Current Students

Ph.D. Students

Research: Sustainable DNN acceleration and carbon-efficient edge systems
Research: Multi-tenant DNN execution and LLM optimization on edge devices

Alumni

Ph.D. Graduates

Orchestrating Multi-Objective Neural Network Deployment in Heterogeneous Edge Systems
💼 AMD, USA
Resource-Optimized Scheduling for Enhanced Power Efficiency and Throughput on Chip Multi-Processor Platforms.
💼 Apple, USA
Resource-aware Optimization Techniques for Machine Learning Inference on Heterogeneous Embedded Systems
🏫 Asst. Professor, Eastern Michigan University
Resource Management and Application Customization for Hardware Accelerated Systems
💼 Nvidia, USA
Resource Management in Edge Computing for Internet of Things
💼 Intel, USA
Enhancing Fairness and Performance on Chip Multi-processor Platforms with Contention-aware Scheduling Policies
💼 Nvidia, USA

MSc Graduates

Jared Hilyer
Optimizing Differentiable Logic Gate Networks
Nimmi Regmi
Real-Time Fault Detection and Classification in Radial Power Distribution Network using DNNs
💼 CMTA, USA
Benjamin Trewin
Architecture and Mapping Co-exploration and Optimization for DNN Accelerators
💼 Texas Instruments, USA
Anish Ghimire
Optimization of Symmetric Many-core Systems
💼 Qualcomm, USA
Shraddha Dahal
Synergistic Execution of Neural Networks on Modern Embedded Systems
💼 Qualcomm, USA
Saroj Sapkota
Efficient Resource Management on Embedded Devices Via Isolation and Adaptive Resource Allocation
💼 Intel, USA
Jonathan Dickerson
Supporting Approximate Computing on Coarse-Grained Re-configurable Array Accelerators
Throughput Optimization and Resource Allocation on GPUs under Multi-application Execution
Efficient Resource Management for Video Applications in the Era of Internet-of-Things (IoT)
💼 Fiat Chrysler Automobiles, USA
Simple Pool Architecture for Application Resource Allocation in Many-Core Systems
💼 Qualcomm, USA
Performance-Aware Resource Management of Multi-Threaded Applications for Many-Core Systems
💼 Boeing, USA
Mohammad Essa Mohammad
Distributed Run-Time and Power Constraints Mapping for Many-Core Systems

Undergraduate Students