My paper titled Three factor delay learning rules for spiking neural networks has been accepted for publication in Frontiers in Neuroscience.
Greetings!
Hello there, I’m Luke! I have a background in electronics engineering and a keen interest in artificial intelligence. I find great satisfaction in building customised computational systems that can solve complex problems and impact the world. I specialise in signal processing, artificial intelligence, and embedded systems, focusing on reconfigurable heterogeneous platforms.
As an engineer, I have a natural curiosity and a strong motivation to continuously learn and expand my knowledge. I’m particularly passionate about exploring various ideas and concepts related to computational systems inspired by biology and neuroscience. This could include examining the underlying structures or studying processes that demonstrate adaptability, intelligence, or emergent properties.
I believe that interdisciplinary research can lead to innovative developments in areas related to computation and intelligent systems. I would be happy to chat and explore potential collaborations if you’re working on related projects or have any interesting ideas. Please don’t hesitate to reach out!
In my free time, I love engaging in various activities. Running and exploring the outdoors are among my top favourites. Exploring remote areas is a unique way to experience adventure and appreciate nature’s beauty. Besides, meeting up with friends over a cold beer is always enjoyable. I am also keen on learning how to sail, as it offers an exciting way to discover new places on the open water.
Updates
News
Research, publications, and milestones.
My late-breaking results abstract titled Three-Factor Delay Learning Rules for Spiking Neural Networks has been accepted at the 2025 Neuro-Inspired Computational Elements (NICE) Conference in Heidelberg.
My research paper titled Learning Circuit Placement Techniques through Reinforcement Learning with Adaptive Rewards based on my Master’s thesis, has been accepted for publication at DATE’24.
I joined the Institut für Technische Informatik (Computer Architecture Group) at Universität Heidelberg for my Ph.D., where I am investigating hardware-software co-design methodologies for emerging computing systems.
I completed my Master of Science in Artificial Intelligence and graduated with the highest honours.
I defended my Master’s thesis titled Automated PCB Component Placement using Reinforcement Learning successfully.
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I joined the High-Performance Computing and Data Analysis research group at the University of Osijek for a temporary position, investigating alternative x86 architectures for HPC workloads.
Taped out my first ASIC: a dual-channel XOR stream cipher with fully programmable 32-bit Galois LFSRs, manufactured through Tiny Tapeout 3 on the SkyWater 130 nm node.
The personal website was made public.
I submitted the conference paper titled Generalised PCB Component Placement through Reinforcement Learning with Adaptive Rewards to IJCAI 2023.
I submitted my M.Sc. thesis titled Automated PCB Component Placement using Reinforcement Learning for examination.
The Malta Digital Innovation Authority granted the Pathfinder Digital Scholarship for conducting artificial intelligence research in electronic design automation.