Featured Speakers: Michael Wehner, Sherri Li, Wenji Wu
Date: July 22, 2025
Time: 11 a.m. – 12 p.m.
Where: 59-3101. Virtual: Zoom Available
Three Short Talks:
Talk Title TBD
Presented by Michael Wehner (Senior Scientist)
Abstract TBD.
Interplay of Linear Algebra, Machine Learning, and High Performance
Computing
Presented by Sherry Li (Group Lead, Scalable Solvers Group, AMCR)
In recent years, we have seen a large body of research using hierarchical matrix algebra to construct low complexity linear solvers and preconditioners. Not only can these fast solvers significantly accelerate the speed of large scale PDE based simulations, but also they can speed up many AI and machine learning algorithms which are often matrix-computation-bound. On the other hand, statistical and machine learning methods can be used to help select best solvers or solvers’ configurations for specific problems and computer platforms. In all these fields, high performance computing is an indispensable cross-cutting tool for achieving real-time solutions for big data problems. In this talk, we will show our recent developments in the intersection of these areas
An Introduction to Quantum Networks
Presented by Wenji Wu (Scientific Networking, ESnet)
Quantum networks are envisioned to achieve novel capabilities that are provably impossible using classical networks and could be transformative to science, economy, and national security. These novel capabilities range from cryptography, sensing and metrology, distributed systems, to secure quantum computing in the Cloud. To realize these great potentials, quantum networks are currently being actively researched and developed worldwide across different physical platforms, from solid-state systems such as superconducting circuits and nitrogen vacancy (NV) centers in diamond, to neutral atoms, to trapped ions. In this talk, I will first give an introduction to quantum networks, highlighting the quantum network logic entities, key mechanisms, and its relationships with classical networks etc. I will then discuss two major quantum network research projects that are currently being conducted in Lawrence Berkeley National Laboratory, the DOE-funded quant-net project and the LDRD-funded QNPack project.
Read more about our presenters below.
There are 2 tours of 25 spaces each on July 23.
Please sign up for one or the other below:
ALS TOUR #1
Date: July 23, 2025
Time: 2 p.m. – 3 p.m.
Where: In person at the Advanced Light Source or ALS (Bldg 66)
RSVP in advance is required for this event. Only 25 spaces available per tour.
ALS TOUR #2
Date: July 23, 2025
Time: 3:30 p.m. – 4:30 p.m.
Where: In person at the Advanced Light Source or ALS (Bldg 66)
RSVP in advance is required for this event. Only 25 spaces available per tour.
Dr. Wehner's current research concerns the behavior of extreme weather events. He has appeared on CNN and has spoken to the U.S. Congress. Dr. Wehner earned his master’s degree and Ph.D. in nuclear engineering from the University of Wisconsin-Madison, and his bachelor’s degree in Physics from the University of Delaware. He received the 2022 LBNL Director's Award for Exceptional Scientific Achievement and was named a Clarivate Highly Cited Researcher in 2020, 2021, 2022 and 2023.
Sherry Li is a Senior Scientist in the Applied Math and Computational Research Division, Lawrence Berkeley National Laboratory. She has worked on diverse problems in high performance scientific computing and machine learning, including parallel algorithms, sparse matrix computations, multi-precision arithmetic, and Bayesian optimization. She is the lead developer of SuperLU, a widely-used sparse direct solver, and has contributed to the development of several other mathematical libraries, including ARPREC, LAPACK, PDSLin, STRUMPACK, and XBLAS. She earned Ph.D. in Computer Science from UC Berkeley. She is a Fellow of SIAM and a Senior Member of ACM.
An expert in both quantum and classical networks, Dr. Wenji Wu is a network research engineer in Lawrence Berkeley National Laboratory's Scientific Networking Division, where he works on quantum networks, high-speed networking, and distributed systems for QUANT-NET and for ESnet's Testbeds & Prototypes group.
