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I am a Ph.D. student in Computer Science at Princeton University. I am a member of Princeton Vision and Learning Lab, advised by Prof. Jia Deng. I completed my Masters from University of Michigan and Bachelors from IIT Kanpur. I am fortunate to have interned at some wonderful places and work with some amazing mentors.
Email / CV / Google Scholar / LinkedIn / Twitter |
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I am interested in understanding various aspects of intelligence, especially reasoning and common sense. In particular, I want to develop computation models for various reasoning skills that humans possess. |
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Many point-based approaches have been proposed reporting steady benchmark improvements over time. We study the key ingredients of this progress and uncover two critical results. First, auxiliary factors, independent of the model architecture, make a large difference in performance. Second, a very simple projection based method performs surprisingly well. |
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Understanding spatial relations is important for both humans and robots. We create Rel3D, the first large-scale, human-annotated dataset for grounding spatial relations in 3D. The 3D scenes in Rel3D come in minimally contrastive pairs: two scenes in a pair are almost identical, but a spatial relation holds in one and fails in the other. |
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Simultaneously reasoning about geometry and planning action is crucial for intelligent agents. This ability of geometric planning comes in handy while grocery shopping, rearranging room, warehouse management etc. We create PackIt, a virtual environment that caters to geometric planning. |
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We study geometric reasoning in the context of question-answering. We introduce Dynamic Spatial Memory Network (DSMN), a deep network architecture designed for answering questions that admit latent visual representations. |
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C Gupta, AS Suggala, A Goyal, HV Simhadri, BP, AK, SG, RU, MV, P Jain ICML 2017 [code] Prateek Jain, Chirag Gupta, AS Suggala, Ankit Goyal, HV Simhadri US Patent Applicaiton We propose ProtoNN, a novel algorithm that addresses the problem of real-time and accurate prediction on resource-scarce devices. |
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Ankit Goyal, Naveen Kumar, Tanaya Guha, Shrikanth S. Narayanan ICASSP 2016 We address the problem of continuous emotion prediction in movies. We propose a Mixture of Experts (MoE)-based fusion model that dynamically combines information from the audio and video modalities for predicting the emotion evoked in movies. |
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NK Verma, Ankit Goyal, A Harsha Vardhan, Rahul Kumar Sevakula, Al Salour IES 2016 We propose a robust algorithm which is capable of detecting all the instances of a particular object in a scene image using Speeded Up Robust Features. |
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We propose a methodology for object counting using color histogram based segmentation and spatial filters. |
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I have been a Teaching Assistant for the following courses:
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