Projects per year
Organization profile
Organization profile
The Viz Lab is an interdisciplinary research lab that focuses on emerging visual technologies. We are a brainstorming and project space with a long-standing record of research support. The Viz Lab is open to faculty, graduate students and undergraduates working directly with UMD faculty.
More than 125 researchers from over 20 departments at UMD including Art & Design, Chemical Engineering, Foreign Languages, Large Lakes Observatory, History and Seagrant utilize the Viz Lab and MMAD Lab. Both labs are under the administration of the School of Fine Arts.
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Our work contributes towards the following SDG(s):
Fingerprint
Dive into the research topics where Visual & Digital Image Lab is active. These topic labels come from the works of this organization's members. Together they form a unique fingerprint.
Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Projects
- 1 Active
-
Responding to Climate: Expressing Ourselves Through Conversation, Story, and Art
Fitzpatrick, L.
1/1/23 → 1/1/24
Project: Internal Grant
Research output
- 2 Conference contribution
-
GTraclus: A Local Trajectory Clustering Algorithm for GPUs: A Local Trajectory Clustering Algorithm for GPUSA
Mustafa, H., Barrus, C., Leal, E. & Gruenwald, L., Apr 1 2021, Proceedings - 2021 IEEE 37th International Conference on Data Engineering Workshops, ICDEW 2021. Institute of Electrical and Electronics Engineers Inc., p. 30-35 6 p. 9438775. (Proceedings - 2021 IEEE 37th International Conference on Data Engineering Workshops, ICDEW 2021).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
2 Scopus citations -
An Experimental Comparison of GPU Techniques for DBSCAN Clustering
Mustafa, H., Leal, E. & Gruenwald, L., Dec 2019, Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. Baru, C., Huan, J., Khan, L., Hu, X. T., Ak, R., Tian, Y., Barga, R., Zaniolo, C., Lee, K. & Ye, Y. F. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 3701-3710 10 p. 9006169. (Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
6 Scopus citations