Ankita Raj

I am a PhD candidate in the Computer Science Department at IIT Delhi. I am working on robust and trustworthy algorithms for Machine Learning, specifically in the context of Computer Vision, advised by Dr. Chetan Arora.

I obtained a Master's degree in Electronics and Communication Engineering from IIIT Delhi in 2016, where I was advised by Dr. Pravesh Biyani. I also held a research position in the Robotics lab, Tata Consultancy Services from 2016 to 2018, where I worked on computer vision for robotics.

Email / CV / Google Scholar / Github / LinkedIn

Research

My research goal is to develop robust computer-vision systems. To this end, I am working on techniques for mounting and preventing various types of attacks on learning-based computer vision systems.

In the past, I have worked on incremental learning and object detection for computer vision, and optimization for resource allocation.

	Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Ankita Raj, Ambar Pal, Chetan Arora International Conference on Image Processing, 2021 IEEE Xplore · pdf Given a face recognition network potentially backdoored with physically realizable triggers like sunglasses or bowtie, we propose a technique to identify such triggers.
	Weighted-A* Based Energy Efficient Resource Allocation in G. Fast Ankita Raj, Pravesh Biyani IEEE Transactions on Communications, 2019 IEEE Xplore · pdf We formulate and solve an optimization problem to minimize power consumption in G.fast broadband access technology.
	HiFI: A Hierarchical Framework for Incremental Learning using Deep Feature Representation Ankita Raj, Anima Majumder, Swagat Kumar IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2019 IEEE Xplore · pdf A hierarchical deep-learning framework for object recognition, with near real-time training for recognizing previously unseen objects.
	A* algorithm based power minimization for discontinuous operations in G. fast Ankita Raj, Pravesh Biyani, Sandip Aine IEEE International Conference on Communications (ICC), 2017 IEEE Xplore · pdf We schedule users to time slots during discontinuous operation mode in G.fast, to achieve high energy efficiency.
	Analysis and Synthesis Prior Greedy Algorithms for Non-linear Sparse Recovery Kavya Gupta, Ankita Raj, Angshul Majumdar Data Compression Conference (DCC), 2016 IEEE Xplore · arxiv · pdf We propose algorithms for recovering sparse solutions to non-linear inverse problems.

Academic Activities

Teaching Assistant (at IIT Delhi): Machine Learning, Digital Image Processing, Computer Vision, Datastructures and Algorithms, Introduction to Computer Science, Advanced Functional Brain Imaging.
Teaching Assistant (at IIIT Delhi): Probability and Statistics, Engineering Optimization, Signals and Systems, Maths I (Linear Algebra), Maths II (Differential Equations).

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