Alexandros Angelakis
I am an MSc student in Computer Science and Engineering at the University of Crete (GPA: 9.64/10.00), with a focus on Artificial Intelligence, Machine Learning, and Signal Processing. My thesis explores Adaptive Sinusoidal Models for Parkinson’s disease. I am also a member of the Speech Signal Processing Lab as an MSc student. In addition, I serve as a Teaching Assistant in the Applied Mathematics for Engineers and Digital Signal Processing courses, supporting lectures, grading, and student mentoring.
Research & Industry Experience
In parallel, I am a research intern at the Data Science Lab of IACM-FORTH, working with Dr. Yannis Pantazis. I led the development of NeuroDiMe, a unified Python library for neural-based estimation of statistical distances (e.g., f-divergences, IPMs), which supports PyTorch, JAX, and TensorFlow. This tool is used in cutting-edge AI workflows, including $\beta$-VAE representation learning and GAN/VAE generative modeling. Since June 2024, the NeuroDiMe project has been supported by Apple Inc. through IACM.
I also contributed to the IACM’s research on complex systems by designing and implementing graph traversal algorithms for optimal sensor placement in Water Distribution Networks, enabling accurate leak localization using Python, GeoPandas, NetworkX, and GIS.
My recent research at the Speech Signal Processing Lab involves developing deep learning models for Tuberculosis detection from cough audio signals, achieving robust classification between healthy and unhealthy samples using Python, Sklearn, and TensorFlow. I have also assisted in building and evaluating a 20-hour multi-speaker Greek speech dataset, training state-of-the-art text-to-speech models with ESPnet.
Academic Background & Honors
I hold a BSc in Computer Science from the University of Crete (GPA: 8.77/10.00), where I worked as a teaching assistant for several courses, including Applied Mathematics for Engineers, Probabilities, and Information System Analysis and Design. I have received multiple academic honors, including four scholarships from the State Scholarships Foundation (IKY) between 2020-2023 and the Chrysanthos and Anastasia Karidis Scholarship for outstanding performance in the national entrance exams.
I have actively engaged in the academic community by delivering outreach presentations to high school students, highlighting research from the Speech Signal Processing Laboratory, and mentoring first-year students through the STEER mentoring program as a Peer Mentor.
Technical Snapshot
My technical expertise includes programming in Python, MATLAB, C, and Java, and proficiency with deep learning frameworks and libraries such as PyTorch, TensorFlow, JAX, Numpy, Pandas, Scikit-Learn, and Scipy. I am also familiar with databases like SQL and PostgreSQL.
For more details, please refer to my detailed CV.