Locations and Networks at scale: From insights to predictive models.

1. Locationsand Networksat scale:
From insightsto predictivemodels
Dmytro Karamshuk
Centreof TelecommunicationsResearch
Department of Informatics, King'sCollege London

2. Understanding watching patterns of on-demand TV users
On Factors Affecting the Usage and Adoption of a Nation-wide TV Streaming Service.
D. Karamshuk, N. Sastry, A. Secker, J. Chandaria, IEEE INFOCOM, Hong Kong, 2015.
ISP-friendly Peer-assisted On-demand Streaming of Long Duration Content in BBC iPlayer.
D. Karamshuk, N. Sastry, A. Secker, J. Chandaria, IEEE INFOCOM, Hong Kong, 2015.

3. Identifying Geographic Clustersof Scientific Activity
Identifying Geographic Clusters: A Network Approach. R. Catini, D. Karamshuk,
O. Penner, M. Riccaboni, Elsevier Journal on Research Policy, 2015.
Japan
Tokyo

4. Mining Social Mediafor Geographic Retail Analysis
Geo-Spotting: Mining Online Location-based Services for Optimal Retail Store Placement.
D. Karamshuk, A. Noulas, S. Scellato, V. Nicosia, C. Mascolo, ACM SIGKDD
Conference on Knowledge Discovery and Data Mining (KDD), Chicago, 2013.

5. Predicting Pinterest: Automating a distributed human computation.
C. Zhong, D. Karamshuk, N. Sastry,
World Wide Web Conference (WWW), Florence, 2015.
Predicting user behavior in Pinterest

6. Dmytro Karamshuk
Twitter: @karamshuk
“Truegeniusresidesin thecapacity for evaluation of
uncertain, hazardous, and conflicting information”
#ChurchillQuotes

7. Dmytro Karamshuk
Twitter: @karamshuk
“Truegeniusresidesin thecapacity for evaluation of
uncertain, hazardous, and conflicting information”
#ChurchillQuotes