Buddhi Ashan Mallika Kankanamalage
Postdoctoral Fellow, Department of Computer Science · The University of Texas at San Antonio
I redesign classical geometric data structures making them efficient in theory and fast in practice on parallel hardware. On top of them I build fast retrieval systems that search billions of shapes over large spatial data. These systems can extend naturally into metric-native retrieval for AI systems.
Email buddhiashan [dot] mallikakankanamalage [at] utsa [dot] edu
I work on parallel algorithms and data structures over large geospatial datasets: polygon clipping harnessing GPUs that handle degenerate cases, which are common in real-world data, improve non contributing line segments employing segment trees, and quadtree-based encodings that make shape-based similarity search practical at the scale of a billion polygons. My work has appeared at CCGrid (best paper finalist), ICPP, IEEE BigData, and ACM SIGSPATIAL, and have released code and benchmark datasets publicly. Additionally, I lead Research Activities Management Portal (RAMP) development for the NSF-funded ScooterLab project.
Education
- Ph.D. in Computer Science The University of Texas at San Antonio · Advisor: Dr. Sushil K. Prasad · Co-advisor: Dr. Satish Puri 2019 – 2024
- M.S. in Computing and Information Science Sam Houston State University 2017 – 2019
- B.Sc. (Special) in Computer Science University of Kelaniya, Sri Lanka · First class honours 2011 – 2016
Appointments
- Postdoctoral Fellow Department of Computer Science, UT San Antonio Sep 2024 – present
- Graduate Research / Teaching Assistant Department of Computer Science, UT San Antonio 2019 – 2024
- Graduate Assistant Department of Computer Science, Sam Houston State University 2017 – 2019
- Temporary Lecturer / Demonstrator University of Kelaniya, Sri Lanka 2016 – 2017