IT Weekend Ukraine 2018 & Ukrainian IT Awards 2018

2018 Sep 08
16a Parkova Rd, Kyiv, Ukraine
Convention & Exhibition Centre PARKOVY
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About conference

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IT Weekend comes back to facilitate the discussions around the evolving trends and emerging technologies and their impact on a the future of the IT industry.

This year’s conference aims to highlight the latest innovations in the areas of Artificial Intelligence, Big Data and Data Science, Cloud technologies, Security and Blockchain industries with the world-class presenters and over 1000 participants in this unique event.

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6+

years

15+

speakers

1000+

attendees
Program

Program

Stream 1

Stream 2

Stream 1

Stream 2

08:00 09:00

Registration

09:00 09:15

Welcome speech from Chris Baker, CEO, SoftServe

Serverless For the Enterprise

Language ENG

Forrest Brazeal

Senior cloud architect at Trek10

Forrest is a senior cloud architect at Trek10, Inc, an AWS Advanced Consulting Partner that specializes in serverless solutions. Prior to joining Trek10, Forrest spent several years leading serverless and AWS projects at Infor. He understands the challenges faced by enterprises moving to the cloud and loves building solutions that provide maximum business value for minimal cost. Forrest hosts the “Think FaaS” serverless podcast at Trek10 and contributes to their open source efforts. Outside of his day job, he interviews the top names in cloud for his “Serverless Superheroes” series at A Cloud Guru and also creates the “FaaS and Furious” webcomic. He is heavily involved with ServerlessConf and regularly speaks at workshops and other events in the serverless community. Forrest holds a master’s degree in computer science from Georgia Tech and is an AWS Certified Solutions Architect — Professional. more

Research to Industry: Deep Learning gray boxes & rabbit holes

Deep Learning is now at the core of many industrial applications. This, preceded by an inevitable hype, has sparked a trend advocating rigor, interpretability and reproducibility. How does one open the so-called black box and enable scientists, engineers and all those inbetween to work together and make products powered by Neural Networks a success? What specific steps can be taken from the very beginning?

Deep Learning is now at the core of many industrial applications. This, preceded by an inevitable hype, has sparked a trend advocating rigor, interpretability and reproducibility. How does one open the so-called black box and enable scientists, engineers and all those inbetween to work together and make products powered by Neural Networks a success? What specific steps can be taken from the very beginning?

Irina Vidal Migallón

Computer Vision & Machine Learning engineer at Siemens Mobility

Irina is a Computer Vision and Deep Learning engineer with a past in Electrical and Biomedical engineering. Seasoned in different industries. She has enabled machine vision products from medical imaging devices at INRIA (France) and surgical planning tools or Virtual and Augmented Reality systems in German start-ups. She is now part of the Computer Vision & AI team in Siemens Mobility. Even more than waking up Skynet, she’s interested in the limits of Natural Intelligence and its decisions over our data. more

VR/AR adoption has been slower than predicted, what will really drive it forward?

Much emphasis has been placed on when VR & AR will go mainstream whilst only really concentrating on the devices themselves. Immersive enterprise training solutions need acceleration in many conceptual areas simultaneously to drive growth and enable services to meet requirements, including cloud AR & VR, 5G, blockchain and more. Discussing unique insights and outcomes from the products Make Real has delivered over the past decade, find out lessons learned and how they are shaping product delivery towards scalable solutions built upon disruptive technologies, that will be commonplace within the next couple of years.

Much emphasis has been placed on when VR & AR will go mainstream whilst only really concentrating on the devices themselves. Immersive enterprise training solutions need acceleration in many conceptual areas simultaneously to drive growth and enable services to meet requirements, including cloud AR & VR, 5G, blockchain and more. Discussing unique insights and outcomes from the products Make Real has delivered over the past decade, find out lessons learned and how they are shaping product delivery towards scalable solutions built upon disruptive technologies, that will be commonplace within the next couple of years.

Sam Watts

Director of Immersive Technologies @MakeRealVR

Sam is actively engaged in the immersive technology community, living his passion for VR and games. Focused on delivery and deployment of Make Real products, he ensures that Make Real’s production teams are fully aligned with customer needs and that quality is assured. In previous leadership roles, Sam has delivered and supported dozens of digital products at Zynga, NCsoft, Kerb and Epic. Clients have included BBC, Channel 4, EDF Energy, McDonald’s, Sky and Sony PlayStation. Sam’s commitment to the VR community means that he is an in-demand panelist and commentator on the emergence of VR. Maintaining close relationships with industry leaders such as Oculus, HTC/Valve and Sony, Sam also ensures that Make Real has early access to all key emerging technologies. more

Deep Learning Atlas

What are neural networks? What makes them recurrent or convolutional? This talk will give you an introduction to and a whirlwind tour of the field of Deep Learning. We’ll start by explaining how simple artificial neural networks work and how they learn (with a minimum of math, I promise). We’ll then go over different network architectures used in computer vision, sequence analysis, neural machine translation and other areas. I’ll also show you how easy it is to get started using PyTorch. Lieutenant Commander Data, the android in Star Trek, famously had a positronic network for his brain. I’m not sure how positrons fit in the picture, but just like sliding doors and portable Padd computers, the networks from Data’s brain are coming into existence in our reality. Current Artificial Neural Networks are already quite capable of recognizing objects in images, composing speech, even basic reasoning. So what was Data’s brain composed of? Convolutional neural networks (CNNs) scan images and are able to detect objects and recognize them, perhaps Data’s eyes had some similar structure. Recurrent neural networks (RNNs) are quite capable of understanding and composing sequences of words to make sentences and sequences of sounds to make speech. An android’s language center would probably have a recurrent structure as well. Commander Data was also very artistic as a painter and composer of music, we see that generative adversarial networks (GANs) can also do these things. We will briefly talk about how all these different types of artificial neural networks work, how we can use them today and perhaps how they will be used in the distant future.

What are neural networks? What makes them recurrent or convolutional? This talk will give you an introduction to and a whirlwind tour of the field of Deep Learning. We’ll start by explaining how simple artificial neural networks work and how they learn (with a minimum of math, I promise). We’ll then go over different network architectures used in computer vision, sequence analysis, neural machine translation and other areas. I’ll also show you how easy it is to get started using PyTorch. Lieutenant Commander Data, the android in Star Trek, famously had a positronic network for his brain. I’m not sure how positrons fit in the picture, but just like sliding doors and portable Padd computers, the networks from Data’s brain are coming into existence in our reality. Current Artificial Neural Networks are already quite capable of recognizing objects in images, composing speech, even basic reasoning. So what was Data’s brain composed of? Convolutional neural networks (CNNs) scan images and are able to detect objects and recognize them, perhaps Data’s eyes had some similar structure. Recurrent neural networks (RNNs) are quite capable of understanding and composing sequences of words to make sentences and sequences of sounds to make speech. An android’s language center would probably have a recurrent structure as well. Commander Data was also very artistic as a painter and composer of music, we see that generative adversarial networks (GANs) can also do these things. We will briefly talk about how all these different types of artificial neural networks work, how we can use them today and perhaps how they will be used in the distant future.

Language ENG

Michał Karzyński

Software Engineer, Intel AI

Michal Karzynski has a scientific research background in the areas of molecular biology and bioinformatics. He is currently working as a Machine Learning software engineer, tech lead and consultant. He also has web development experience and spent many years writing code in Python and JavaScript. Michal loves Linux and everything open source. He’s currently working on nGraph, Intel’s runtime and graph compiler for Deep Learning.  He wrote “Webmin Administrator’s Cookbook”, a book on Linux server administration. As consultant he was responsible for designing and deploying cloud infrastructure for a number of companies. Michal is currently employed as a tech lead at Intel. He also runs the consulting company Atarnia.com. He writes a blog, which can be found at http://michal.karzynski.pl more

AI Is the Solution for Everything? Stories of Self-Experienced Failed AI Applications and What We Can Learn from Them

This talk is heavily inspired by the “Fuckup-Night” format. Instead of praising the success stories, in this format stories of failures and “fuckups” are told. What might look as pure entertainment at first glance turns out to be highly informative. Quite often we can learn even more from failures than from success stories. In the current AI hype, we always hear the success stories, be it from Google, Uber or Amazon. In this talk I will share with you the stories of failed AI applications I experienced so far in my six years of being a data scientist. There will be stories from different fields, retail, insurance, industry and various different applications, from predictive maintenance to churn management. So, all the AI hype is crap? No, in the contrary! There are, and there will be even more AI success stories in future, just it is not always that simple as it might look like on marketing slides. That is why I will point you to the common patterns that eventually lead to a failure of these AI applications so that you can avoid falling in the same traps. I hope I will be able to teach you something about statistics and business politics, at the least you will hear some exclusive witty anecdotes!

This talk is heavily inspired by the “Fuckup-Night” format. Instead of praising the success stories, in this format stories of failures and “fuckups” are told. What might look as pure entertainment at first glance turns out to be highly informative. Quite often we can learn even more from failures than from success stories. In the current AI hype, we always hear the success stories, be it from Google, Uber or Amazon. In this talk I will share with you the stories of failed AI applications I experienced so far in my six years of being a data scientist. There will be stories from different fields, retail, insurance, industry and various different applications, from predictive maintenance to churn management. So, all the AI hype is crap? No, in the contrary! There are, and there will be even more AI success stories in future, just it is not always that simple as it might look like on marketing slides. That is why I will point you to the common patterns that eventually lead to a failure of these AI applications so that you can avoid falling in the same traps. I hope I will be able to teach you something about statistics and business politics, at the least you will hear some exclusive witty anecdotes!

Sebastian Neubauer

Senior Data Scientist at Blue Yonder GmbH

Sebastian joined Blue Yonder as a Data Scientist after completing his PhD in physics. One of the first things Sebastian learned on the job is that it takes a lot more than just software and algorithms to deliver value to customers. Realizing this, he focused his efforts on configuration management and application life cycle management as well as the design, development and operation of distributed systems. He is now a Senior Data Scientist at Blue Yonder and contributed already in nearly all layers, from infrastructure to algorithms. more

Machine Learning Design, Demystified...

Once available only to scientists, today machine learning (ML) is open to a much broader audience of software architects and engineers. In fact, the practice of ML is so advanced that some algorithm results look like "black magic,” even to experienced practitioners. Inspired by attribute-driven design (ADD) and Smart Decisions (a software architecture design game for big data), our speakers are excited to share a new version of the game focused on designing ML systems. In this interactive session, you will learn about designing the architecture for ML systems via series of gamified interactive exercises. We will simulate state-of-the-art ML design systems by analyzing both business and technical requirements, selecting the best matching algorithms, and teaching how to validate early design decisions using rapid prototyping techniques.

Once available only to scientists, today machine learning (ML) is open to a much broader audience of software architects and engineers. In fact, the practice of ML is so advanced that some algorithm results look like "black magic,” even to experienced practitioners. Inspired by attribute-driven design (ADD) and Smart Decisions (a software architecture design game for big data), our speakers are excited to share a new version of the game focused on designing ML systems. In this interactive session, you will learn about designing the architecture for ML systems via series of gamified interactive exercises. We will simulate state-of-the-art ML design systems by analyzing both business and technical requirements, selecting the best matching algorithms, and teaching how to validate early design decisions using rapid prototyping techniques.

Serge Haziev

VP Technology Services Group, SoftServe

Serge has more than 18 years’ experience in designing, evaluating and modernizing large scale software architectures in various technology domains including BI, Big Data, Clouds, SOA and Carrier-grade telecommunication services for both Fortune 100 and startups. more

Iurii Milovanov

Data Science Practice Leader, SoftServe

Iurii has more than 8 years’ experience in enterprise-level solutions including Big Data, data mining, and information security. He specializes in scientific and algorithmic approaches to solving various business tasks using state-of-the-art AI techniques, such as deep learning, computer vision, natural language processing, and speech recognition. more

18:30 19:30

Prize Drawings

19:30 20:30

Ukrainian IT Awards 2018

Awarding ceremony

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Prices

Prices

$79
10.05-19.07
Early Birds
$99
20.07-20.08
Regular
$119
21.08
Hot Birds
25% goes to charity

This year, IT Weekend Ukraine is raising money for a good cause with 25% of the ticket price going to a charity initiative.

Money raised will go to SoftServe Charity Fund “Open Eyes” to implement a project ‘Positive rooms’. This is a special bright place for kids who undergo treatment in hospitals. The aim of the project is to create positive space with games, books, toys, creative and educational materials. This is the room where kids can forget about being patients for a while, just smile and have fun.

Charity Fund “Open Eyes” founded in 2014 has been implementing social, educational, cultural and infrastructure projects. To find more information about the Fund please visit website.

Speakers

Speakers

Director of Immersive Technologies @MakeRealVR

Sam Watts

Director of Immersive Technologies @MakeRealVR

Sam Watts

Sam is actively engaged in the immersive technology community, living his passion for VR and games. Focused on delivery and deployment of Make Real products, he ensures that Make Real’s production teams are fully aligned with customer needs and that quality is assured. In previous leadership roles, Sam has delivered and supported dozens of digital products at Zynga, NCsoft, Kerb and Epic. Clients have included BBC, Channel 4, EDF Energy, McDonald’s, Sky and Sony PlayStation. Sam’s commitment to the VR community means that he is an in-demand panelist and commentator on the emergence of VR. Maintaining close relationships with industry leaders such as Oculus, HTC/Valve and Sony, Sam also ensures that Make Real has early access to all key emerging technologies.

VP Technology Services Group, SoftServe

Serge Haziev

VP Technology Services Group, SoftServe

Serge Haziev

Serge has more than 18 years’ experience in designing, evaluating and modernizing large scale software architectures in various technology domains including BI, Big Data, Clouds, SOA and Carrier-grade telecommunication services for both Fortune 100 and startups.

Senior cloud architect at Trek10

Forrest Brazeal

Senior cloud architect at Trek10

Forrest Brazeal

Forrest is a senior cloud architect at Trek10, Inc, an AWS Advanced Consulting Partner that specializes in serverless solutions. Prior to joining Trek10, Forrest spent several years leading serverless and AWS projects at Infor. He understands the challenges faced by enterprises moving to the cloud and loves building solutions that provide maximum business value for minimal cost. Forrest hosts the “Think FaaS” serverless podcast at Trek10 and contributes to their open source efforts. Outside of his day job, he interviews the top names in cloud for his “Serverless Superheroes” series at A Cloud Guru and also creates the “FaaS and Furious” webcomic. He is heavily involved with ServerlessConf and regularly speaks at workshops and other events in the serverless community. Forrest holds a master’s degree in computer science from Georgia Tech and is an AWS Certified Solutions Architect — Professional.

Data Science Practice Leader, SoftServe

Iurii Milovanov

Data Science Practice Leader, SoftServe

Iurii Milovanov

Iurii has more than 8 years’ experience in enterprise-level solutions including Big Data, data mining, and information security. He specializes in scientific and algorithmic approaches to solving various business tasks using state-of-the-art AI techniques, such as deep learning, computer vision, natural language processing, and speech recognition.

Computer Vision & Machine Learning engineer at Siemens Mobility

Irina Vidal Migallón

Computer Vision & Machine Learning engineer at Siemens Mobility

Irina Vidal Migallón

Irina is a Computer Vision and Deep Learning engineer with a past in Electrical and Biomedical engineering. Seasoned in different industries. She has enabled machine vision products from medical imaging devices at INRIA (France) and surgical planning tools or Virtual and Augmented Reality systems in German start-ups. She is now part of the Computer Vision & AI team in Siemens Mobility. Even more than waking up Skynet, she’s interested in the limits of Natural Intelligence and its decisions over our data.

Senior Data Scientist at Blue Yonder GmbH

Sebastian Neubauer

Senior Data Scientist at Blue Yonder GmbH

Sebastian Neubauer

Sebastian joined Blue Yonder as a Data Scientist after completing his PhD in physics. One of the first things Sebastian learned on the job is that it takes a lot more than just software and algorithms to deliver value to customers. Realizing this, he focused his efforts on configuration management and application life cycle management as well as the design, development and operation of distributed systems. He is now a Senior Data Scientist at Blue Yonder and contributed already in nearly all layers, from infrastructure to algorithms.

Software Engineer, Intel AI

Michał Karzyński

Software Engineer, Intel AI

Michał Karzyński

Michal Karzynski has a scientific research background in the areas of molecular biology and bioinformatics. He is currently working as a Machine Learning software engineer, tech lead and consultant. He also has web development experience and spent many years writing code in Python and JavaScript. Michal loves Linux and everything open source. He’s currently working on nGraph, Intel’s runtime and graph compiler for Deep Learning.  He wrote “Webmin Administrator’s Cookbook”, a book on Linux server administration. As consultant he was responsible for designing and deploying cloud infrastructure for a number of companies. Michal is currently employed as a tech lead at Intel. He also runs the consulting company Atarnia.com. He writes a blog, which can be found at http://michal.karzynski.pl

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