Computer Science and Automation (CSA)
Recent Submissions
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Advancing the Communication Complexity Landscape of Perfectly Secure Multiparty Computation
Secure multiparty computation (MPC) allows n distrustful parties to jointly compute a function on their inputs while keeping their inputs private. The distrust is modelled as an adversary that controls up to t parties and ... -
Zero-Knowledge Proofs with Enhanced Deniability
In cryptography, deniability is a crucial concept that allows a participant to plausibly deny taking part in executing a scheme or protocol. Non-interactive zero-knowledge (NIZK) proofs enable a party (the prover) to ... -
Ankora: Notions of Multi-party Computation and Zero-knowledge Beyond Conventional Models
In the era of digitalization, data privacy and integrity are of utmost importance. Secure multiparty computation (MPC) and zero-knowledge (ZK) facilitate data privacy and integrity. MPC enables privacy-preserving collaborative ... -
Single and Multi-Agent Finite Horizon Reinforcement Learning Algorithms for Smart Grids
In this thesis, we study sequential decision-making under uncertainty in the context of smart grids using reinforcement learning. The underlying mathematical model for reinforcement learning algorithms are Markov Decision ... -
Analysis, Design, and Acceleration of DNN Training Preprocessing Pipelines
The performance of deep neural network (DNN) training is a function of both the training compute latency and the latency to fetch and preprocess the input data needed to train the model. With advance- ments in GPUs and ... -
Mean Field Based Investigations for Inducing Socially Optimal Epidemic Behavior in Rational Individuals
In the recent years, the world has been devastated by multiple pandemics arising out of different variants of the Corona virus. When an epidemic or pandemic strikes, it is important to move quickly to contain and suppress ... -
Barrier Function Inspired Reward Shaping in Reinforcement Learning
Reinforcement Learning (RL) has progressed from simple control tasks to complex real-world challenges with large state spaces. During initial iterations of training in most Reinforcement Learning (RL) algorithms, agents ... -
Exploring Fairness and Causality in Online Decision-Making
Online decision-making under uncertainty is a fundamental aspect of numerous real-world problems across various domains, including online resource allocation, crowd-sourcing, and online advertising. Multi-Armed Bandits ... -
Rational Secure Computation: New Definitions and Constructions
Cryptography and Game Theory are two fascinating areas of modern computing, and there have been numerous works since the early 2000s to bridge these. While cryptography provides mechanisms to detect deviations, game theory ... -
Bandit Algorithms: Fairness, Welfare, and Applications in Causal Inference
We study regret in online learning from a welfarist perspective and explore an application of bandit algorithms in causal inference. We introduce Nash regret, which measures the difference between the optimal action ... -
Topological Structures and Operators for Bivariate Data Visualization
Understanding complex phenomena in diverse scientific and engineering disciplines often relies on decoding the interplay among real-valued or scalar fields that are measured or computed over a spatial domain. This thesis ... -
An Explainable Hierarchical Class Attention Model for Legal Appeal Automation
Judicial systems worldwide are overburdened due to the limited number of legal professionals. The digitization of legal processes has resulted in abundant legal data, paving the way for the development of legal automation ... -
Decentralized information flow control for the robot operating system
The Robot Operating System (ROS) is a popular open-source middleware widely used in the robotics community. While ROS provides extensive support for robotic application develop- ment, it lacks certain fundamental security ... -
Algorithmic Problems on Vertex Deletion and Graph Coloring
In the thesis, we mainly discuss variants of two well-studied graph theoretical problems - vertex deletion problem and graph coloring problem - both have been used to tackle many real-world problems in diverse fields. Vertex ... -
Exploring Welfare Maximization and Fairness in Participatory Budgeting
Participatory budgeting (PB) is a voting paradigm for distributing a divisible resource, usually called a budget, among a set of projects by aggregating the preferences of individuals over these projects. It is implemented ... -
Specification Synthesis with Constrained Horn Clauses
Many practical problems in software development, verification and testing rely on specifications. The problem of specification synthesis is to automatically find relational constraints for undefined functions, called ... -
Maximum Independent Set of Rectangles - An Empirical Study
We study the Maximum Independent Set of Rectangles (MISR) problem. The problem involves a collection of n axis-parallel rectangles in 2D with weights. For the unweighted case, the goal is to find the maximum number of ... -
Temporal Point Processes for Forecasting Events in Higher-Order Networks
Real-world systems consisting of interacting entities can be effectively represented as time-evolving networks or graphs, where the entities are depicted as nodes, and the interactions between them are represented as ... -
Secure Computation Protocol Suite for Privacy-Conscious Applications
As an alternative to performing analytics in the clear, there is an increasing demand for developing privacy-preserving solutions that aim to protect sensitive data while still allowing for its efficient analysis. Among ... -
Novel Algorithms for Improving Agricultural Planning and Operations using Artificial Intelligence and Game Theory
This dissertation work is motivated by the critical need to address a perennial global problem, namely, how to mitigate the distress of the small and marginal agricultural farmers in emerging economies. Key reasons behind ...
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