Machine Learning & Signal Processing Engineer
🔍 Seeking Thesis/Applied AI/ML Opportunities | Computer Vision & MLOps | Python & C++
Applying signal processing principles to machine learning problems. Based in Tampere, Finland.
I work at the intersection of machine learning and signal processing, applying signal processing principles to data-driven problems. I am a Master's student in Signal Processing and Machine Learning at Tampere University, based in Tampere, Finland.
My interests include supervised and unsupervised learning, time-series analysis, digital filtering, and spectral analysis. I am actively seeking thesis or applied AI/ML opportunities.
I approach problems from an AI/ML perspective while critically evaluating whether simpler analytical or signal-based methods can achieve better efficiency or reliability.
When machine learning is the right choice, I focus on building models that are accurate, explainable, and grounded in strong mathematical principles.
Timeline
A quick look at the education that grounds me, the internships and roles that shaped my craft, and the experiments that keep me curious.
Independent Project
Developing a gesture recognition system using signal processing and machine learning. Focused on real-time performance, robustness to noise, and deployment on edge devices.
Independent Project
Developing a gesture recognition system using signal processing and machine learning. Focused on real-time performance, robustness to noise, and deployment on edge devices.
Tampere University
Focusing on statistical signal processing, time-series modeling, and deployment of ML systems that respect latency and hardware constraints.
Tampere University
Focusing on statistical signal processing, time-series modeling, and deployment of ML systems that respect latency and hardware constraints.
Full Stack Web Development, Computer Science
Completed full stack web development training with a strong focus on practical projects, teamwork, and software engineering best practices.
Full Stack Web Development, Computer Science
Completed full stack web development training with a strong focus on practical projects, teamwork, and software engineering best practices.
Commu App · Part-time
Built and optimized a mobile UI using React Native, and developed backend APIs with PHP, Laravel, GraphQL, and Lighthouse. Worked in a team on full development lifecycle including deployment.
Commu App · Part-time
Built and optimized a mobile UI using React Native, and developed backend APIs with PHP, Laravel, GraphQL, and Lighthouse. Worked in a team on full development lifecycle including deployment.
Tampere University of Applied Sciences · Internship
Developed interactive behaviors for Pepper using Kotlin, enabling communication with humans and performing basic motions like hand waving and dancing.
Tampere University of Applied Sciences · Internship
Developed interactive behaviors for Pepper using Kotlin, enabling communication with humans and performing basic motions like hand waving and dancing.
Tampere University of Applied Sciences (TAMK)
Completed coursework in software engineering fundamentals, algorithms, and system design.
Tampere University of Applied Sciences (TAMK)
Completed coursework in software engineering fundamentals, algorithms, and system design.
Supervised and unsupervised learning approaches with focus on practical, interpretable models rather than black-box solutions.
Advanced filtering, spectral analysis, and transformation techniques for signal enhancement and feature extraction.
Forecasting and pattern recognition in sequential data using both statistical methods and modern machine learning approaches.
Strong background in linear algebra, probability theory, statistics, and optimization—the core of robust ML and DSP work.
Reading Notes
A curated list of papers with personal Notion summaries, critical takeaways, and practical insights for applied ML and signal processing.
Albert Gu, Tri Dao, et al. · ICML · 2024 · Read
Introduced Mamba, a selective state space model that achieves linear-time sequence modeling, avoiding quadratic attention while maintaining strong long-context performance and hardware efficiency.
Interested in collaboration, discussing signal processing challenges, or exploring machine learning projects? Feel free to reach out via email or LinkedIn.
Tampere, Finland
UTC+2
Preferred contact method: LinkedIn message or email