Explores provably beneficial AI, aligning AI goals with human preferences and behaviors, illustrating complexities through examples like image classification and fetching coffee.
Covers wildfire susceptibility mapping using ML-Al robotics and various related topics, including experimental protocols, DFT feature engineering, SimpedCLIP, and Covid-19 detection.
Covers proteomics techniques and their applications in neuroscience, focusing on mass spectrometry and the challenges of studying proteins in cellular functions.
Explores learning from interconnected data with graphs, covering modern ML research goals, pioneering methods, interdisciplinary applications, and democratization of graph ML.
Covers the basics of proteomics, mass spectrometry, protein synthesis, and amino acids, emphasizing the importance of molecular weight and isotopic abundance.
