I am a researcher and systems engineer working at the intersection of autonomous systems, robotics, and computing systems. My doctoral research in Electrical and Computer Engineering at The Ohio State University, advised by Dr. Marco Brocanelli in the Energy-Aware Systems Lab (EAS-Lab), focuses on improving the efficiency, reliability, and sustainability of resource-constrained autonomous systems.
My work combines algorithm design, software development, and experimental systems engineering. I am particularly interested in how computing resources, hardware limitations, energy consumption, and physical dynamics influence the behavior of autonomous systems. My research spans resource-aware autonomy, energy-efficient robotic navigation, battery-aware computing, edge computing, and parallel graph algorithms.
Beyond algorithm development, I have hands-on experience building and integrating robotic systems, including developing an autonomous mobile robot platform from the ground up. This work has involved embedded computing, sensing, motor control, power monitoring, ROS-based navigation, and software-hardware integration. Working across these components has shaped my interest in understanding how computation, communication, sensing, and physical execution interact in real robotic systems.
I also work on simulation, validation, and system-level performance analysis. My experience includes simulation-based testing, ROS data processing, debugging distributed and compute-intensive systems, and analyzing performance bottlenecks across software and hardware stacks. I am especially interested in making simulation more representative of real-world deployment, so that it can serve as a more reliable tool for evaluating autonomous systems before they are deployed in practice.
Alongside autonomous systems, I study how structural transformations and parallel algorithms improve the efficiency of large-scale graph processing. I also enjoy teaching and mentoring undergraduate and graduate students. Across research and engineering, I am motivated by problems that require both theoretical insight and practical implementation, and I enjoy turning technical ideas into working systems.
News
Paper accepted: Our paper “Speeding-up Graph Algorithms via Parallel Randomized Clique Partitioning” has been accepted for publication in IEEE Transactions on Parallel and Distributed Systems (TPDS). We introduce Par-RCP, a parallel randomized approach to lossless graph restructuring that reduces the number of edges while preserving path information and improving the efficiency of graph algorithms.
Paper accepted: Our paper “Per-object IoU Forecasting for Deadline-Aware Real-Time Embedded Detection Control” (with Erfan Foorginejad and Marco Brocanelli) has been accepted at ECCV 2026. This work studies per-object detection accuracy degradation and deadline-aware runtime control for real-time embedded vision systems.
Paper accepted: Our paper “Fair Battery Degradation-Aware Edge Admission for Mobile Systems” has been accepted as a Regular Full Paper at IEEE EDGE 2026. The work introduces a lightweight battery stress metric for mobile edge tasks, enabling admission decisions that account for latency, energy savings, and long-term battery degradation.
Paper published: Our paper “Speeding-up Graph Algorithms via Clique Partitioning” has been published in Networks. The work investigates lossless graph restructuring using deterministic clique partitioning to improve the efficiency of graph algorithms.