WOMEN IN TECH RUSSIA
Data Science Online Conference
26th September 10:00 CET
MEET OUR SPEAKERS
Ekaterina Kondrateva
PhD Student Skoltech
It is my fifths-year in the field of data analysis, of which I worked for a couple of years in Tel Aviv predicting for the agro-industrial sector. Now at Skoltech, I am engaged in the study of medical images and the development of algorithms for cobrain.ai. Also, medical image analysis is my PhD thesis topic, you can find more on github.com/kondratevakate. Apart from academia, I teach machine learning on additional educational programs at Skoltech and HSE.
Noa Weiss
 Data Science & Machine Learning Consultant
Noa is a data science & machine learning consultant who’s been playing with data for nearly a decade. Prior to freelancing, Noa explored the world of risk & security, working for companies such as Armis and PayPal, as well as consulting startups on fraud prevention.
Noa also leads the Israeli community of Women in Data Science, works at the Deep Voice Foundation for whale research, and mentors junior data scientists taking their first steps in the field.
Anna Aljanaki
Data Scientist and Lecturer
Dr. Anna Aljanaki is a researcher in the field of music information retrieval, a data scientist and a lecturer at the University of Tartu. She worked in research institutions (Utrecht University, University of Geneva, Johannes Kepler University Linz) on topics of music emotion recognition, music categorization and description, music generation. She also worked as a data scientist in STACC, Mooncascade, and currently, Datafruit.
Aelita Shaykhutdinova
Data Scientist
Aelita has recently finished her education as a bachelor at Innopolis University. She is working at EORA Data Lab and mainly focused on Computer Vision and Deep Learning. At the beginning of her career, she has already solved a variety of problems such as segmentation of humans and their parts, classifying diseases on chest x-ray images, anomaly detection on images, real-time face detection, landmarks localization, and others.
Valeriy Babushkin
Senior Director of Data Science at X5 Retail Group
Valeriy Babushkin is the Senior Director of Data Science at X5 Retail Group where he leads a team of 100+ people. Also, Valeriy is a Kaggle competition Grand Master; ranking globally in the top 30. He was 23th in global ratings of ML specialists (https://www.kaggle.com/venheads).
Polina Polunina
Data Science Expert
Polina is an expert in Analytics and ML with 10+ years of experience. Used to work in quantitative finance, product analytics, machine learning. Ex head of the Data Science division of HR, Finance, and Video analytics at M.Video-Eldorado, а visiting lecturer on Machine Learning at HSE University, the winner of several worldwide Data Analysis championships.
Rajasekhar Nannapaneni
Dell Technologies, Consultant Solutions Architect
Rajasekhar Nannapaneni comes with 15+ years of experience in the IT/Software industry and is specialized in storage, servers and operating systems.
As a Consultant Solutions Architect he works closely with customers, delivering enterprise storage based services. He is also passionate about upcoming technologies such as Machine Learning, AI and Quantum Computing and has authored papers in the areas of artificial neural networks, computational intelligence and pattern recognition.
CONFERENCE SCHEDULE
26 September 2020
10:00 (CET)
10:00 (CET)
Greeting Speech
Elina Valeeva, CEO & Founder of Meditivity / Women in Tech ambassador
Ksenia Matveeva, Dell Technologies, Innovation programs manager
10:10 (CET)
10:10 (CET)
Machine Learning in Medical Imaging: who’s in charge?
Ekaterina Kondrateva, PhD Student Skoltech
Who is in charge? We are going to discuss the decision-making process inside the ML diagnostic tools as well as medical policies around the AI systems. I will share my experience in building MRI-based models that can support the decision-making process of a doctor. We will discuss the current state-of-the-art solutions and think about the moral and legal responsibilities that come with AI applications in medicine. A bit of philosophy, Big Data, Computer Vision - a standard kit for any ML practitioner. Vision, Artificial Intelligence - a standard set for any medical ML practitioner.
11:10 (CET)
11:10 (CET)
10 Machine Learning Concepts Every Startup Founder Must Know
Noa Weiss, Data Science & Machine Learning Consultant
Do you often find yourself in meetings with obscure machine learning terms thrown all around you, and no idea what they mean? There is hope yet. Designed for tech professionals, this talk introduces 10 must-know concepts in ML, giving you the basic tools to better understand the work around you. Rock the next water cooler chat with your newfound knowledge of these fundamentals of machine learning.
12:10 (CET)
12:10 (CET)
The magic behind your playlist
Anna Aljanaki, Data Scientist and Lecturer
Have you ever wondered how does YouTube always know that a song is copyrighted? What sort of magic are music streaming services doing to organize your music? Or even where is that service that you can use to find a song that's stuck in your head? In this talk I'll explain some of the techniques used to do these tricks. We will get acquainted with the field of music information retrieval, its challenges and toolset.
12:50 (CET)
12:50 (CET)
Plants weighting based on camera footage
Aelita Shaykhutdinova, Data Scientist
Have you ever wondered what it takes to get a fresh salad on your table, how this process can be improved in terms of ecology, time and money spent. In this topic we will cover how Data Science can help in achieving the goals. In particular, how we did plant weighting based on camera footage using computer vision methods.
13:40 (CET)
13:40 (CET)
Why do we need Data Science for the Largest Food Retailer in Russia
Valeriy Babushkin, Senior Director of Data Science at X5 Retail Group
X5 Retail Group, with more than 17000 stores is the largest food retailer in Russia. In 2 years the Data Science team grew up from five to more than a hundred people and Big Data in total from twenty to five hundred. Why do we need so many Data Scientist and what we do them? Pay attention to this talk and you will find out.
14:30 (CET)
14:30 (CET)
Can we make machines understand human emotions
Rajasekhar Nannapaneni, Dell Technologies, Consultant Solutions Architect
This talk starts with a basic overview of Machine Learning and Deep Learning along with insights on how they differ. We will then cover one of the use cases of human emotion recognition using Machine Learning techniques and it’s applicability.
15:40 (CET)
15:40 (CET)
DS career during the crisis (feat. all speakers)
Polina Polunina, Data Science expert
The global industry outlook during COVID-19: how the pandemic has changed work and hiring processes both in business and science? What's happened to the data science job market? Are there bounds to hire talents from non-residence geographical regions? How did business vectors change during COVID? How did it affect regural tasks for a data scientist? Career perspectives, business challenges, personal failures and successes will be discussed with top industry and academy professionals.
ORG TEAM
Elina Valeeva
Women in tech Russia Ambassador
Dilyara Saetova
Women in tech Russia Administrative coordinator
Ksenia Matveeva
Dell Technologies, Innovation programs manager
Anna Aksenova
Conference organization and coordination
Vera Novikova
Website Development and Tech Support
Lidia Timkovskaya
Women in tech Corporate relationships
Polina Polunina
Women in tech Corporate relationships
WIT VIDEOS
CONTACT US
womenintechrus@gmail.com
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