Division of Electrical, Electronics, and Computer Science (EECS): Recent submissions
Now showing items 201-220 of 1278
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OTFS Transceivers Design using Deep Neural Networks
Next generation wireless systems are envisioned to provide a variety of services with a wide range of performance requirements. Particularly, demand for high-mobility use cases involving high-speed trains, UAVs/drones, and ... -
Tailoring optical and electrical characteristics of layered materials through van der Waals heterojunctions
The feasibility of isolation of layered materials and arbitrary stacking of different materials provide plenty of opportunities to realize van der Waals heterostructures (vdWhs) with desired characteristics. In this thesis, ... -
Low Power Machine Learning Systems for Energy Efficient Edge Devices
Energy-efficient devices are essential in the world of edge computing and the tiny Machine Learning (tinyML) paradigm. Edge devices are often constrained by the available compu- tational power and hardware resource. To ... -
Large Time Behaviour and Metastability in Mean-Field Interacting Particle Systems
This thesis studies the large time behaviour and metastability in weakly interacting Markov processes with jumps. Our motivation is to quantify the large time behaviour of various networked systems that arise in practice. The ... -
Modeling and verification of database-accessing applications
Databases are central to the functioning of most IT-enabled processes and services. In many domains, databases are accessed and updated via applications written in general-purpose lan- guages, as such applications need ... -
Analysis and Methods for Knowledge Graph Embeddings
Knowledge Graphs (KGs) are multi-relational graphs where nodes represent entities, and typed edges represent relationships among entities. These graphs store real-world facts such as (Lionel Messi, plays-for-team, Barcelona) ... -
Techniques for estimating the direction of pointing gestures using depth images in the presence of orientation and distance variations from the depth sensor
A significant part of our daily life is spent interacting with various computing devices, mobile phones, etc. Soon, robots and drones may become common in daily life, as might be virtual reality based interfaces. Currently, ... -
High Performance GPU Tensor Core Code Generation for Matmul using MLIR
State of the art in high-performance deep learning is primarily driven by highly tuned libraries. These libraries are often hand-optimized and tuned by expert programmers using low-level abstractions with significant effort. ... -
Hybrid Electromagnetic Solvers for EMIEMC
With advances in technology and increased design complexity in the automotive industry, Electromagnetic Interference (EMI) and Electromagnetic Compatibility (EMC) issues are becoming increasingly important. An accurate ... -
Robust Non-convex Penalties for Solving Sparse Linear Inverse Problems and Applications to Computational Imaging
Sparse linear inverse problems require the solution to the l-0-regularized least-squares cost, which is not computationally tractable. Approximate and computationally tractable solutions are obtained by employing ... -
Imitation Learning Techniques for Robot Manipulation
Robots that can operate in unstructured environments and collaborate with humans play a major role in raising productivity and living standards as societies age. Unlike the robots currently used in industrial settings for ... -
Plasma catalysis of diesel exhaust using industrial wastes: a study on NOX and THC removal
Air pollution, caused by large scale consumption of fossil fuels such as diesel, has been the leading cause of several adverse environmental effects such as global warming, higher acidity in rainwater, lower yield ... -
Hypothesis Testing under Communication Constraints - Theory and an Application in IoT
Applications in the Internet of Things (IoT) often demand enabling low-compute devices to perform distributed inference and testing by communicating over a low bandwidth link. This gives rise to a plethora of new problems ... -
Security of Post-Quantum Multivariate Blind Signature Scheme: Revisited and Improved
Current cryptosystems face an imminent threat from quantum algorithms like Shor's and Grover's, leading us to post-quantum cryptography. Multivariate signatures are prominent in post-quantum cryptography due to their fast, ... -
Analysis and Enhancement of Stability of Power Systems with Utility-scale Photovoltaic Power Plants
Owing to the negative impact of carbon emissions on environment, power systems are experiencing a paradigm shift in power generation. The fossil fuel-based generators that utilize synchronous machines are increasingly being ... -
Deep Learning over Hypergraphs
Graphs have been extensively used for modelling real-world network datasets, however, they are restricted to pairwise relationships, i.e., each edge connects exactly two vertices. Hypergraphs relax the notion of edges ... -
Classifying Magnetic and Non-magnetic Two-dimensional Materials by Machine Learning
There has been a giant leap in technological advancement with the introduction of graphene and its remarkable properties after 2005. Since the inception of graphene, the new class of materials called 2D materials are ... -
Probabilistic source-filter model of speech
The human respiratory system plays a crucial role in breathing and swallow ing. However, it also plays an essential role in speech production, which is unique to humans. Speech production involves expelling air from the ... -
Novel Regularized Image Reconstruction Algorithms for Sparse Photoacoustic Tomography
Among all tissue imaging modalities, photo-acoustic tomography (PAT), has been getting increasing attention in the recent past due to the fact that it has high contrast, high penetrability, and has capability of retrieving ... -
MPCLeague: Robust MPC Platform for Privacy-Preserving Machine Learning
In the modern era of computing, machine learning tools have demonstrated their potential in vital sectors, such as healthcare and finance, to derive proper inferences. The sensitive and confidential nature of the data in ...