
About
Batuhan Sesli is a Researcher at the Department of Computer Science 12 (Hardware-Software-Co-Design) at Friedrich-Alexander University Erlangen-Nuremberg (FAU), Germany, since July 2024. His work focuses on embedded systems with emphasis on hardware acceleration for machine learning and efficient deployment of TinyML applications on resource-constrained devices.
His educational background includes:
- M.Sc. in Information and Communication Technology from FAU (2022-2024)
- B.Sc. in Electrical & Electronics Engineering from Istanbul Ozyegin University, Turkey, with a minor in Computer Science (2016-2021)
Research interests span acceleration techniques for machine learning workloads via RISC-V ISA extensions and specialized hardware accelerators, efficient deployment of TinyML on low-power devices, and co-design of AI algorithms and hardware. His work optimizes the synergy between algorithmic requirements and hardware capabilities in embedded systems, targeting practical solutions for edge AI applications.
His recent DATE 2024 publication on DNN acceleration through weight clustering on RISC-V custom functional units exemplifies the trend toward energy-efficient specialized hardware, reflecting his focus on bridging algorithmic demands with hardware constraints in real-world embedded scenarios.
He teaches a tutorial on Embedded Systems for Winter Semester 2024/2025 and offers thesis opportunities in his research domain, though no current open theses are listed.
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