This course offers students an introduction to some of the latest state-of-the-art techniques in the field of deep learning. Throughout the course, students will delve into a wide range of advanced topics and methodologies, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative models such as large language models, and transformers, among others.
This course sets the foundational knowledge necessary to understand quantum computing and quantum information science by covering some of the advanced linear algebra tools, and basic quantum mechanics. Students will learn about the four critical postulates of quantum mechanics, explore quantum circuits, and delve into the universal gate set. The curriculum includes studies on quantum teleportation, superdense coding, and the no-cloning theorem, alongside a comprehensive introduction to key quantum algorithms like Shor's Algorithm, Grover's Algorithm, and the Adiabatic Algorithm.
In recent years, we have witnessed the widespread usage of ML tools for various classification, detection, and control problems. More recently, we have witnessed the use of ML for various networking problems as well. However, operationalizing ML solutions for networked systems is more nuanced than simply calibrating existing tools, developed for other domains (image classification, NLP, etc.). More in-depth exploration to develop flexible, scalable, and generalizable ML-based networked systems.
One of the perennial goals of Computer Graphics is creating high quality images which are indistinguishable from photographs: a goal referred to as photorealism. Another important goal is interactivity for visualization, simulation, gaming and other real-time applications. These two goals have historically been at odds with each other.
This course is a graduate-level introduction to automated reasoning techniques and their application in tools for the design, analysis, and construction of software. In the first half of the course, we will survey the logical foundations and algorithms behind SAT solvers and SMT solvers. In the second half of the course, we will apply these techniques to automatic bug finding, program verification, and program synthesis. As a student in this course, you will learn how solvers work, and how to use them to build cool programming tools.
The course covers all aspects of blockchains and cryptocurrencies with a slight focus on security, including distributed consensus, smart contracts, economics, scalability, and applications. We will focus on the Ethereum ecosystem as the case study.
We will cover cutting-edge research topics in quantum information and modern quantum cryptography, including unclonable cryptography, notions of quantum pseudorandomness, post-quantum cryptography, and protocols. Background in quantum information and cryptography will be assumed.
The course is about cutting edge techniques in machine learning and cybersecurity. We will introduce various deep learning methods that are widely used in security applications, including multilayer perceptron, recurrent neural networks, and transformers. We will also discuss the trustworthiness issue of these methods, including explainability and adversarial robustness.
After over 30 years of research and engineering in controllable quantum devices, we are at the cusp of discovering the first real-world applications for quantum computing systems. A critical element that connects high-level applications to low-level quantum system designs is quantum control and metrology.
Real world tasks such as assembly, repair, or surgery, often require the simultaneous use of both hands. In these scenarios, one hand is used to grasp a tool like a screwdriver or a scalpel, while the other hand is engaged in manipulating the object being worked on. Creating one-handed interfaces for users engaged in physical tasks that involve tools or objects presents several challenges. Learning how do to these tasks with an AI-based task assistant in AR/VR requires the ability to not only perform the task but engage with the AR/VR interface simultaneously.