that knowledge gained by agents trained within the environment would better transfer to real-world applications.

Broader Research Interests

My primary interests lie in the fields of computer vision and artificial intelligence, specifically when applied to machine perception.

My passion for computer vision derives from a fascination with the intersection between humans and machines. I have long been interested by Robotics and Biomechatronics, and I realized that a focus on computer vision would afford me the freedom to specialize in either of my major interests, while offering potential to branch out further, were my interests to evolve.

I am mainly interested in improving the utility of vision in more natural environments. I seek to grant machines a better sense for geometric and spatiotemporal characteristics of and relationships between objects, using context to build on learned or determined priors to better understand the relevance and larger meaning of visual information in the scene in which it is presented. Where feasible, I would also like to work on intelligently integrating extra-sensory information to aid environment-modeling and understanding. I am particularly interested in the potential impact such studies could present when applied to robotics and augmented reality.


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