Branching Out

With the anticipation of Data Science activities in full swing at UC Davis, in Fall 2020, our campus decided to renovate the first floor and basement of the former Physical Sciences and Engineering Library (PSEL) for the use of campus-wide Data Science and Artificial Intelligence (AI) related activities. The renovation was finally completed in December 2023. Together with QMAP (Center for Quantum Mathematics and Physics), which has occupied the 2nd and 3rd floors since 2021, this renovated building has become a gathering space for research activities in physical and data sciences, and hence it has now been officially renamed as the Physical and Data Sciences Building (PDSB).  

Between the two floors there are 16 offices, a seminar room for up to 50 people, two  meeting/conference rooms, a ‘huddle’ room for small collaborations of 3, 11 cubicles, and some shared office and collaborative space.  

These offices and meeting rooms are shared by various groups: AI Institute for Next Generation Food Systems (AIFS), DataLab, UC Davis TETRAPODS Institute of Data Science (UCD4IDS); and DS+AI-related researchers from the Computer Science, Math, and Statistics Departments. From our Department, faculty Naoki Saito, Jesús De Loera, Yunpeng Shi, and Abi Gopal moved into their offices on the first floor. One postdoc and two graduate students associated with these faculty have also taken spaces there. Since Bruno Nachtergaele, Andrew Waldron, and Martin Fraas are already in offices on the second floor as members of QMAP, the presence of the Department of Mathematics at PDSB has become very significant.

With all this preparation of the building, Fall quarter was perfect timing to have a symposium on “Foundations of Data Science and Machine Learning.” Seventy people registered for this symposium, held on September 23-24, 2024. Three external speakers: Dustin Mixon (Ohio State Univ.); Gal Mishne (UCSD); Junwei Lu (Harvard) and four internal speakers: Thomas Strohmer (Math); Krishna Balasubramanian (Stat); Xin Liu (CS); Yubei Chen (ECE) gave excellent and stimulating talks on cutting-edge research in DS/AI. To conclude this symposium, we organized a panel discussion on the future directions of data science and machine learning both in research and education. We invited six panelists: Gal Mishne (UCSD); Patrice Koehl (CS); Junwei Lu (Harvard); Chen-Nee Chuah (ECE); and Thomas Lee (Stat). Their presentations generated heated discussions among participants, and it was an excellent way to conclude the symposium. With the ample space available and new white boards we could also host a poster session. This event clearly demonstrated the usefulness and functionality of the PDSB! Now there are a number of seminars and research meetings happening every day.