I am a Machine Learning Engineer and Researcher working at the intersection of computer vision, machine learning, and systems design. I focus on translating learning-based methods into deployable, resource-aware implementations that integrate tightly with hardware and embedded platforms. My work spans algorithm development, optimization-based estimation, and computer architecture, with an emphasis on building end-to-end intelligent systems.
-
Active Learning for Object Detection
Active learning framework for underwater object detection, improving annotation efficiency and model performance in vision systems. -
Orientation Tracking with Projected Gradient Descent
IMU-based 3D orientation tracking using constrained quaternion trajectory optimization via projected gradient descent, applied to panoramic image reconstruction. -
Out-of-Order RISC-V Processor
32-bit out-of-order superscalar RISC-V processor implementing dynamic scheduling, register renaming, and instruction-level parallelism. -
Shortest Path Algorithms Exploration
Comparative implementation and analysis of Dijkstra’s and Breadth-First Search (BFS) algorithms for GPS-style routing applications. -
Vaccine Research Data Analysis
Bioinformatics data analysis integrating statistical modeling and computational methods for vaccine research.
Leading Research and Development of Underwater Vision Systems at Engineers for Exploration at UCSD
For questions or collaborations, please contact anallacheruvu@gmail.com
Always exploring, always learning.