Illinois Computer Science Speaker Series - Public
Illinois Computer Science Speaker Series - Public
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From cs-speakerseries
Abstract: I will recount the story of my career in computing, mostly as an academic at the University of Illinois Urbana-Champaign since 1981. This story will include a… -
From cs-speakerseries
Abstract: Machine learning is revolutionizing technology and society. However, like any technology, it can be misused by adversaries and our understanding of the… -
From cs-speakerseries
Abstract: Using data compression methods in the memory hierarchy can improve the efficiency of memory systems by enabling higher effective cache capacity, more effective… -
From cs-speakerseries
Abstract: In recent years, artificial intelligence (AI) has achieved great success in many fields. Although impressive advances have been made, AI algorithms still… -
From cs-speakerseries
Abstract: Recent hardware advances have brought multicore parallel machines to the mainstream. Although the progress in hardware advance seems promising, it does not… -
From cs-speakerseries
Abstract: Artificial intelligence (AI) has emerged as a powerful tool for solving complex health problems. AI for health is fueled by both the advancement in AI methods… -
From cs-speakerseries
Abstract: Data plays an increasingly crucial role in both the performance and the safety of AI models. In this talk, I will advocate for data attribution--a family of… -
From cs-speakerseries
Abstract: Hardly a day passes without a new technology ethics scandal in the news — from privacy violations on social media to biased algorithms to controversial… -
From cs-speakerseries
Abstract: This talk will focus on two main categories of our recent advancements in parallel algorithms. In the first part, I will introduce our new graph algorithms… -
From cs-speakerseries
Abstract: Verified artificial intelligence (AI) is the goal of designing AI systems that have strong, ideally provable, assurances of correctness with respect to… -
From cs-speakerseries
Abstract: As ubiquitous AI becomes increasingly integrated into the smart devices that users use daily, the rise of extensive datafication, data surveillance, and… -
From cs-speakerseries
Abstract: The emergence of generative LLM processing is revolutionizing NLP. Many researchers have had to completely redefine their goals and work: there is little or no… -
From cs-speakerseries
Abstract: The advent of large language models promises a new level of performance in generation of text of all kinds, enabling generation of text that is far more… -
From cs-speakerseries
Abstract: Graphs have been widely applied to model intricate relationships among entities. The application of Graph Machine Learning (GML) to enhance prediction… -
From cs-speakerseries
Abstract: Deep learning has largely improved the performance of natural language understanding (NLU) systems. However, most deep learning models are black-box… -
From cs-speakerseries
Abstract: Human-centered AI advocates the shift from emulating human to empowering people so that AI can benefit humanity. A useful metaphor is to consider human as a… -
From cs-speakerseries
Abstract: Constant emergence of new computer systems, architectures, and hardware require us to study their security and design protections before adversaries… -
From cs-speakerseries
Abstract: Understanding the genetic basis of complex human disorders is crucial in the realm of medical research, particularly in the context of precision medicine.… -
From cs-speakerseries
Abstract: Quantum position verification (QPV) is a cryptographic task in which the spatial location of an untrusted agent is certified using the principles of quantum… -
From cs-speakerseries
Abstract: Pre-training datasets are a critical component in recent breakthroughs in artificial intelligence. However, their design has not received the same level of… -
From cs-speakerseries
Abstract: Large AI Models demonstrate promising capabilities and open numerous possibilities for innovative applications. What are future AI applications like and how… -
From cs-speakerseries
Abstract: At least since the initial public proposal of public-key cryptography based on computational hardness conjectures (Diffie and Hellman, 1976), cryptographers… -
From cs-speakerseries
Abstract: The evergreen popularity of computer science as a degree, and accompanying student enrollments, necessitate effective instruction at scale that meets the dual… -
From cs-speakerseries
Abstract: Content creators compete for exposure on recommendation platforms, and such strategic behavior leads to a dynamic shift over the content distribution.… -
From cs-speakerseries
Abstract: "Do we have to learn proofs?" – a question that Discrete Math instructors receive time and time again from students. In this talk, I will… -
From cs-speakerseries
Abstract: Recent advancements in large language models (LLMs) have marked a significant milestone in the field of natural language processing. Yet, as we venture into… -
From cs-speakerseries
Abstract: For the past three years, instructors have been challenged to find creative and efficient alternatives for teaching in remote and hybrid formats, creating an… -
From cs-speakerseries
Abstract: Distribution matching (DM) has emerged as a cornerstone of trustworthy machine learning, finding application in fairness, robustness, causality, and… -
From cs-speakerseries
Abstract: As the field of computer science (CS) is gaining increased attention in K-8 schools, the need for qualified teachers is rapidly growing. Yet little is still… -
From cs-speakerseries
Abstract: Developing a theoretical model (architecture) for the way the brain “computes” is a decades long research effort that still has a very long way to…
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