Speakers

Our speaker lineup includes leading data scientists, software engineers, and machine learning researchers from international companies and both domestic and foreign universities who apply Deep Learning to real-world problems.

The list below is preliminary and subject to change.

Alphabetical list of speakers: 


Alfredo Canziani
NYU Courant Institute of Mathematical Sciences, USA

Alfredo Canziani is a Post-Doctoral Deep Learning Research Scientist and Lecturer at NYU Courant Institute of Mathematical Sciences, under the supervision of professors KyungHyun Cho and Yann LeCun. His research mainly focusses on Machine Learning for Autonomous Driving. He has been exploring deep policy networks actions uncertainty estimation and failure detection, and long term planning based on latent forward models, which nicely deal with the stochasticity and multimodality of the surrounding environment. Alfredo obtained both his Bachelor (2009) and Master (2011) degrees in EEng cum laude at Trieste University, his MSc (2012) at Cranfield University, and his PhD (2017) at Purdue University. In his spare time, Alfredo is a professional musician, dancer, and cook, and keeps expanding his free online video course on Deep Learning and Torch.

Krzysztof Geras
NYU School of Medicine, USA

Krzysztof is an assistant professor at NYU School of Medicine and an affiliated faculty at NYU Center for Data Science. His main interests are in unsupervised learning with neural networks, model compression, transfer learning, evaluation of machine learning models and applications of these techniques to medical imaging. He previously did a postdoc at NYU with Kyunghyun Cho, a PhD at the University of Edinburgh with Charles Sutton and an MSc as a visiting student at the University of Edinburgh with Amos Storkey. His BSc is from the University of Warsaw. He also did industrial internships in Microsoft Research (Redmond, working with Rich Caruana and Abdel-rahman Mohamed), Amazon (Berlin, Ralf Herbrich’s group), Microsoft (Bellevue) and J.P. Morgan (London). 

Xavier Giró
Universitat Politècnica de Catalunya, Spain

Xavier Giro-i-Nieto is an associate professor at the Universitat Politecnica de Catalunya (UPC) in Barcelona and visiting researcher at Barcelona Supercomputing Center (BSC). His obtained his doctoral degree from UPC in 2012 under the supervision of Prof. Ferran Marques (UPC) and Prof. Shih-Fu Chang (Columbia University). His research interests focus on deep learning applied to multimedia and reinforcement learning.
Home page: https://imatge.upc.edu/web/people/xavier-giro

Alexandr Kalinin
Shenzhen Research Institute of Big Data, China
University of Michigan, USA

Dr. Alexandr Kalinin is a PostDoctoral Research Fellow jointly at the University of Michigan and the Chinese University of Hong Kong, Shenzhen. He received his PhD in Bioinformatics at the University of Michigan in 2018. His PhD thesis focused on applications of statistical modeling, machine learning, and visual analytics to analyze morphological changes of cellular structures from 3D microscopic images. He holds BSc and MSc in Applied Math and Informatics from Novosibirsk State Technical University, Russia. In 2012-2013 Alexandr was a Fulbright Visiting Graduate Researcher at the University of California, Los Angeles, where he was designing and developing online statistical tools for interactive visual analytics and scientific data visualization. His current research is broadly focused on applications of machine learning and deep learning to the analysis of biomedical imaging data.


Krzysztof Kwaśniewski,
Google, Poland

Software engineer at Google, since 2017 has been developing both the internal and external Google Clouds. Presently focuses on robust, easily configurable and auto-renewed managed SSL certificates for Google Cloud Platform. He has been driving Managed Certificates for Google Kubernetes Engine (https://github.com/GoogleCloudPlatform/gke-managed-certs).

Previously Krzysztof was developing a business and market intelligence platform, IHS Connect, at IHS Markit. Thrilled to give a talk at Politechnika Gdańska, his Alma Mater.

Sebastian Raschka
University of Wisconsin-Madison, USA

Sebastian Raschka is an Assistant Professor of Statistics at UW-Madison focusing on machine learning and deep learning research (http://www.stat.wisc.edu/~sraschka/ ). Some of his recent research methods have been applied to solving problems in the field of biometrics for imparting privacy to face images. Other research focus areas include the development of methods related to model evaluation in machine learning, deep learning for ordinal targets, and applications of machine learning to computational biology. Among Sebastian’s other works is his book “Python Machine Learning,” which introduced people to the practical and theoretical aspects of machine learning around the globe with translations into German, Korean, Chinese, Japanese, Russian, Polish, and Italian. 


Alicja Kwasniewska,
SiMa.ai, USA
Gdansk University of Technology, Poland

Alicja graduated with distinction from Gdansk University of Technology, receiving Bachelor’s and Master’s Degree in Biomedical Engineering – Computer Science in Medicine. Her Master Thesis was conducted in cooperation with Norwegian University of Science and Technology in the area of signal and image processing, where she developed a platform for contactless monitoring of elderly people. This work has been frequently awarded in different contests, e.g. best diploma in the area of bioinformatics. As a Ph.D. candidate at Gdansk University of Technology, she is conducting the research in image processing using machine learning algorithms for remote healthcare. She also conducts a joint research in the field of neural networks with University of Texas, San Antonio. She has 8 years professional experience in computer vision gained while developing software for processing images from various sources (e.g. webcams, medical data, security cameras, etc.). For the past 3 years, she has been working on deep learning algorithms for servers monitoring, autonomous cars, smart home, and healthcare at Intel Corporation.

Jacek Ruminski
Gdansk University of Technology, Poland

Prof. Jacek Ruminski (Ph.D. in Computer Science, habilitation in Biocybernetics and Biomedical Engineering) is a head of Biomedical Engineering Department at GUT. He has spent about 2 years working on projects at different European institutions. He was a coordinator or an investigator in about 20 projects receiving a number of awards, including for best papers, practical innovations (7 medals and awards) and also the Andronicos G. Kantsios Award. Prof. Ruminski is the author of about 210 papers, and several patent applications and patents. Recently he was a main coordinator of the European eGlasses project focused on HCI using smartglasses. His research is focused on application of machine learning in healthcare.

Maciej Szankin
Intel AI Labs, USA

Maciej received M.Sc. in Computer Science in 2016 at the Department of Computer Architecture, Gdansk University of Technology. In his Master Thesis, he proposed methods for running machine learning algorithms in the distributed environment. His work focuses on leveraging hardware accelerators for improving deep learning workloads in constrained and mission-critical environments. Many of his solutions have been published in journals and presented during IEEE conferences, and has received best paper award and best young professional paper award.