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Hi! I am Lakshita, a first year PhD student at Brown University, advised by Prof. Stefanie Tellex . I'm interested in Robot Learning, Human-Robot Interaction and Natural Language Processing. I also completed my Master's in Computer Science at Georgia Tech with a specialisation in Computational Perception and Robotics and worked in the CORE Robotics Lab on Human-Robot Interaction advised by Prof. Matthew Gombolay. Previously, I was working as Software Development Engineer at Amazon, India in the Prime Verification Team. I did my undergrad studies from NIT Kurukshetra, India where I worked with Dr Mayank Dave on Digital Image Watermarking and Wireless Networks Email / CV (updated Feb'24) / Linkedin / Google Scholar / Github / Twitter |
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Towards the design of user-centric strategy recommendation systems for collaborative Human–AI tasks
In International Journal of Human Computer-Studies Artificial Intelligence is being employed by humans to collaboratively solve complicated tasks for search and rescue, manufacturing, etc. Efficient teamwork can be achieved by understanding user preferences and recommending different strategies for solving the particular task to humans. In this paper, we seek to understand the important factors to consider while designing user-centric strategy recommendation systems for decision-making. We conducted a human-subjects experiment (n=60) for measuring the preferences of users with different personality types towards different strategy recommendation systems. Paper Link |
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A Computational Interface to Translate Strategic Intent from Unstructured Language in a Low-Data Setting
In EMNLP 2023 Many real-world tasks involve a mixed-initiative setup, wherein humans and AI systems collaboratively perform a task. While significant work has been conducted towards enabling humans to specify, through language, exactly how an agent should complete a task (i.e., low-level specification), prior work lacks on interpreting the high-level strategic intent of the human commanders. In this paper, we build a computational interface capable of translating unstructured language strategies into actionable intent in the form of goals and constraints. Paper Link |
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Hybrid color image watermarking algorithm based on DSWT-DCT-SVD and Arnold transform
In Advances in Signal Processing and Communication: Select Proceedings of ICSC 2018 With emergence of new technologies it is now easier to communicate through multimedia like image, audio, video and text. But at the same time the problem of unauthorized access and copyright protection has also emerged. In order to handle these problems digital image watermarking is one of the best technique. In this paper we present an optimized color image watermarking technique to protect an image data from any unauthorized access. The technique presented in the paper uses a combination of Discrete Stationary Wavelet Transform (DSWT), Singular Value Decomposition (SVD), Discrete Cosine Transform (DCT) and Arnold Transform. Paper Link |