<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Devis Nishku</title><description>Posts and projects by Devis Nishku.</description><link>https://devisnishku.com/en/</link><language>en</language><atom:link href="https://devisnishku.com/en/rss.xml" rel="self" type="application/rss+xml"/><item><title>Multi-person localization with UWB radar on a microcontroller</title><link>https://devisnishku.com/en/projects/uwb-radar-multi-person-localization/</link><guid isPermaLink="true">https://devisnishku.com/en/projects/uwb-radar-multi-person-localization/</guid><description>TinyML system locating up to 4 people from 6 UWB radars: a 90.3 KB int8 CNN for the ESP32-S3, F1 of 0.907 on held-out validation windows.</description><pubDate>Thu, 01 Oct 2026 00:00:00 GMT</pubDate><category>TinyML</category><category>Edge AI</category><category>UWB radar</category><category>Quantization</category><category>CNN</category><category>TensorFlow Lite</category></item><item><title>Continuous LSTM and cPNN in CapyMOA for continual learning</title><link>https://devisnishku.com/en/projects/continuous-lstm-cpnn-capymoa/</link><guid isPermaLink="true">https://devisnishku.com/en/projects/continuous-lstm-cpnn-capymoa/</guid><description>cLSTM and cPNN as CapyMOA classifiers on a stream with 7 concept drifts: cPNN has the higher mean Kappa in 2 concepts, cLSTM in 5.</description><pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate><category>Streaming continual learning</category><category>Concept drift</category><category>CapyMOA</category><category>PyTorch</category><category>LSTM</category></item><item><title>Data quality pipeline for the Global Shark Attack File</title><link>https://devisnishku.com/en/projects/shark-attacks-data-quality-pipeline/</link><guid isPermaLink="true">https://devisnishku.com/en/projects/shark-attacks-data-quality-pipeline/</guid><description>A pandas pipeline for the Global Shark Attack File: 6,094 to 5,980 rows, completeness from 91.54% to 100%, 91 duplicates removed by record linkage.</description><pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate><category>Data quality</category><category>Data cleaning</category><category>Record linkage</category><category>Deduplication</category><category>pandas</category><category>Python</category></item><item><title>Multivariate time series classification with Conv1D and GRU</title><link>https://devisnishku.com/en/projects/multivariate-time-series-classification/</link><guid isPermaLink="true">https://devisnishku.com/en/projects/multivariate-time-series-classification/</guid><description>Multivariate time series classification in PyTorch for a Politecnico di Milano course challenge: 95.5% F1 on the Kaggle leaderboard.</description><pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate><category>Time series</category><category>Deep learning</category><category>PyTorch</category><category>GRU</category><category>Class imbalance</category><category>Kaggle</category></item><item><title>PoliMillionaire quiz QA agent: web-search RAG with a local LLM</title><link>https://devisnishku.com/en/projects/polimillionaire-qa-agent/</link><guid isPermaLink="true">https://devisnishku.com/en/projects/polimillionaire-qa-agent/</guid><description>Web-search RAG with a 4-bit Qwen2.5-7B for a timed quiz, in text and speech modes: $1M reached in text mode in every category.</description><pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate><category>RAG</category><category>Open-weights LLMs</category><category>Web search</category><category>Reranking</category><category>Quantization</category><category>NLP</category></item><item><title>Streaming Continual Learning: MSc thesis on architectures</title><link>https://devisnishku.com/en/projects/master-thesis-streaming-continual-learning/</link><guid isPermaLink="true">https://devisnishku.com/en/projects/master-thesis-streaming-continual-learning/</guid><description>Early-stage MSc thesis at Politecnico di Milano on deep learning architectural strategies for Streaming Continual Learning.</description><pubDate>Wed, 30 Sep 2026 00:00:00 GMT</pubDate><category>Streaming Continual Learning</category><category>Concept drift</category><category>Deep learning</category><category>Recurrent neural networks</category><category>MSc thesis</category></item></channel></rss>