Thirst for Knowledge: The Future of Spatial Computing

Join Computer Science & Engineering alumni and faculty at Surly Brewing!

Join the Department of Computer Science & Engineering (CS&E) for this all-alumni event featuring Minnesota spatial computing faculty. Enjoy hosted beverages and appetizers and the chance to reconnect with former classmates, colleagues, instructors, and friends. All alumni of University of Minnesota CS&E programs (Computer Science, Data Science, MSSE) are invited to attend, and guests are welcome.

Register for the event now!

There is no charge to attend our event, but pre-registration is required. Register by Tuesday, Oct. 18.

About the Program

Learn about current and future directions in spatial computing research from three star CS&E faculty members:

• Shashi Shekhar, Professor, Distinguished McKnight University Professor, Distinguished University Teaching Professor: Spatial computing has enriched billions of lives via pervasive services (e.g., navigation, ride-sharing and delivery apps), ubiquitous systems (e.g., global positioning system, remote sensing), and pioneering scientific methods (e.g., spatial statistics). These successes are only a beginning and many transformative opportunities lie ahead due to growth in high-value spatial big data, geospatial cloud analytics, GeoAI, digital twins, etc. Recent initiatives include Amazon Earth on AWS, Google Earth Engine, Microsoft AI for Earth, DARPA Geospatial Cloud Analytics,  I-ARPA HAYSTACK, and NSF Navigating the New Arctic. This presentation shares the spatial computing accomplishments and opportunities along with influential contributions from the University of Minnesota (UMN), the world’s first spatial university.
   
• Mohamed Mokbel, Professor: Spatial Computing Systems: Embedding spatial awareness boosts scalability, accuracy, and efficiency of computing system infrastructures for big data, knowledge discovery, data cleaning, and machine learning. This presentation will discuss the impact of spatial computing systems in various applications along with UMN SpatialHadoop, a pioneering geospatial cloud computing system.
   
• Yao-Yi Chiang, Associate Professor. Spatially-enabled AI: Spatial concepts and methods enhance the effectiveness of Artificial Intelligence (AI) in many areas including health, transportation, and environmental sciences. This presentation will share spatially-enable AI technologies for air quality predictions, data-driven intelligent transportation systems, human mobility mining, and automatic reading of thousands of historical map scans in archives for understanding human-induced changes in the environment.

Questions? Contact cscievents@umn.edu.