About Conference

GHOST Day returns in 2020!

Many of you loved last year’s edition of our conference. This time, we would like to expand on our schedule in order to bring even more data science to the eyes and ears of our participants. We’ve planned two whole days for the talks, so everyone will find enough for themselves. As before, multiple presentations of top-tier specialists in various branches like computer vision and natural language processing will be held in parallel sessions, in between which you will get the chance to speak with other data science enthusiasts and exchange experience.

Due to the pandemic, this year’s edition can’t be held in Poznań. We regret that meeting you all in person is not possible. Fortunately, we’re happy to announce that all our participants will be able to gather online. We want to make the experience as real as possible, so things like Speaker Q&As, lunch break discussions, and gadget-boxes for participants are all here! Our Speakers once again surprised us with captivating ideas for the talks, which you can read below.

Don’t wait, and register now for the machine learning experience you’ve been waiting for!

LEARN MORE
Conference Date

23-24 October 2020

Our Speakers

Who’s speaking

Participate

Registration

The registration of participants lasted until October, 16th and is now closed.
If you have registered during the open registration period (first 300 tickets), you are automatically & successfully registered for the conference. No additional confirmations or decisions will be sent to you. Regarding the selective process: every applicant should receive an email with a final decision. Unfortunately, we learned that some applicants did not receive our email due to SPAM filters. If for some reason you have not received an email from us, please contact us to learn about the status of your application. We are sorry for the inconvenience.

Our Timetable

Agenda

Day 1 (23.10.) Day 2 (24.10.)
10:00 – 10:15 Conference opening Opening of 2nd day
10:15 - 11:15 Keynote lecture 1: Unsupervised representation learning with deep neural networks (Piotr Bojanowski, Facebook AI Research) Keynote lecture 3: The 7 Habits of Highly Effective ML Practitioners (Karol Kurach, Cosmose)
11:15 - 11:30 Coffee break (ML in Medicine; prof. n. med. Andrzej Grzybowski) Coffee break (Quiz)
11:30 – 13:00 Session 1: NLP
This session is sponsored by Allegro
Session 2: Computer Vision Session 3: General ML Session 7: ML in Cybersecurity
This session is sponsored by F-Secure
Session 8: Business Intelligence Session 9: ML Methodology
13:00 - 14:30 Lunch break (Future of AI; Michał Giełda, Antmicro & prof. Jerzy Stefanowski) Lunch break (Managing ML Projects; Ireneusz Gawlik, Allegro & Krzysztof Jędrzejewski, Pearson)
14:30 - 15:30 Keynote lecture 2: Brain-inspired computing (Stanisław Woźniak, IBM Research - Zurich)Keynote lecture 4: On Deep Learning of Sets (Adam Kosiorek, Google DeepMind)
15:30 - 15:45 Coffee break (ML start-ups; Jan Mizgajski) Coffee break (ML in Cybersecurity; dr Marcin Kowiel, F-Secure)
15:45 – 17:15 Session 4: NLP Session 5: Computer Vision
This session is sponsored by Pearson
Session 6: Sensors & Embedded Session 10: ML in Medicine Session 11: ML Applications Session 12: Student Session
17:15 - 18:30 Poster session Closing session

Conference Sessions

Recent advancements in adversarial speech synthesis

by Mikołaj Bińkowski | Google DeepMind

11:30-12:30

Virtual room 1

View More
What does the user ask for? - Discovering new intents in conversational data

by Piotr Rybak | Allegro

12:30-13:00

Virtual room 1

View More
How to build a deep learning-based system for precise pose estimation in sports in 3 months?

by Wojciech Rosinski | ReSpo.Vision

11:30-12:00

Virtual room 2

View More
Image Classification in Mixed Martial Arts - Recognition of fighting techniques

by Mateusz Maj | OLX Group

12:00-12:30

Virtual room 2

View More
Multi-object tracking of people in surveillance videos

by Artur Zygadło | deepsense.ai

12:30-13:00

Virtual room 2

View More
Enhancing machine learning algorithms with a human-in-the-loop approach

by Adam Gonczarek | Alphamoon

11:30-12:00

Virtual room 3

View More
Extreme classification: applications and algorithms

by Marek Wydmuch | OLX Group/Poznan University of Technology

12:00-12:30

Virtual room 3

View More
Batch construction strategies in deep metric learning

by Bartosz Ludwiczuk & Kalina Kobus | Allegro

12:30-13:00

Virtual room 3

View More
Delivering FastPitch: A Major League, Parallel Text-to-speech Model

by Adrian Łańcucki | NVIDIA

15:45-16:45

Virtual room 1

View More
Challenges of commercializing language models on mobile devices

by Szymon Łęski | Allegro

16:45-17:15

Virtual room 1

View More
Machine learning in fashion industry - intelligent clothes swapping

by Patryk Miziuła | deepsense.ai

15:45-16:15

Virtual room 2

View More
SmogSpots. How machine learning may help us to solve smog issue?

by Kacper Łukawski | AI Embassy

16:15-16:45

Virtual room 2

View More
Let the Product Lead: R&D Paradigms for Recognition Models of Handwritten Math Expressions

by Quinn Lathrop | Pearson

16:45-17:15

Virtual room 2

View More
Developing and testing TensorFlow Lite edge AI algorithms without need for hardware using Renode

by Michael Gielda | Antmicro

15:45-16:15

Virtual room 3

View More
Radar data analysis and classification in practice: tips & tricks

by Joanna Piwko & Sylwana Kaźmierska | Digica

16:15-16:45

Virtual room 3

View More
The future of machine learning in autonomous cars

by Maciej Dziubinski | Equinix

16:45-17:15

Virtual room 3

View More
Where do the adversarial examples come from?

by Marcin Mosiolek | EY GDS Poland

11:30-12:00

Virtual room 1

View More
Building NLP toolbox for cybersecurity. Language model for command lines

by Julia Będziechowska | F-Secure

12:00-12:30

Virtual room 1

View More
Fighting ransomware with Machine Learning - zero-day ransomware detection at Egnyte

by Wojciech Mikołajczyk | Egnyte

12:30-13:00

Virtual room 1

View More
Transforming Data into Decisions

by Zbigniew Michalewicz | Complexica

11:30-12:00

Virtual room 2

View More
Document Intelligence - Natural Language Processes Challenges and Solutions

by Adam Karwan | EY GDS Poland

12:00-12:30

Virtual room 2

View More
Advances in neural network information retrieval

by Czeslaw Jedrzejek | Poznan University of Technology

12:30-13:00

Virtual room 2

View More
How to Invent: From Probability Theory to Expressive Text-To-Speech.

by Daniel Korzekwa | Amazon TTS-Research

11:30-12:30

Virtual room 3

View More
The 21st century approach to ML

by Grzegorz Mrukwa | Netguru

12:30-13:00

Virtual room 3

View More
Kidney tumor malignancy prediction: How deep learning can save 8 out of 10 kidneys.

by Aleksander Obuchowski | Radiato.ai/Gdańsk Universtity of Technology

15:45-16:15

Virtual room 1

View More
Explainable deep neural networks for medical image analysis

by Krzysztof Geras | New York University

16:15-17:15

Virtual room 1

View More
Application of Generative Query Networks for industrial time series

by Grzegorz Miebs & Rafał A. Bachorz | PSI Polska

15:45-16:15

Virtual room 2

View More
(Many shades of) ML @ Allegro.pl: NLP, Vision & ranking at the largest Polish e-commerce marketplace

by Przemysław Pobrotyn | Allegro

16:15-16:45

Virtual room 2

View More
Natural Language Processing with Deep Learning and TensorFlow

by Barbara Fusińska | Google

16:45-17:15

Virtual room 2

View More
Explaining the unexplainable - can we depend on what we don’t understand?

by Zuzanna Trafas | GHOST

15:45-16:15

Virtual room 3

View More
Changing the future with probabilistic models

by Dariusz Max Adamski | GHOST

16:15-16:45

Virtual room 3

View More
Attention-based approach to malware classification

by Piotr Wyrwiński | GHOST

16:45-17:15

Virtual room 3

View More

Partners & Sponsors

Honorary Patronage

Official Sponsors

Platinum
Gold
Silver

Media Partners