BIDMaP is happy to be jointly hosting this year's seminar series with colleagues in computational physical sciences, including collaborators from the departments of Physics and Astronomy, and the Lawrence Berkeley National Laboratory.
How societal computing links data, infrastructure, and stakeholders to drive innovation and real-world impact in the AI era. Her talk highlights AI-enabled scientific workflows and digital twins from the WIFIRE Program for wildfire management and the NSF-funded National Data Platform, which expands access to AI-ready data and computing to foster collaboration, reproducibility, and innovation across scientific domains.
Artificial intelligence has the potential to bring much-needed acceleration to the development of chemicals and materials for energy and sustainability, just as it has delivered intelligence gains in other fields...
Artificial Intelligence and Machine Learning (AI/ML), especially deep learning, are becoming increasingly popular across scientific fields, with many believing they will have transformational impacts. But important questions remain...
Stay tuned for more information about this seminar. Speaker Bio: Amir Barati Farimani received his Ph.D. in 2015 in mechanical science and engineering from the University of Illinois at Urbana-Champaign. His Ph.D. thesis was titled “Detecting and Sensing Biological...
Developing fast and efficient methods for simulating our observable Universe is a key challenge in maximizing information extraction from cosmological datasets...
Stay tuned for more information about this seminar. Speaker Bio: Wahid Bhimji leads NERSC’s Data and AI Services Group. His interests include machine learning and data management. Recently, he has led several projects that apply AI to science, including deep learning at scale, generative models...
Stay tuned for more information about this seminar. Speaker Bio: Berend Smit received an MSc in Chemical Engineering and Physics from the Technical University in Delft, and a Ph.D. in Chemistry from Utrecht University. He was a (senior) Research Physicist at Shell Research from 1988-1997...
Stay tuned for more information about this seminar. Speaker Bio: Anubhav Jain leads a research group studying new materials design using a mix of theory, computing, and artificial intelligence. Jain's group develops, evaluates, and applies models for predicting materials properties to applications such as electrocatalysis...
Stay tuned for more information about this seminar. Speaker Bio: Wen Jie Ong is the senior product manager for NVIDIA ALCHEMI. He is an organic and polymer chemist by training, and received his PhD at MIT where he discovered a new class of dynamic covalent...
We are excited to host the 1st BIDMaP Hackathon with the Fair Universe Higgs Uncertainty Challenge. The challenge uses the example of the rate at which Higgs bosons are produced in the ATLAS detector at the LHC, and poses the question of how to infer...
The efficient construction of hypothetical metal-organic framework (MOF) structures is essential for advancing MOF-related research under the data-driven paradigm. This seminar will introduce a new computational program that is capable of constructing new MOF structures rapidly based on existing MOF structures and organic ligand libraries...
The rapid advancement of artificial intelligence is transforming materials modeling, simulation, and design. This report explores breakthroughs in AI-assisted materials design, emphasizing the transition from multi-scale modeling to multi-scale pre-training. These pre-trained models integrate literature, simulation, and experimental data in a novel manner, paving the...
The recent shale gas boom in the US has made catalytic ethane dehydrogenation (EDH) an economically viable route to produce ethylene, a precursor for the synthesis of several commodity chemicals. Supported atomically dispersed metals and sub-nanometer clusters are an emerging class of catalysts that have...
The intersection of synthetic chemistry, condensed matter physics, electronic devices, and artificial intelligence (AI) holds the potential for paradigm-shifting scientific breakthroughs. Innovations in these interdisciplinary interfaces can lead to the development of novel quantum materials, advanced electronic circuits, and new methodologies for material discovery. In...
Registration is required for this Friday, May 3 seminar in Banatao Auditorium in Sutardja Dai Hall. This presentation will be about how the precision of manipulating molecules has led to several large classes of porous materials capable of carbon capture and water harvesting from desert...
The future of chemistry is self-driving In this talk, I will overview the growing field of self-driving laboratories (SDLs). SDLs are systems that help accelerate the process of scientific discovery or scale-up by employing artificial intelligence and automation for experiment planning and execution. Several SDLs...
Statistical inference is a crucial step in gleaning insights from experimental / observational data to build better physics models to describe our universe. Whether it is to unravel the mysteries of what is happening in the interior of neutron stars, or to uncover the secrets...
The need for new materials to tackle societal challenges in energy and sustainability is widely acknowledged. As demands for performance increase while resource constraints narrow available options, the vastness of composition, structure and process parameter space make the apparently simple questions of where to look...
Composite materials are known for their customizable properties and superior performance characteristics. However, the design of these materials is inherently complex, as it involves navigating through an extensive array of possible material combinations and configurations. In this talk, I will first present novel computational approaches...
Studying low-likelihood high-impact climate events in a warming world requires massive ensembles of hindcasts to capture their statistics. It is currently not feasible to generate these ensembles using traditional weather or climate models, especially at sufficiently high spatial resolution. We describe how to bring the...
Metal-organic frameworks are ultraporous materials that can exhibit selective and cooperative CO2 adsorption chemistry, with potential for future reversible carbon capture applications. While CO2 adsorption enthalpies are relatively well documented, many temperature-dependent and chemical dynamical phenomena related to CO2 and other competing molecular species remain...
The launch of ChatGPT in November 2022 ignited an ongoing worldwide conversation about the possible impacts of Large Language Models (LLMs) on the way we work. There is little doubt that LLMs will significantly influence many people's jobs: one prominent study estimated that about 20%...
The annual BASC Symposium will take place on March 7 and 8, 2024. This year, the theme is “Going with the flow: AI/ML in Atmospheric Science.” The speakers and schedule appear below. The “early-ish bird” registration deadline is this Friday, March 1 st , but...
As scientific data sets become progressively larger algorithms to process this data quickly become more complex. In response Artificial Intelligence (AI) has emerged as a solution to efficiently analyze these massive data sets. Emerging processor technologies such as graphics processing units (GPUs) and field-programmable gate...
