Wei Zhang (张威) is currently a Postdoctoral Researcher in Scientific Data Management Group at Lawrence Berkeley National Laboratory (LBNL), USA. He received his Ph.D. degree from Texas Tech University in 2021. His research interests generally lies in the intersection of high performance computing (HPC) and big data management. Specifically, his research areas include metadata search and querying, graph data management, geospatial data analytics, and storage resource management. Before joining LBNL, he had many years of industrial experiences working for some of the prominent large scale distributed storage systems, including the storage system of Weibo.com (the Chinese version of Twitter) as well as the Big Data Service of Oracle Cloud Infrastructure.

On My Research

My overall research focus is on big data management in high performance computing. Specifically, my research includes: 1) efficient self-contained data discovery with metadata indexing; 2) data partitioning for scalable data-intensive applications in distributed settings; 3) applied geo-spatial data mining; 4) user activeness based storage resource management methodology. These research works have been published in many top-tier conferences and journals (such as SC ’21, SC ’19, PACT ’18, HPDC ’17, and TGRS). Besides the knowledge and insight I gained from these research studies, what I have learned the most is the high-standard research execution, including accurately identifying problems, profoundly analyzing problems, creatively proposing efficient solutions, and thoroughly conducting evaluations, etc.

On Teaching and Mentoring

As for teaching and mentoring experience, I had diverse teaching experience being an invited lecturer, a lab instructor, a teaching assistant for multiple times. I also helped with mentoring a junior Ph.D. student in his research study and I also coached some master students on their course projects and master thesis projects.

On Grant Seeking

I proactively took part in other types of academic activities, including developing funding proposals, teaching and mentoring students, reviewing others’ work, etc. I directly or indirectly contributed to three funding proposals, including 3 NSF funding proposals and one DOE research proposal. One of them successfully gets funded. Particularly, I have been serving as the panelist of the DOE ASCR funding opportunity for two years, in the track of Management and Storage of Scientific Data and the track of Distributed Resilient Systems, respectively. Such experience prepared my mindset and skills towards future success in seeking funding opportunities.

On Other Services

To serve the academic community, I also helped with reviewing conference articles and journal ar- ticles, including TPDS, SC, ICPP, IPDPS, CCGrid, BigData, IEEE Open Access, etc. In 2020, upon invitation, I served as a program committee member of HiPC 2020 conference