https://engineering.temple.edu/directory/yichuan-zhu-tup46467
Biography Dr. Yichuan Zhu leads the Computational Geosystems Laboratory in the Civil & Environmental Engineering Department at Temple University. Prior to joining Temple University, he worked as a Post-doctoral fellow at Kentucky Geological Survey where he applied quantitative methods such as machine learning, Bayesian techniques, and spatio-temporal simulations to solve applied Earth science ...
https://guides.temple.edu/az/databases?q=AI%E6%8D%A2%E8%84%B8%E6%98%8E%E6%98%9F%E7%99%BD%E9%B9%BF%28%E7%BD%91%E5%9D%80%3Asff88%C2%B7com%29.gqy
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https://guides.temple.edu/qda/atlas
ATLAS.ti is a commercial qualitative research tool that allows advanced coding, analysis, and visualization for qualitative data.
https://cis.temple.edu/~pwang/5603-AI/5603-Syllabus.htm
Artificial intelligence encompasses the algorithms and representations used to design computers and agents for problem-solving and learning. This course covers the classic and modern methods that support technology such as game-playing agents, autonomous vehicles, and virtual assistants. The topics covered include: search, reasoning, knowledge representation, and learning. The course is ...
https://sites.temple.edu/ticlj/files/2025/07/Sergeev-The-International-Law-of-Artificial-Intelligence-How-to-Regulate-a-Technological-Revolution-Stimulate-the-Global-Economy.pdf
Emerging technologies at the intersection of Artificial Intelligence (AI) and robotics threaten not only the disruption of market economies and workers’ rights, but also international security. As humankind reaps the benefits of the technological revolution, nation-states grapple with disruptive innovation in a variety of ways, choosing to restrict the development, deployment, and use of AI ...
https://cis.temple.edu/~jiewu/research/publications/Publication_files/FedHAN.pdf
FedHAN: A Cache-Based Semi-Asynchronous Federated Learning Framework Defending Against Poisoning Attacks in Heterogeneous Clients Xiaoding Wang1 , Bin Ye1 , Li Xu1 , Lizhao Wu1 , Sun-Yuan Hsieh2 , Jie Wu3;4 and Limei Lin1 1College of Computer and Cyber Security, Fujian Provincial Key Laboratory of Network Security and Cryptology, Fujian Normal University, Fuzhou 350117, China 2Department of ...
https://cis.temple.edu/tagit/events/workshop2025/
Being one of the most sophisticated models of AGI, NARS (Non-Axiomatic Reasoning System) has attracted much interest from researchers, AI professionals, and students worldwide. The goal of the NARS project is to build thinking machines. Endeavors are made to uniformly explain and reproduce many cognitive facilities, including reasoning, learning, planning, etc., to provide a unified theory ...
https://cis.temple.edu/tagit/presentations/A%20Path%20Towards%20Autonomous%20Machine%20Intelligence.pdf
Topic This is a position paper expressing the vision for a path towards intelligent machines that learn more like animals and humans, that can reason and plan, and whose behavior is driven by intrinsic objectives, rather than by hard-wired programs, external supervision, or external rewards.
https://cis.temple.edu/~wu/research/publications/Publication_files/jsan-13-00044-v2.pdf
The term AI on Edge refers to the execution of AI processes right on edge devices, whereas AI for Edge refers to the deployment of AI models and algorithms in the central servers or upper layers to enhance edge computing capabilities. Previous works conducted on the edge–cloud continuum focused on many aspects of the domain.