PhD Agnieszka Mikołajczyk is an author of datasets, scientific papers, and publications, holding numerous scholarships and awards. She works on Large Language Models like the first Polish GPT model called TRURL. She is a co-organizer of PolEval2021 and PolEval 2022 tasks with punctuation prediction and restoration. She organizes and actively contributes to the scientific community in her free time: she managed and led the team during the HearAI project focused on modeling Sign Language (hearai.pl). A former organizer and a team leader at the open-source project detectwaste.ml. As an ML Expert, she supports the project “Susana” designed to detect and read product expiry dates to help the Blind “see”. Daily, she conducts her research on her grant “Detecting and overcoming bias in data with explainable artificial intelligence” Preludium, awarded by Polish National Centre (biasinml.netlify.app).
PhD in Machine Learning, 2017 - 2021
Gdańsk University of Technology
MEng in Control Theory, 2016 - 2017
Gdańsk University of Technology
BSc in Automation Control and Robotics, 2012 - 2016
Gdańsk University of Technology
Currently, in contrast to shallow models exploited in the past, most deep learning systems extract features automatically, and to do …
The proposed classify-waste benchmark is a merged collection of publicly available datasets with eight classification labels. The …
Deaf people are affected by many forms of exclusion, especially now in the pandemic world. HearAI aims to build a deep learning …
Speech transcripts generated by Automatic Speech Recognition (ASR) systems typically do not contain any punctuation or capitalization. …
Dataset TinyHero includes 64x64 retro-pixel character. All characters were generated with Universal LPC spritesheet by makrohn. Each …
In the last twenty years the interest of automated skin lesion classification dynamically increased partially because of public …
Sound-Based Bird Classification using Convolutional Neural Networks and Mel-Cepstrum Sepctrograms
Using detection models to localize and classify waste on images and video.
Hackathon. Let's do something for our environment.
ML data collections
Currently, in contrast to shallow models exploited in the past, most deep learning systems extract features automatically, and to do …
The proposed classify-waste benchmark is a merged collection of publicly available datasets with eight classification labels. The …
Deaf people are affected by many forms of exclusion, especially now in the pandemic world. HearAI aims to build a deep learning …
Speech transcripts generated by Automatic Speech Recognition (ASR) systems typically do not contain any punctuation or capitalization. …
Dataset TinyHero includes 64x64 retro-pixel character. All characters were generated with Universal LPC spritesheet by makrohn. Each …
In the last twenty years the interest of automated skin lesion classification dynamically increased partially because of public …
Sound-Based Bird Classification using Convolutional Neural Networks and Mel-Cepstrum Sepctrograms
Using detection models to localize and classify waste on images and video.
Hackathon. Let's do something for our environment.