Jan Bancerewicz
Jan Bancerewicz / AI & software developerOpen to AI/ML / full-stack roles

I build software that
survives contact with

real data.

Nice '26Hover: run detection

I work on applied machine learning: LLM interpretability, computer vision, and model optimization – as well as the full-stack systems needed to carry them in production. Final-year CS student at Gdańsk Tech with over 1 year of commercial experience in IT, spending my free time competing at hackathons and conducting AI research.

See the work↓Get in touch↗
23+Projects shipped
6Hackathons entered
8+Certifications earned
1+Years of commercial xp
Gdańsk, Poland
PythonSQLTypeScriptC++Spring / JavaPyTorchHugging Facescikit-learnYOLOOpenCVvLLM / OllamaMLflowQdrant / ChromaDBLlamaIndexLoRA/PEFTQuantizationRAG SystemsAnthropic/OpenAI APIGoogle ADKLLM InterpretabilityMultimodal / VLMsComputer VisionSignal ProcessingModel OptimizationFastAPIPyTestPostgreSQLRedisMongoDBREST APINumpy / PandasAndroidDockerKubernetesAzure DatabricksAWSReact / Next.jsTailwind CSSLinuxCI/CD & GitHub ActionsClaude CodeOpenAI CodexCursor IDE

01/Selected work

All 5 projects ↗

My flagship research and full-stack projects. Each breakdown highlights architectural decisions, real-world metrics, and key takeaways.

01 / Multimodal LLMs, Vision-Language / 2026

Qwen-VL for Angiography↗

Adapting Qwen3-VL for coronary vessel segmentation using DeepStack and LoRA, benchmarked against ResNet-34 U-Net on ARCADE SYNTAX. Extension of the Arterio labeling platform at Gdańsk University of Technology

  • Qwen3-VL
  • Hugging Face
  • PyTorch
  • LoRA/PEFT
  • DeepStack
  • Medical Imaging
  • Transformers
  • Segmentation
  • Arterio
02 / Research / Applied ML (biosignals) / 2025

Analysis of HRV Using Mobile Devices and Machine Learning↗

Research project for mobile ECG/PPG peak detection and HRV analysis. Compares 1D-CNN detectors against classical Pan–Tompkins/NeuroKit baselines using smartphone camera PPG and Polar H10 ECG. Peer-reviewed TASK Quarterly publication (March 2026).

  • PyTorch
  • Signal Processing
  • Android
  • Python
  • Research
  • HRV
  • PPG
  • ECG
03 / LLM interpretability / 2026

CORE↗

COmments as a REasoning: do code comments actually change how a language model reasons, or only how its output reads? We answer it by opening the model up rather than grading what comes out.

  • PyTorch
  • Transformers
  • LLM fine-tuning
  • Python

02/Hackathons & competitions

6 programming challenges
2 podium finishes

How I enjoy spending my weekends:
a complex problem, something impactful to build
and zero time for overthinking.

Nov 2024 & 2025

AMPPZ – Polish Collegiate Programming Contest (2x)↗

Warsaw – University of Warsaw

Representing my university in the Polish collegiate programming contest (ICPC) since 2024, placing #34 nationally in 2024 and #55 in 2025 (out of ~80 teams).   As President of the Sfera PG Algorithmic Club, I lead team training in advanced algorithms, complex data structures, and high-pressure problem-solving in C++.

  • Algorithms & Data Structures
  • ICPC
  • C++
34th nationally in 2024
Representing Gdańsk University of Technology
Jan 2026

EU Critical Infrastructure Hackathon↗

Gdańsk – Gdańsk Science and Technology Park

Engineered a security layer for PV inverters, insulating critical grid infrastructure from remote cyberattacks through real-time anomaly detection for remote control. Evaluated and awarded 1st place by an international jury of industry experts.

  • Cybersecurity
  • Energy
  • Modbus32
  • Embedded
  • React Native
1st place
Energy & Offshore category
Nov 2025

Heroes of the Brain – Neurohackathon↗

Wrocław – Wrocław University of Science and Technology

Developed AuraCloud, a Brain-Computer Interface translating raw 8-channel EEG into a continuous three-dimensional emotional space (PAD model) and an automated stimulus path using OASIS dataset to actively guide user mood.

  • BCI
  • EEG
  • Signal Processing
  • Dash
  • Python
2nd place
Signal processing & modelling
May 2026

Hackology II – AI Hackathon↗

Lublin – Lublin University of Technology

Built a 369-class retail product detection pipeline evaluated on mAP@0.5. Combined YOLO and RF-DETR detection with embedding-based retrieval and multi-step reranking to identify products on dense store shelves.

  • Computer Vision
  • YOLO
  • RF-DETR
  • Machine Learning
  • Python
Shipped a full pipeline
Computer vision & Object Detection
Oct 2025

HackYeah↗

Kraków – Tauron Arena

My first hackathon! I built StressLess – a mobile biofeedback app measuring heart rate and HRV via smartphone camera PPG. Combined biometric signals with an LLM pipeline to deliver real-time stress analysis and biohacking insights.

  • Android
  • Signal Processing
  • LLM API
  • Spring / Java
Solo debut, high score
Biohacking Category

03/Internships & commercial experience

2 companies/14 months

Over a year of commercial experience in software engineering and high-throughput production systems, gained alongside studying Computer Science.

  1. ERGO Hestia S.A.
    Jan 2026 — presentCurrent

    8 months

    Data & Software Engineering Intern

    • Working in the Pricing department, I develop and maintain PricePoint, the insurance premium calculation system that takes over 200,000 requests a day.
    • Designed and hosted cloud pipelines on Azure Databricks, developing a translator to convert Earnix risk formulas into scikit-learn prediction models.
    • Delivered features through a CI/CD workflow, collaborating with the team on iterative deployments.
    • Python
    • SQL
    • Azure
    • Databricks
    • Dynatrace
    • Git
    • Agile
  2. Energa Operator S.A.
    Jul — Dec 2025

    6 months

    IT Department Intern — DevOps & systems administration

    • Administered OT infrastructure across a fleet of 90 virtualized servers, managing VMs and system configurations on both Windows and Linux.
    • Developed automation scripts in PowerShell and Bash to handle server monitoring, alerting, and backup processes.
    • Gained hands-on experience with DevOps tasks: deployment, monitoring, and keeping systems up.
    • Hyper-V
    • PowerShell
    • Bash
    • Linux
    • Windows
    • Azure
    • Vim

04/Certifications & courses

Academic foundation, published research, and specialized coursework targeting deep learning, LLMs and software engineering.

19 entries/6 sources

Gdańsk University of Technology

BSc in Computer Science (4.41 GPA) & leadership roles

  • Bachelor's thesis – defending 2026
  • Gradient PG - AI & Machine Learning Science Club – Board Member
  • Sfera PG - Algorithmic & Competitive Programming Club – President

Research & programmes

Peer-reviewed publications & research initiatives

Google

AI business applications & cloud

NVIDIA Deep Learning Institute

High-performance AI & GPU acceleration

DataCamp

Deep learning specialisations

Academic Partners

Modern AI Stack & Applied Software Architecture

05/Writing

All posts ↗

Notes on the technical topics that might interest you.

12 Aug 2026

How to cut your Claude Code token usage by 20x↗

Claude bills a cached token at 0.1x and a cache write at 2x – a 20x spread on identical content. How context and prompt caching work in Claude Code, the hygiene that cuts always-on context, and a one-plugin guard that blocks cold-cache turns before you pay.

LLM tooling/8 min
10 Aug 2026

How to debug Python like a pro↗

Debugging in PyCharm is not print-spam. Breakpoints freeze the process, Step Over/Into/Out move with intent, diffs show what changed, and one mute-all trick lets you jump without getting snagged.

Developer Tools/10 min
28 Jul 2026

What quantization really is↗

Quantization is not magic compression. It is a controlled change in numerical representation that trades precision for memory, bandwidth, and often speed – illustrated with Gemma 4 12B.

AI Engineering/8 min

06/Stack

43 tools

Technologies I reach for by default — tools I’ve trained models with, built pipelines around, and shipped to production.

Languages

  • PythonPython
  • SQL — relational storeSQL
  • TypeScriptTypeScript
  • C++C++
  • SpringSpring / Java

Core AI / ML Frameworks

  • PyTorchPyTorch
  • Hugging FaceHugging Face
  • scikit-learnscikit-learn
  • YOLO — object detection boxYOLO
  • OpenCVOpenCV
  • vLLMvLLM / Ollama
  • MLflowMLflow

GenAI & LLM Stack

  • QdrantQdrant / ChromaDB
  • LlamaIndex — indexed retrieval treeLlamaIndex
  • LoRA — low-rank adaptationLoRA/PEFT
  • Quantization — continuous signal, discretisedQuantization
  • Retrieval-augmented generationRAG Systems
  • AnthropicAnthropic/OpenAI API
  • GoogleGoogle ADK

AI Domains & Architectures

  • Interpretability — probing inside the layersLLM Interpretability
  • Multimodal — vision and language togetherMultimodal / VLMs
  • Computer vision — lens apertureComputer Vision
  • Signal processing — waveformSignal Processing
  • Optimisation — loss coming downModel Optimization

Backend & Data Engineering

  • FastAPIFastAPI
  • PytestPyTest
  • PostgreSQLPostgreSQL
  • RedisRedis
  • MongoDBMongoDB
  • REST API — expose / shareREST API
  • NumPyNumpy / Pandas
  • AndroidAndroid

Cloud, Web & DevOps

  • DockerDocker
  • KubernetesKubernetes
  • DatabricksAzure Databricks
  • AWS — cloud infrastructureAWS
  • ReactReact / Next.js
  • Tailwind CSSTailwind CSS
  • LinuxLinux
  • GitHub ActionsCI/CD & GitHub Actions

Coding GenAI Tools

  • Claude CodeClaude Code
  • OpenAIOpenAI Codex
  • CursorCursor IDE

07/Contact

If this matches what
you are looking for
– say hello.

LinkedIn or email, whichever you prefer – I read everything and reply within a day or two. Tell me what you are building and I will tell you honestly whether I am the right person for it.

Open to AI/ML / full-stack roles. Available for full-time roles. Based in Gdańsk, Poland, comfortable working remote across European time zones.

Message me on LinkedIn↗Email instead→
LinkedInjan-bancerewiczGitHubJanBancerewiczCVDownload PDFORCID0009-0001-3898-5576
jan@portfolio: ~

Jan Bancerewicz — AI & software developer

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