| Joint optimization of device to device resource and power allocation based on genetic algorithm H Takshi, G Doǧan, H Arslan IEEE Access 6, 21173-21183, 2018 | 52 | 2018 |
| Sentiment analysis in Turkish with deep learning GM Demirci, ŞR Keskin, G Doğan 2019 IEEE international conference on big data (big data), 2215-2221, 2019 | 35 | 2019 |
| Energy efficient smart buildings: LSTM neural networks for time series prediction I Sülo, SR Keskin, G Dogan, T Brown 2019 International conference on deep learning and machine learning in …, 2019 | 35 | 2019 |
| HEEL: A new clustering method to improve wireless sensor network lifetime A Seyyedabbasi, G Dogan, F Kiani IET wireless sensor systems 10 (3), 130-136, 2020 | 24 | 2020 |
| A case study on English as a second language speakers for sustainable MOOC study I Duru, AS Sunar, S White, B Diri, G Dogan Sustainability 11 (10), 2808, 2019 | 19 | 2019 |
| A Survey of Provenance in Wireless Sensor Networks. G Dogan Adhoc & Sensor Wireless Networks 30, 2016 | 18 | 2016 |
| Human activity recognition using convolutional neural networks G Dogan, SS Ertas, İ Cay 2021 IEEE Conference on Computational Intelligence in Bioinformatics and …, 2021 | 17 | 2021 |
| An overview of studies about students' performance analysis and learning analytics in MOOCs I Duru, G Dogan, B Diri 2016 IEEE International Conference on Big Data (Big Data), 1719-1723, 2016 | 17 | 2016 |
| ProTru: a provenance‐based trust architecture for wireless sensor networks G Dogan International Journal of Network Management 26 (2), 131-151, 2016 | 16 | 2016 |
| Pronet: Network trust assessment based on incomplete provenance K Govindan, X Wang, M Khan, G Dogan, K Zeng, GM Powell, T Brown, ... 2011-MILCOM 2011 Military Communications Conference, 1213-1218, 2011 | 16 | 2011 |
| Evaluation of network trust using provenance based on distributed local intelligence G Dogan, T Brown, K Govindan, HKM Maifi, T Abdelzaher, P Mohapatra, ... 2011-MILCOM 2011 Military Communications Conference, 1493-1498, 2011 | 14 | 2011 |
| A survey of provenance leveraged trust in wireless sensor networks G Dogan, T Brown Computer Engineering and Intelligent Systems 5 (2), 1-11, 2014 | 10 | 2014 |
| Where are you? Human activity recognition with smartphone sensor data G Dogan, I Cay, SS Ertas, ŞR Keskin, N Alotaibi, E Sahin Adjunct Proceedings of the 2020 ACM International Joint Conference on …, 2020 | 9 | 2020 |
| Dustdoctor: A self-healing sensor data collection system MMH Khan, H Ahmadi, G Dogan, K Govindan, R Ganti, T Brown, J Han, ... Proceedings of the 10th ACM/IEEE International Conference on Information …, 2011 | 9 | 2011 |
| Challenges of identifying second language English speakers in MOOCs I Duru, AS Sunar, G Dogan, S White Digital Education: Out to the World and Back to the Campus: 5th European …, 2017 | 8 | 2017 |
| MultiProTru: A kalman filtering based trust architecture for two-hop wireless sensor networks G Dogan, K Avincan Peer-to-Peer Networking and Applications 10, 278-291, 2017 | 8 | 2017 |
| Predicting ocean-wave conditions using buoy data supplied to a hybrid RNN-LSTM neural network and machine learning models G Dogan, M Ford, S James 2021 IEEE International Conference on Machine Learning and Applied Network …, 2021 | 7 | 2021 |
| Protru: Leveraging provenance to enhance network trust in a wireless sensor network G Dogan City University of New York, 2013 | 7 | 2013 |
| Uncertainty modeling in wireless sensor networks G Dogan, T Brown Proceedings of the International Conference on Big Data and Internet of …, 2017 | 6 | 2017 |
| DNN and CNN approach for human activity recognition ŞR Keskin, A Gençdoğmuş, B Yıldırım, G Doğan, Y Öztürk 2020 7th International Conference on Electrical and Electronics Engineering …, 2020 | 5 | 2020 |
Ted Brownprofessor computer science, queensVerified email at gc.cuny.edu
