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Symposium to Showcase Postdoctoral Fellows' Research

Berkeley Lab Community Encouraged to Attend, January 30-31

January 14, 2020

Twenty-two postdoctoral fellows in the Computing Sciences Area have been chosen to present their research during a two-day symposium that is the culmination of a targeted communications training program designed specifically for postdocs. The symposium, open to the Berkeley Lab community, takes place January 30-31 in Wang Hall (Building 59), room 3101. It will showcase ongoing research projects in exascale computing; machine learning; data management and analysis for experimental science; modeling and simulation of complex scientific problems; computer networking; and quantum computing. (Remote attendance is available.)

“Developing excellent communications and presentation skills is one of the most important things that a young scientist can do,” said David Brown, director of the Computational Research Division at Berkeley Lab. ”We created this educational program to provide our postdocs with communications training, mentorship, and coaching sessions along with an opportunity to present their research in a public forum.”

CS Area Postdoc Symposium Poster

Select image to enlarge.


Speaker Schedule

Thursday, January 30, 2020


9:00 a.m., Hugo Brunie – Mixed Precision Tuning on HPC Applications

9:30 a.m., Michael Rowan – Use of CUDA Profiling Tools Interface (CUPTI) for Profiling Asynchronous GPU Activity

10:00 a.m., Muaaz Awan – GPU-BSW: A GPU Based Sequence Alignment Algorithm for Accelerating Bioinformatics Applications

10:30 a.m., Nan Ding – An Instruction Roofline Model for GPUs

11:00 a.m., Wenjing Wang –Bilevel Optimization and Data Analysis for Efficient Tuning of High

11:30 a.m., Jangho Park – Input Structure Selection for Time-Series Prediction with Machine Learning

1:00 p.m., Reetik Sahu – Predicting Daily Groundwater Levels with Deep Learning Models

1:30 p.m. Venkitesh Ayyar – Building Compact Convolutional Neural Networks for Signal-Background Classification in Particle Physics Experiments

2:00 p.m., Yu-Hang Tang – GraphDot: A GPU-Accelerated Python Package for High-Throughput Graph Kernel Computation

2:30 p.m., Daniel Murnane – Graph Neural Networks for Particle Tracking

3:00 p.m., Bashir Mohammed – DeepRoute: A Deep Reinforcement Learning approach for Dynamic Network Routing Optimization and SDN on Chameleon Testbed

Friday, January 31, 2020


9:00 a.m., Mike MacNeil – Distributed Digital Volume Correlation by Optimal Transport

9:30 a.m., Zhe Bai – Computed Tomography (CT) Image Registration and Segmentation for Traumatic Brain Injury (TBI) Analysis

10:00 a.m., Jie Luo – An Alternative Architecture for Computing with Exponential Acceleration

10:30 a.m., Adam Peterson – Numerical Construction of Vortices in a Strongly Coupled Superconductor

11:00 a.m., David Williams-Young – Parallel Shift-Invert Spectrum Slicing for Symmetric Self-Consistent Eigenvalue Computation

11:00 a.m., Don Willcox – Towards Exascale Supernovae Simulations

1:00 p.m., Doreen Fan – Modeling Type Ia Supernovae: The Key to Understanding the Cosmic Universe

1:30 p.m., Katie Klymko – A Low Mach Number Fluctuating Hydrodynamics Model for Room Temperature Ionic Liquids

2:00 p.m., Revathi Jambunathan – 2:00 pm Towards Exascale Modeling of Pulsar Magnetospheres Using WarpX

2:30 p.m., Roberto Porcu – A Hybrid PIC-DEM Approach for Multi-Phase Computational Fluid Dynamics

3:00 p.m., Vincenzo Gulizzi – High-order Numerical Schemes for the Exascale