Applied persistent homology, a toolset to analyse high-dimensional data using topological data analysis, to motor control, which includes stride-to-stride fluctuations and gait dynamics, and neurodegenerative diseases.
In this project, we built an ultra-low power backscatter device for monitoring Atlanta’s urban heat islands, using digital communications techniques to extend the range between the tag and transmitter/receiver by sacrificing throughput. We explore digital range-increasing techniques such as forward error correction (FEC) and investigate low-power digitization and signal generation. We build a system consisting of a co-located transmitter and receiver capable of reading temperature data from a single backscatter tag.
mmWave radar data is rich in information related to humans like pose and movement. We also observe that collection of data is easy, however labelling the data is extremely hard. In this project, we have built an unsupervised framework to extract spatial and temporal features of the data which are critical to downstream supervised tasks like pose estimation, tracking and identifying individuals. Using the latent space features, we are able to build more effective supervised learning frameworks that require 50 times fewer training samples than prior work.
Published in EAI VALUETOOLS, 2023
This paper is about Better-Late-Than-Never (BLTN), an online algorithm which decides the state of an edge computing server based on historic request arrival rates. In this work, we propose a deterministic online policy and characterize its performance for adversarial and stochastic request arrival processes. We also characterize a fundamental bound on the performance of an arbitrary deterministic online policy. Further, we compare the performance of our policy with suitably modified versions of existing policies to conclude that our policy is robust to temporal changes in the intensity of request arrivals.
Recommended citation: Madnaik, A., Moharir, S., Karamchandani, N. (2023). Renting Edge Computing Resources for Service Hosting. In: Hyytiä, E., Kavitha, V. (eds) Performance Evaluation Methodologies and Tools. VALUETOOLS 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 482. Springer, Cham. https://doi.org/10.1007/978-3-031-31234-2_17 https://link.springer.com/chapter/10.1007/978-3-031-31234-2_17
Published in IEEE Infocom, 2024
(to appear) This paper is about NeTo-X, a scalable network tomography framework which estimates joint client access statistics with just linear overhead, and forms a blue-print of the interference, thus enabling efficient DSA for future networks. NeTo-X’s design incorporates intelligent algorithms that leverage multi-channel diversity and the spatial locality of interference impact on clients to accurately estimate the desired interference statistics from just pair-wise measurements of its clients. The merits of its framework are showcased in the context of resource management and jammer localization applications, where its performance significantly outperforms baseline approaches and closely approximates optimal performance at a scalable overhead.
Recommended citation: A. Madnaik, N. C. Matson and K. Sundaresan, "Scalable Network Tomography for Dynamic Spectrum Access," IEEE INFOCOM 2024 - IEEE Conference on Computer Communications, Vancouver, Canada, 2024 https://arxiv.org/abs/2403.03376
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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