Summary
Shamini Koravuna is a research-driven embedded AI engineer with eight years of experience bridging deep learning, computer vision and electronics, currently pursuing a PhD in Intelligent Systems at Bielefeld University. Trained at Chemnitz University of Technology and Udacity, she combines hands-on embedded development (C/C++, Embedded C, VHDL/Verilog in progress) with production-ready ML—Python, TensorFlow, Keras, PyTorch and OpenCV—for edge and resource-constrained platforms. Her work on neuro-inspired, resource-efficient hardware architectures for plastic spiking neural networks reflects a rare blend of neuroscience-informed research and practical hardware-aware model design. She has taught and scaled ML curricula—training 350+ graduates—and led projects translating 3D human-pose and multi-sensor research into applied solutions during industry and academic collaborations. Comfortable across the stack from data modeling and evaluation to 3D image processing, she’s focused on making intelligent systems both efficient and deployable on embedded platforms. Based in Bielefeld, Germany, she brings curiosity-driven problem solving and a strong math/statistics foundation to interdisciplinary AI and embedded systems challenges.
7 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD Intelligent Systems, Doctor of Philosophy - PhD Intelligent Systems at Bielefeld University
Nanodegree Machine Learning Engineer, Nanodegree Machine Learning Engineer at Udacity
Master's degree Embedded Systems, Master's degree Embedded Systems at Technische Universität Chemnitz
Bachelor's degree Electronics and Communications Engineering, Bachelor's degree Electronics and Communications Engineering at Osmania University
Kendriya Vidyalaya Sangathan
Hindi, Telugu, English, German