Data-driven Scientific Discovery and Ubiquitous Computing: Systems, Algorithms, Applications

Speaker: Dr. Qin Lv
         University of Colorado Boulder

Title:   "Data-driven Scientific Discovery and Ubiquitous Computing:
         Systems, Algorithms, Applications"

Date:    Thursday; Oct 19th 2023

Time:    3:00pm - 4:00pm

Venue:   Rm5508 (via lift 25/26), HKUST


Abstract:

The explosive growth of our digital universe has brought about fundamental
changes to scientific research and our daily activities. Effective and
efficient data analytics has become increasingly important for managing
and exploring massive amounts of data in a wide range of application
domains. Many of these real-world problems call for a full-stack data
analytics approach that jointly considers the systems, algorithms, and
applications aspects that span the complete data analytics pipeline. In
this talk, I will give an overview of our research work, including
mobile/wearable/IoT sensing at the systems layer, multi-modal data fusion
and anomaly detection at the algorithms layer, and some application
scenarios. I will highlight the technical challenges and our key
innovations, and discuss directions for future research.


Biography:

Dr. Qin "Christine" Lv is a Professor and Co-Associate Chair for Graduate
Education in the Department of Computer Science, University of Colorado
Boulder, USA. She received her PhD degree in computer science from
Princeton University. Lv's research focuses on full-stack data analytics.
Topics of interest include mobile/wearable/IoT sensing, multi-modal data
fusion, anomaly detection, and user behavior analysis. Her research
interacts with many scientific domains including Earth sciences,
electrified transportation, renewable and sustainable energy,
oceanography, as well as the information needs in people's daily life. Lv
has received many awards, including the IMWUT 2021 Distinguished Paper
Award, SenSys 2018 Best Paper Runner-up Award, 2017 Google Faculty
Research Award, and VLDB 2017 Ten Year Best Paper Award.