Srinivasa Kanduru
PhD (Tech)
spakan@utu.fi +358 29 450 4910 +358 40 686 5391 Joukahaisenkatu 3-5 Turku |
Heterogeneous Multi-core and Many-core Systems
On-chip Run-time Resource Management
Power/Performance/Thermal Modeling and Analysis
https://users.utu.fi/spakan/
System software for resource efficient edge computing
Machine learning for on-chip resource management
Past: Adaptive resource efficient computing, run-time approximation, dynamic power/performance management.
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- Exploiting Approximation for Run-time Resource Management of Embedded HMPs (2025)
- ACM Transactions in Embedded Computing Systems
- HiDP: Hierarchical DNN Partitioning for Distributed Inference on Heterogeneous Edge Platforms (2025)
- Proceedings : Design, Automation, and Test in Europe Conference and Exhibition
- Invited Paper: Mindful AI for Pervasive Health and Wellbeing (PHW) (2025)
- IEEE/ACM International Conference on Computer-Aided Design
- ISCA: Intelligent Sense-Compute Adaptive Co-Optimization of Multimodal Machine Learning Kernels for Resilient mHealth Services on Wearables (2025)
- IEEE Design and Test
- Twill: Scheduling Compound AI Systems on Heterogeneous Mobile Edge Platforms (2025)
- IEEE/ACM International Conference on Computer-Aided Design
- Adaptive approximate computing in edge AI and IoT applications: A review (2024)
- Journal of Systems Architecture
- Adaptive Workload Distribution for Accuracy-aware DNN Inference on Collaborative Edge Platforms (2024)
- Proceedings of the Asia and South Pacific Design Automation Conference
- EA2: Energy Efficient Adaptive Active Learning for Smart Wearables (2024)
- Proceedings : International Symposium on Low Power Electronics and Design
- ECG Unveiled: Analysis of Client Re-identification Risks in Real-World ECG Datasets (2024)
- International Conference on Wearable and Implantable Body Sensor Networks
- SEAL: Sensing Efficient Active Learning on Wearables through Context-awareness (2024)
- Proceedings : Design, Automation, and Test in Europe Conference and Exhibition
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