Reza Rawassizadeh
Email: rezar@bu.edu
Address: 1010 Commonwealth Avenue, 3rd Floor, 320, Boston, MA
Telephone: 617-3535296
[Google Scholar] [DBLP]
About me:
I am an assistant professor in the department of computer science, Metropolitan College, Boston University. My research focuses is threefold, one aspect focuses on building low power, or small machine learning algorithms that can run on small devices, and utilizing small datasets (even neural networks). The next aspect of my research dedicates to building health artifacts, including algorithms, applications, and robots to assist users in improving their physical and mental health. My third research focus is on digital health, including public health studies and medical data (image, text) analysis.
Since 2017 I am writing a book a machine learning and AI and tries to cover almost any possible algorithm or concept that it is useful. Still, it is ongoing, but I shared some chapters online here: https://github.com/Rezar/MLBook. Any feedback is very welcome :)
Research Interests: On-device machine learning, Ubiquitous Computing, Digital Health, Wearable Technologies, Assistive Robots
Some public press and media coverages of my work
Computer Science Research Team Wins Best Search UX Award for Fitness Tracker Chatbot - 2023 https://www.bu.edu/met/news/computer-science-research-team-wins-best-search-ux-award-for-fitness-tracker-chatbot
BCS Search Industry awards Reza Rawassizadeh and Yi Rong for best search user experience - 2023 https://www.bu.edu/csmet/2023/03/28/bcs-search-industry-award-winners-reza-rawassizadeh-and-yi-rong
ODSearch enables users to communicate with their fitness tracker in plain natural language - 2023 https://www.growkudos.com/publications/10.1145%25252F3569488/reader
Digital Potentials for [fitness activity] Participation Motivations (translated from German) https://www.fitnessmanagement.de/digital/digitale-potenziale-mitgliedermotivation-science-news
Selected Recent Publications
Javaheri, T. [including Rawassizadeh, R as corresponding author] (2024) XKidneyOnco: An Explainable Framework to Classify Renal Oncocytoma and Chromophobe Renal Cell Carcinoma with a Small Sample Size. BioArXiv https://doi.org/10.1101/2024.01.23.576782
Karimi, F., Amoozgar, Z., Reiazi, R., Hosseinzadeh, M., & Rawassizadeh, R. (2024). Longitudinal Analysis of Heart Rate and Physical Activity Collected from Smartwatches. CCF Transactions on Pervasive Computing and Interaction (To Appear) https://arxiv.org/abs/2211.08628.
Martin, M., Rawassizadeh, R., Pinsky, E., Moreau, P., Gadenne, J., Dautel, J., Félicien, C. (2023) ADA-SHARK: A Shark Detection Framework Employing Underwater Cameras And Domain Adversarial Neural Nets. In , ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). Volume 7, Issue 4. https://dl.acm.org/doi/abs/10.1145/3631416
Ji, X., Sungu-Eryilmaz, Y., Momeni, E., & Rawassizadeh, R. (2023). Speeding Up Question Answering Task of Language Models via Inverted Index. The Generative AI for Pervasive Computing Symposium (GenAI4PC), in conjunction with ACM Interactive, Mobile, Wearable and Ubiquitous Technologies. https://arxiv.org/pdf/2210.13578.pdf.
Rawassizadeh, R. & Rong, Y. (2022). ODSearch: Fast and Resource Efficient On-device Natural Language Search for Fitness Trackers’ Data. https://dl.acm.org/doi/abs/10.1145/3569488. ACM Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). Volume 6, Issue 4. British Computing Society Search Industry Award (Best Search User Experience). [Video demo]
Please check my Google Scholar to see a full list of my works.