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I am on the job market! I am a Ph.D. candidate at the University of Maryland, advised by Soheil Feizi and Héctor Corrada Bravo. My research focuses on the interpretability of neural models, long-term forecasting in time series, and applications of deep learning in neuroscience and health informatics. |
I recieved Wylie Dissertation Fellowship.
I will be giving a talk at NCI about Deep learning interpretability.
One paper accepted at NeurIPS 2021.
RNNs, LSTMs and Transformers. (Deep Learning Foundations course)
Deep Learning Interpretations. (Deep Learning Foundations course)
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Improving Deep Learning Interpretability by Saliency Guided TrainingAya Abdelsalam Ismail, Héctor Corrada Bravo, Soheil Feizi. NeurIPs 2021. |
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Benchmarking Deep Learning Interpretability in Time Series PredictionsAya Abdelsalam Ismail, Mohamed Gunady, Héctor Corrada Bravo, Soheil Feizi. NeurIPs 2020. |
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Input-Cell-Attention Reduces Vanishing Saliency of Recurrent Neural NetworksAya Abdelsalam Ismail, Mohamed Gunady, Luiz Pessoa, Héctor Corrada Bravo, Soheil Feizi. NeurIPs 2019. |
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The Alzheimer’s Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-upRazvan V. Marinescu, … et al, Aya Ismail. |
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Improving Long-Horizon Forecasts with Expectation-Biased LSTM NetworksAya Abdelsalam Ismail, Timothy Wood, Héctor Corrada Bravo. |
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LIMO: Learning Programming using Interactive Map ActivitiesRuby Y. Tahboub, Jaewoo Shin, Aya Abdelsalam, Jalaleldeen W Aref, Walid G. Aref, Sunil Kumar Prabhakar. SIGSPATIAL 2015. |
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On Map-Centric Programming EnvironmentsWalid G Aref, Sunil Prabhakar, Jaewoo Shin, Ruby Y Tahboub, Aya Abdelsalam, Jalaleldeen W Aref. SIGSPATIAL 2015. |