Bio

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Dr. Karan Sikka is a Senior Computer Vision Scientist at SRI International in Princeton, USA. He graduated with a PhD degree in 2016 from Machine Perception Lab at UCSD and was advised by (Dr. Marian Bartlett)[https://www.linkedin.com/in/marian-bartlett-92545ba/]. Before joining UCSD, he completed his bachelor’s in ECE at Indian Institute of Technology Guwahati in 2010. His current research is focused on solving some fundamental problems in Computer Vision and Machine Learning such as learning with multiple modalities (incl. vision and language), learning under weak supervision, few/zero-shot learning. He has successfully applied these methods to multiple problem such as facial expression recognition, action recognition, object detection, visual grounding, visual localization. The underlying theme in his research has been to improve the generalization of Computer Vision models by providing useful inductive biases either in the model design (e.g. better features or interactions), data (augmentation with knowledge or multimodality) or the loss function (e.g. weakly supervised learning) and that is also applicable across multiple domains. His work has been published at high-quality venues such as CVPR, ECCV, ICCV, PAMI etc. He has won a best paper honorable mention award at IEEE Face and Gesture 2013, and a best paper award at the Emotion Recognition in the Wild Workshop at ICMI 2013. He serves as a reviewer/program-committee for venues such as ECCV, CVPR, ICCV, ICML, NIPS, AAAI, ACCV, IJCV, IEEE TIP, IEEE TAC, IEEE TM, ICMI, AFGR and also as an AC for ACMM-19,20

At SRI he is a PI/co-PI for several Govt. funded programs related to understanding and analyzing social media content in multiple modalities and user structures.