Special Topics Course

This class covers essential components of today’s computing environment, which we all use and take for granted but do often not understand very well. We will look at different types of virtual machines, i.e., process and system VMs, with a particular focus on high-level VMs (e.g., the Java JVM) and dynamic translators and how to make them run efficiently. In addition, we will touch on some other cool system tools, such as linkers or debuggers, and their internals.
 

This course is concurrently offered with "MAT 238: Compfab" in the Media Arts & Technology program

The course will cover techniques to compute on encrypted data, particularly homomorphic encryption, both partial homomorphic encryption, and fully homomorphic encryption. The course will have a large theory component. However, it will also discuss how homomorphic encryption is applied to real systems such as databases, media streaming services, anonymous messaging services, and machine learning systems.

Course information: this course covers the  fundamentals of quantum computation as well as some advanced topics including quantum information theory, algorithms and cryptography. Necessary math prerequisites: linear algebra and probability. Mathematical maturity is a must. 

Have you ever used intelligent virtual assistants such as OpenAI ChatGPT, Google Now, Apple Siri, Amazon Alexa or Microsoft Cortana? What are the technologies behind such systems? How did IBM's Watson beat top human Jeopardy players? Or are you just curious about how Google Translate works? Understanding human language is an important goal for Artificial Intelligence, and this course introduces fundamental theories and practical applications in Natural Language Processing (NLP).

Haptics lies at the intersection of robotics, human-computer interaction, and computational and human perception. The term "haptics" is often used to refer to science and engineering related to the sense of touch. This course introduces human haptics, including sensory specializations and touch perception. It reviews the engineering of electronic technologies for haptic (touch) feedback, emerging technologies, and the design of haptic systems for human-computer interaction, sensory substitution, virtual reality, augmented reality, and other emerging areas.

This is a graduate-level research course on deep learning.  We will discuss/present the newest and important publications in deep learning, specifically Transformer-based techniques in the areas of knowledge base, question answering, conversational AI, natural language processing and multimodal learning.

Deep neural networks have achieved remarkable success owing to their superior predictive performance. Yet, they are extremely vulnerable to adversarial attacks. This makes adversarial machine learning an emerging topic. The idea of learning with adversaries is crucial for expanding the learning capability, ensuring trustworthy decision-making, and enhancing the generalizability of AI models. Despite diverse adversarial concepts and applications, they share very similar learning, computation, and optimization foundations.

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.