Twenty postdoctoral research fellows presented their work in exascale computing, computational science, machine learning, quantum computing, data management and analysis, and much more at Berkeley Lab’s Computing Sciences Area 2021 Postdoc Symposium on February 11 and 12.
The symposium is designed to provide area postdocs with communications training, mentorship, and coaching sessions, plus an opportunity to present their research in a public forum. Following a workshop and dry run, participants gave 30-minute presentations, including 10 minutes for questions, about their research to the wider Lab community.
»Watch the Presentations on Youtube.
| 9:00 a.m. |
Venkitesh Ayyar |
[youtube id=”7RqYvZW2aD0″] Mapping the Universe Using Generative Adversarial Neural Networks |
| 9:30 a.m. | Alice Gatti | [youtube id=”q0ajVVWM3Fw”] Deep Reinforcement Learning for Graph Partitioning |
| 10:00 a.m. | Aditi Krishnapriyan |
Learning Continuous Models for Continuous Physics |
| 10:30 a.m. | Doru Thom Popovici | [youtube id=”7KcR_YXzbtc”] Improving Data Locality Across Fourier Transforms and Linear Algebra Operations |
| 11:00 a.m. | Qiao Kang | [youtube id=”uGtRavvqn-o”] Improving All-to-Many Personalized Communication in Two-Phase I/O |
| 1:00 p.m. | Prashant Pandey | [youtube id=”I1hCXFpLlYE”] Metagenomic Reads Classification Using Graph Neural Networks |
| 1:30 p.m. | Daan Camps | [youtube id=”Od3XITnUu9E”] Approximate Quantum Circuit Synthesis Using Block Encodings |
| 2:00 p.m. | Alexis Morvan | [youtube id=”I-eSjpEZ-Nk”] Quantum Imaginary Time Evolution on the Advanced Quantum Testbed |
| 2:30 p.m. | Miro Urbanek | [youtube id=”Jepx3EziIR8″] Mitigating Noise on Quantum Computers |
| 3:00 p.m. | Oluwamayowa Amusat | [youtube id=”npBnuRIHpHI”] Data-Driven Models for Equation-Oriented Optimization |
| 9:00 a.m. |
Zhi (Jackie) Yao |
[youtube id=”fsKfyqMAjGo”] Exascale-Enabled Physical Modeling for Next-Generation Microelectronics |
| 9:30 a.m. | Oisin Creaner | [youtube id=”pASjaucxJDI”] Light Simulations for Dark Matter |
| 10:00 a.m. | Neil Mehta | [youtube id=”yz5RaszoiCM”] Determining the Best Molecular Dynamics Potential for the Job |
| 10:30 a.m. | Jialun (Galen) Wang | [youtube id=”wzBL4l2-v1w”] Modeling Non-equilibrium Phase Transition in Complex Fluids |
| 11:00 a.m. | Oscar Antepara | [youtube id=”AwZ1p1twGOQ”] Accurate Numerical Algorithm for Scientific Applications with Complex Geometries |
| 1:00 p.m. | Ishan Srivastava | [youtube id=”karskW46YjU”] A New Computational Approach for Modeling Nanoscale Electrokinetic Flows |
| 1:30 p.m. | Don Willcox | [youtube id=”tkPiFEy5YcU”] Scalable Computational Modeling of Neutrino Quantum Kinetics in Astrophysics |
| 2:00 p.m. | Anne Felden | [youtube id=”FUN0jL_ucEw”] An AMR Subglacial Hydrology Model – SUHMO |
| 2:30 p.m. | Jordi Wolfson-Pou | [youtube id=”eKk8LJeULzk”] Comparing the PFASST, MGRIT and Parareal Methods |
| 3:00 p.m. | Lisa Claus | [youtube id=”8XDQMRUre7s”] High-Performance Multifrontal Solver with Low-Rank Compression |
About Computing Sciences at Berkeley Lab
High performance computing plays a critical role in scientific discovery. Researchers increasingly rely on advances in computer science, mathematics, computational science, data science, and large-scale computing and networking to increase our understanding of ourselves, our planet, and our universe. Berkeley Lab's Computing Sciences Area researches, develops, and deploys new foundations, tools, and technologies to meet these needs and to advance research across a broad range of scientific disciplines.
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