Ph.D. Candidate (Electrical Engineering and Computer Science)
- Health Data Monitoring and Tracking
- Machine Learning and Deep Learning
- Active Learning and Reinforcement Learning
- Recommender Systems
- 2015- Now – M.Sc. and Ph.D. in Electrical Engineering and Computer Science, University of California, Irvine, USA.
- 2010-2015 – B.Sc. in Electrical Engineering, Electronics, and minor in Physics, Sharif University of Technology.
- A. Tazarv, S. Labbaf, S. M. Reich, N. Dutt, A. M. Rahmani and M. Levorato, “Personalized Stress Monitoring using Wearable Sensors in Everyday Settings,” 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021. [IEEEXplore] [preprint].
- A. Tazarv and M. Levorato, “A Deep Learning Approach to Predict Blood Pressure from PPG Signals,” 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021. [IEEEXplore] [preprint].
- Ali Tazarv, Sina Labbaf, Amir M. Rahmani, Nikil Dutt, and Marco Levorato. Data Collection and Labeling of Real-Time IoT-Enabled Bio-Signals in Everyday Settings for Mental Health Improvement. In Proceedings of the Conference on Information Technology for Social Good (GoodIT ’21). Association for Computing Machinery, New York, NY, USA (2021). [ACM Digital Library] [preprint].
- Daniel Khashabi, et al.; ParsiNLU: A Suite of Language Understanding Challenges for Persian. Transactions of the Association for Computational Linguistics 2021; 9 1147–1162. [MIT Press Direct] [preprint].