Rate My Professor Farnoush Banaei-Kashani

Her research encompasses Data Science applications addressing real-world challenges with AI-powered solutions across the data lifecycle, including health informatics, personalized medicine, computational biology, intelligent edge computing, IoT, transportation, smart infrastructures, and geospatial analysis, handling diverse data types such as sequences, time series, graphs, spatiotemporal, images, and videos. She also specializes in data management, mining, and modeling, particularly spatiotemporal and graph data management/mining and high-throughput processing. With over 120 refereed publications, notable works include "Efficient Maximal Reverse Skyline Query Processing" (Geoinformatica, 2017), "A Lightweight and Inexpensive In-ear Sensing System For Automatic Whole-night Sleep Stage Monitoring" (ACM SenSys 2016, Best Paper Award), "Voronoi-based geospatial query processing with MapReduce" (IEEE CloudCom 2010, Best Paper Award), and "Janus - Multi Source Event Detection and Collection System for Effective Surveillance of Criminal Activity" (JIPS, 2014). Her research is funded by NSF, NIH, DOE, DOD, NASA, and industry. She serves as a senior program committee member for conferences like KDD, SIGMOD, VLDB, and has received multiple best paper awards.