Jakub Chłędowski

Jakub Chłędowski

Deep Learning Researcher, PhD Student

Jagiellonian University

Biography

PhD student interested in applying deep learning in practice. My current research revolves around the topic of breast cancer detection. Supervised by prof. Krzysztof Geras and dr. Stanisław Jastrzębski.

Interests
  • Artificial Intelligence
  • Computer Vision
  • Medical Image Analysis
  • Natural Language Processing
Education
  • PhD in Artificial Intelligence, 2017-

    Jagiellonian University (col. with New York University)

  • Erasmus+ in Artificial Intelligence, 2016-2017

    Universitat Politècnica de Catalunya

  • MS in Applied Mathematics, 2015-2017

    Jagiellonian University

  • BSc in Mathematics, 2012-2015

    Jagiellonian University

Publications

(2021). Lessons from the first DBTex Challenge. In Nature Machine Intelligence.

PDF Video DOI

(2021). Robust Learning-Augmented Caching: An Experimental Study. In ICML.

PDF Cite Code Dataset Poster Video

(2021). Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis. In MIDL.

PDF Cite Code

(2020). From Dataset Recycling to Multi-Property Extraction and Beyond. In CONLL.

PDF Cite Code DOI

Experience

 
 
 
 
 
Neurolabs
Computer Vision Engineer
Dec 2021 – Present Edinburgh

Responsibilities include:

  • Implementing Deep Metric Learning approach to create a retail object detector
  • Using synthetic data & domain adaptation to improve performance with a small amount of real data
  • Staying up to date with the latest research, implementing most useful advancements
  • Deploying our solution with the use of FastAPI, PostgresSQL, GCP, Pinecone & Docker
 
 
 
 
 
Jagiellonian University
Research Assistant
Apr 2020 – Sep 2020 Cracow

Responsibilities included:

  • Conducting research
  • Conducting classes (NLP, probability and statistics)
 
 
 
 
 
Applica.ai
Deep Learning Specialist
Sep 2018 – Aug 2020 Cracow

Responsibilities included:

  • Conducting research on deep contextualized language models
  • Improving semantic search of documents
  • Implementing deep learning models that comprehend documents and answer questions about it
 
 
 
 
 
diCELLa
Deep Learning Engineer
Jul 2018 – Sep 2018 Cracow

Responsibilities included:

  • Using SOTA instance segmentation models on medical images
  • Tasks included segmenting keratinocytes and reticulocytes
 
 
 
 
 
CodiLime
Machine Learning Intern
Jul 2017 – Oct 2017 Warsaw

Responsibilities included:

  • CV: training SOTA object detection models
  • RL: training quadrotor in simulation, testing in the real world

Contact