Current
Ph.D. Students
Alumni
Ph.D. Students
- Ourania Spantidi
Dissertation: Resource-aware Optimization Techniques for Machine Learning Inference on
Heterogeneous Embedded Systems.. First placement: Tenured-track Assistant Professor, Eastern Michigan University, USA.
- Zois Gerasimos Tasoulas
Dissertation: Resource Management and application customization for hardware accelerated systems. First placement: Nvidia, USA.
- Ioannis Galanis
Dissertation: Resource management in edge computing for Internet of
Things. First placemnet: Intel, USA.
- Theodoros Marinakis
Dissertation: Enhancing Fairness And Performance On Chip Multi-processor Platforms With Contention-aware Scheduling Policies. First placement: Nvidia, USA.
MSc Students
- Benjamin Trewin
Thesis: Architecture and Mapping Co-exploration and Optimization for DNN Accelerators.
First placement: Texas Instruments, USA.
- Anish Ghimire
Thesis: Optmization of symmetric Many-core Systems.
First placement: Qualcomm, USA.
- Shraddha Dahal
Thesis: Synergistic Execution of Neural Networks on Modern Embedded Systems.
First placement: Qualcomm, USA.
- Saroj Sapkota
Thesis: Efficient Resource Management on Embedded Devices Via Isolation and Adaptive Resource Allocation.
First placement: Intel, USA.
- Jonathan Dickerson
Thesis: Supporting Approximate Computing on Coarse Grained Re-configurable Array Accelerators.
- Srinivasa Reddy Punyala
Thesis: Throughout Optimization and Resource Allocation on GPUs under multi-application execution.
- Sai Saketh Nandan Perala
Thesis: Efficient Resource Management for Video Applications in the Era of Internet-of-Things (IoT).
First placement: Fiat Chrysler Automobiles, USA.
- Jayasimha sai Koduri
Thesis: Simple Pool Architecture for Application Resource Allocation in Many-Core Systems.
First placement: Qualcomm, USA.
- Daniel Olsen
Thesis: Performance-Aware Resource Management of Multi-Threaded Applications for Many-Core Systems.
First placement: Boeing, USA.
- Mohammad Essa Mohammad
Thesis: Distributed Run-Time and Power Constraints Mapping for Many-Core Systems.
Undergraduate Students
