معرفی
Hande Alemdar is an Assistant Professor at the Department of Computer Engineering, Middle East Technical University, specializing in machine learning, data science, and big data analytics. She earned her BSc, MSc, and PhD in Computer Engineering from Boğaziçi University in 2004, 2009, and 2015, respectively, with her PhD thesis awarded the Bogazici University Research Fund (BAP) Best Thesis Award.
- PhD in Computer Engineering (2015), Boğaziçi University
- MSc in Computer Engineering (2009), Boğaziçi University
- BSc in Computer Engineering (2004), Boğaziçi University
Her research focuses on applying machine learning to resource-efficient hardware, wireless sensor networks, and smart environments. She has pioneered work on ternary neural networks for FPGA-based AI, which reduce computational costs while maintaining accuracy. Her work spans diverse applications like activity recognition, fall detection, and sports analytics.
Her recent publications reflect trends in deep learning for hardware efficiency, smart healthcare via ambient sensors, and network security with machine learning. These studies often integrate multi-modal sensor fusion and real-time data analysis, emphasizing deployability in resource-constrained scenarios.
Scientific Awards
- Bogazici University BAP Best Thesis Award
Hande has collaborated with Grenoble Informatics Institute and industry leaders like ST Microelectronics on energy-efficient AI. Her work has been published in journals and conferences such as Sensors, Computers & Graphics, and FPL, addressing topics from elite football performance analysis to covert channel detection in SDN.
She leads research in scalable architectures for smart environments and is involved in the H2020 FET Project 'ROBOtic Replicants for Optimizing the Yield by Augmenting Living Ecosystems', demonstrating her commitment to interdisciplinary AI applications.
