The workshop will examine current opportunities and challenges for the signal and image sciences community. The forum is intended to enable a productive exchange of ideas on state-of-the-art technologies and recent developments. With the goal of sparking interesting discussions, we encourage submission of intermediate results from ongoing projects or recent conference papers. To enhance technical exchange between participants, we are also encouraging posters for this Workshop. The event is open to all engineers, scientists, and students with an interest in the signal and image sciences who are employed at LLNL only this year.
The workshop will be held in-person at the Livermore Valley Open Campus (LVOC), B463 R1400, and requires pre-registration. Coffee and snacks will be provide for morning/afternoon breaks.
We are monitoring the current development and guidelines provided by LLNL to make sure we are following best practices with respect to COVID. Please see current guidelines on the [Return to New Normal] website.
This yearβs workshop will feature the following tracks, moderated by the Program Chairs:
Abstract deadline: Friday, August 12th | Speaker confirmation: Friday, August 19th
Proposal submission: Use the Registration button above to submit your abstract. For general questions about the CASIS Workshop, contact Ruben Glatt. For questions about the program, please reach out to the Program Chair of the track you want to present in.
Computational Engineering Division
This talk will present a retrospective look at data science and machine learning efforts at LLNL and then provide an outlook on future challenges and engagements.
Dr. Chen is a Machine Learning researcher with over 20 years of experience in developing and applying novel machine learning algorithms to a wide variety of applications including automatic speech recognition, image classification, and threat analysis and detection. He has deep expertise in Neural Networks, Random Forests, Graphical Models, Hidden Markov Models, and Support Vector Machines. Dr. Chen currently leads several research teams at LLNL focused on the development of new neural network and graphical model learning algorithms that address recurring challenges in security and scientific applications including: the scarcity of labeled data, the multimodality of data types, and the scalability of training and testing large models on massive datasets.
SESSION 1: 8:00β9:30am
SESSION 2: 10:00amβ12:00pm
SESSION 3: 1:00β2:40pm
SESSION 4: 3:30β5:00pm