🎓 Summer school · 6–17 Jul 2026
Tsinghua University, Shenzhen
Heading to Shenzhen for a two-week summer school at Tsinghua University (SIGS).
Machine learning engineer and architect, and PhD researcher working on Edge AI for robotics and embedded perception. I get modern neural networks running on small hardware: microcontrollers and AI camera sensors. PhD researcher at ETH Zürich and CSEM.
🎓 Summer school · 6–17 Jul 2026
Heading to Shenzhen for a two-week summer school at Tsinghua University (SIGS).
📄 NeurIPS preprint · May 2026
New preprint on fully ternary vision transformers. Each weight is one of three values, which shrinks the model and cuts its memory-bandwidth needs, the real bottleneck on edge chips.
arXiv:2605.21171 ↗
🤖 Hackathon · Forgis
Competing in Forgis's physical-AI robotics hackathon, run with Google DeepMind and IBM.
▶ Watch the demo ↗
🎓 Doctoral exam · 2026
Cleared the ETH doctoral exam, examined by Prof. Luca Benini, Prof. Michele Magno, and Dr. Nadim Maamari.
🎤 Talk · tinyML
Giving a talk at the tinyML event hosted at the Logitech HQ in Lausanne.
🔬 Research trip · Sep 2025
Visited TSMC's Hsinchu fab and met semiconductor researchers across Taiwan.
Read the post ↗I'm Szymon Ruciński, a PhD researcher in electrical engineering at ETH Zürich (D-ITET) and CSEM. I work on running modern AI on small, power-constrained hardware: microcontrollers, AI camera sensors, and embedded boards like NVIDIA Jetson, mostly for robotics and industrial perception. I'm part of SwissChips, the prestigious CSEM–EPFL–ETH Zürich initiative strengthening Switzerland's semiconductor base end to end — chip design, chip production, and running intelligence on the chips themselves.
Day to day that means model compression (quantization and pruning), hardware-aware training, and perception pipelines that fit the chip they run on. With years of experience as a machine learning engineer and machine learning architect, before the PhD I built production systems at Accenture, TransPerfect, Samsung R&D, and Visium: agentic AI for enterprises, custom translation models, and computer-vision pipelines.
On the side I train and open-source Polish language models, and I mentor students at ETH's Robotics and Analytics clubs. I've won AI hackathons for the United Nations and with Samsung's translation team. What I care about most is getting research out of the notebook and onto real hardware.

Model compression for transformers (quantization, pruning) and hardware-aware perception pipelines for robotics. I deploy on microcontrollers, AI camera sensors, NVIDIA Jetson, and DGX Spark, and train at scale on HPC clusters.

Set up an in-house data center. Built custom LLMs that improved translation quality in French, English, German, and Italian, made the production model 5× faster to serve, and added retrieval-augmented search over the internal knowledge base.

Built multimodal and agentic AI systems and MCP servers for enterprise clients. Cut call-center ticket resolution from six hours to five minutes at 84% success, on-premise and on Azure. Led a small engineering team across Berlin and Stuttgart.

Built unsupervised computer-vision anomaly detection that improved faulty-sample identification by 97%. Found and fixed errors in a chemical manufacturer's dataset, which raised output by 20%. Also shipped a document data-extraction system and an internal package for prototyping CNNs.

AI translation for low-resource languages, including Indian dialects. Built synthetic text-generation and quality pipelines over hundreds of terabytes, and shipped NLP features in Bixby. My team, SRPOL, won WAT-2021.
One of the largest open Polish LLMs when it was released. I cleaned and assembled the training data, fine-tuned the model, served it on cheap CPU-only hardware, and released it free for anyone to use.
A 1.5-billion-parameter Polish speech-recognition model that captions in real time. Fine-tuned on 50,000 audio and text pairs, and open-sourced on Hugging Face.
I mentor students in the Robot Learning Division and work on world models and reinforcement learning for robots. We compete in robotics hackathons with partners including OpenAI, Tesla, ABB Robotics, NVIDIA, Hugging Face, and AWS.
I mentor ETH student teams. One project built an NLP tool for WWF Switzerland, where I helped with the modelling and kept the work organized.

Supervised by Prof. Michele Magno & Dr. Nadim Maamari.


Supervised by Prof. Dr. Daniel Perruchoud.

