Naman Awasthi

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Saad Mohammad AbrarGraduate Research Assistant, University of MarylandVerified email at umd.edu
Vanessa Frías MartínezAssociate Professor, iSchool and UMIACS, University of MarylandVerified email at umd.edu
Aniket BeraProfessor of Computer Science, Purdue UniversityVerified email at purdue.edu
Pooja GuhanStudent at University of Maryland College ParkVerified email at cs.umd.edu
Dinesh ManochaDistinguished University Professor, University of Maryland at College ParkVerified email at umd.edu
Enrique Frias-MartinezResearch Institute for Innovation and Technology in Education (UNIR iTED)Verified email at unir.net
Jiahui WuUniversity of MarylandVerified email at umd.edu
Manas AgarwalMasters student, University of Maryland College ParkVerified email at cs.umd.edu
Jessica VitakAssociate Professor, College of Information Studies, University of MarylandVerified email at umd.edu
Daniel SmolyakUniversity of Maryland, College ParkVerified email at umd.edu
Nikhil NaikMITVerified email at mit.edu
Rohit PandharkarMassachusetts Institute of TechnologyVerified email at media.mit.edu

Naman Awasthi

Graduate Student, University of Maryland, College Park

Verified email at terpmail.umd.edu

Deep learning Mobility Multimodal Learning Time series forecasting natural language processing


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Enhancing short-term crime prediction with human mobility flows and deep learning architectures J Wu, SM Abrar, N Awasthi, E Frias-Martinez, V Frias-Martinez EPJ data science 11 (1), 53, 2022	11	2022
ABC-Net: Semi-supervised multimodal GAN-based engagement detection using an affective, behavioral and cognitive model P Guhan, M Agarwal, N Awasthi, G Reeves, D Manocha, A Bera arXiv preprint arXiv:2011.08690, 2020	9	2020
Auditing the fairness of place-based crime prediction models implemented with deep learning approaches J Wu, SM Abrar, N Awasthi, V Frías-Martínez Computers, Environment and Urban Systems 102, 101967, 2023	5	2023
Using COVID-19 vaccine attitudes on Twitter to improve vaccine uptake forecast models in the United States: infodemiology study of Tweets N Sigalo, N Awasthi, SM Abrar, V Frias-Martinez JMIR infodemiology 3 (1), e43703, 2023	3	2023
Developing an effective and automated patient engagement estimator for telehealth: A machine learning approach P Guhan, N Awasthi, K Bussell, D Manocha, G Reeves, A Bera arXiv preprint arXiv:2011.08690, 2020	2	2020
Analysis of performance improvements and bias associated with the use of human mobility data in covid-19 case prediction models SM Abrar, N Awasthi, D Smolyak, V Frias-Martinez ACM Journal on Computing and Sustainable Societies 1 (2), 1-36, 2023	1	2023
The BALTO Toolkit-A New Approach to Ethical and Sustainable Data Collection for Equitable Public Transit V Frias-Martinez, S Abrar, N Awasthi, S Park, J Vitak Proceedings of the 6th ACM SIGCAS/SIGCHI Conference on Computing and …, 2023	1	2023
TeleEngage: A Multimodal Semi-Supervised Approach to Measure Engagement for Telemental Health P Guhan, N Awasthi, R Das, M Agarwal, K McDonald, K Bussell, ...		2022
Spatio-temporal analysis of Indian urban infrastructure growth using deep learning and 3-channel RGB satellite images N Awasthi, R Pandharkar, N Naik Tenth International Conference on Graphics and Image Processing (ICGIP 2018 …, 2019		2019
COVID-19’s Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data SM Abrar, KT Zinat, N Awasthi, V Frias-Martinez

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