Taha Hassan
Taha Hassan
Virginia Tech, Department of Computer Science
Verified email at - Homepage
Cited by
Cited by
An empirical investigation of VI trajectory based load signatures for non-intrusive load monitoring
T Hassan, F Javed, N Arshad
IEEE Transactions on Smart Grid 5 (2), 870-878, 2013
Trust and trustworthiness in social recommender systems
T Hassan
Companion proceedings of the 2019 world wide web conference, 529-532, 2019
Manual-setup residential non-intrusive demand disaggregation using enhanced differential evolution
T Hassan
Proceedings of 1st Int. Workshop Non-Intrusive Load Monitoring, Pittsburgh, PA, 2012
Learning to trust: Understanding editorial authority and trust in recommender systems for education
T Hassan, B Edmison, T Stelter, DS McCrickard
Proceedings of the 29th ACM Conference on User Modeling, Adaptation and …, 2021
On bias in social reviews of university courses
T Hassan
Companion Publication of the 10th ACM Conference on Web Science, 11-14, 2019
Depth of use: an empirical framework to help faculty gauge the relative impact of learning management system tools
T Hassan, B Edmison, L Cox, M Louvet, D Williams, DS McCrickard
Proceedings of the 2020 ACM Conference on Innovation and Technology in …, 2020
Collaborative filtering for household load prediction given contextual information
T Hassan, N Arshad, E Dahlquist, DS McCrickard
SDM '17 Workshop on Machine Learning for Recommender Systems (MLRec '17 …, 2017
Pokémon GO with social distancing: social media analysis of players' experiences with location-based games
M Saaty, D Haqq, M Beyki, T Hassan, DS McCrickard
Proceedings of the ACM on Human-Computer Interaction 6 (CHI PLAY), 1-22, 2022
Exploring the context of course rankings on online academic forums
T Hassan, B Edmison, L Cox, M Louvet, D Williams
Proceedings of the 2019 IEEE/ACM International Conference on Advances in …, 2019
Data-informed learning design in a computer science course
D Williams, II Larry Cox, M Ellis, B Edmison, T Hassan, MA Bond, ...
Learning Design and Technology, 2022
Mining the frequent use-contexts of learning management system tools and assessing their impact on learning outcomes
T Hassan
Preprint, 0
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