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OUR SPEAKERS
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My name is Noa Lubin, nominated in Israel Forbes 30 Under 30 list.
I am the Director of Data Science at Fido and I am interested in any do-good AI. I love public speaking and teaching data science and I am a part of Y-data faculty. I previously worked at: Diagnostic Robotics, NASA, Amazon, Elbit and IAI. I completed a Computer Science Master's degree at Bar-Ilan University with an NLP thesis and an Electrical Engineering Bachelor's degree at the Technion. I am also the proud Founder and Chair of the Board of Hydrocephalus Association Israel.
Noa Lubin
Director of AI & Data
English, Hebrew, French
Languages:
Location:
Kiryat Ono, Israel
Can also give an online talk/webinar
Paid only. Contact speaker for pricing!
MY TALKS
Latest Trends in NLP
Data / AI / ML
In this lecture, we will discuss the latest trends in Natural Language Processing.
The NLP field evolved into the world of Machine Learning and lately to complex sequential Deep Learning models.
This development leads to amazing tools that are capable of solving different problems such as: text generation, machine translation, language understanding and more. We will see the technology, its capabilities and limitations.
We will also talk about the strong ethical issues these tools bring, such as fairness among minority groups and fake news.
Harnessing Data to Improve Healthcare
Data / AI / ML, Innovation
In this talk, you will learn how we create detailed insights from different sources of medical data at Diagnostic Robotics. We will discuss the challenges of working with claims data, a form of health-related administrative data, to build predictive and proactive models. The talk will also cover the concept of causal machine learning and its unique use to emulate randomised controlled trials. Join us to understand how we at Diagnostic Robotics are building models that benefit the patients and help to dramatically reduce the cost of healthcare around the world.
Big Data Small Planets
Data / AI / ML, Innovation
TESS, Transiting Exoplanet Survey Satellite, is a critical mission to increase our understanding of earth-like planets outside our solar system. TESS will survey 100,000s of the brightest stars near us to search for exoplanets, planets outside our solar system. TESS will achieve this by looking for transits. Manual classification of transits is very challenging and time consuming. Thus, we need machine classification systems to automatically determine whether a transit indicates an exoplanet or not. In this talk we will talk about TESS and former mission Kepler, NASA, exoplanets and the use of deep learning methods to identify them.
Aligning Vector-spaces with Noisy Supervised Lexicons
Data / AI / ML, Innovation
This talk was given at NAACL 2019. The problem of learning to translate between two vector spaces given a set of aligned points arises in several application areas of NLP. Cur- rent solutions assume that the lexicon which defines the alignment pairs is noise-free. We consider the case where the set of aligned points is allowed to contain an amount of noise, in the form of incorrect lexicon pairs and show that this arises in practice by analysing the edited dictionaries after the cleaning process. We demonstrate that such noise substantially degrades the accuracy of the learned translation when using current methods. We propose a model that accounts for noisy pairs. This is achieved by introducing a generative model with a compatible iterative EM algorithm. The algorithm jointly learns the noise level in the lexicon, finds the set of noisy pairs, and learns the mapping be- tween the spaces. We demonstrate the effectiveness of our proposed algorithm on two alignment problems.
When Life Meets Your Career
Inspirational
Remember the movie Titanic? Just like an ocean glacier there are some things are more than what meets the eye. In this open talk you will hear how to continue and evolve in your career alongside a personal challenge and uncertainty. You will feel you’re not alone, many powerful women, even the ones speaking to you at GHC went trough or are going trough a personal challenge.
Ethics in NLP
Data / AI / ML, Innovation
We will discuss the importance of ethics and fairness in artificial intelligence and specifically in NLP. We'll suggest methods to evaluate fairness and basic methods to improve our model fairness. We'll discuss the most common methods for NLP embedding de-biasing and the latest research in recent years and state of the art in NLP de-biasing.
The Initiative Behind Opportunity
Inspirational, Innovation, Women in Tech, Soft Skills
"When opportunity knocks, say yes." What if I told you saying "yes" is only where it ends, and you should strive to create and identify your own opportunities? In this session, we'll talk about what an opportunity is in our career, why it is good for our career, and how we can identify and create opportunities in our day-to-day activities.
The Closest I Got to Mars
Inspirational, Innovation
We'll learn about D-mars - home for space exploration, where Noa volunteer as an analog astronaut or what we call “Ramonaut” At D-mars we take a small part in the giant journey to Mars exploration! We develop technologies, scientific methods and human knowledge and skills for human and robotic space exploration, by execution of analog space missions. You’ll hear more about what we do at D-mars and from my isolation experience.
X-AI
Data / AI / ML
Advanced machine learning based products are a part of you everyday-life also in advanced domains such as healthcare. Therefore understanding the decision behind the ML-based model is key to have users gain trust in the model, debug the model, discover biases and more. Providing explanations to the AI-black box models poses a great challenge. We'll discuss some of the most common model-agnostic methods for explainable AI (X-AI): Global Surrogate, LIME, SHAP and counter-factual explanations and explain how each one provides explanation to black box models and the tradeoffs between the methods. This talk assumes previous DS knowledge.
When Data Scientist Get It Wrong
Data / AI / ML
What are the most common mistakes data scientist make? We'll go over use cases and understand the common mistakes to avoid that will set you apart from a junior Data Scientist to a pro!
Once Upon a Data
Data / AI / ML, Soft Skills
As data experts a part of our role is data storytelling. A Good data story is measure by the influence you had on decision making. The main components of a data story are: the data, the narrative and the visualization. A great data story is simple, relevant, credible and engaging.
We will understand the impact of data storytelling, understand the important tips and flow for a great data story. Later we will focus on visualisations and how they can complete a great data story.
After this workshop you'll receive the tools to become a great data story teller.
Keeping Watch: Effective Strategies for Machine Learning Model Monitoring
Data / AI / ML
We will delve into the essential aspects of monitoring machine learning models in production. We will discuss the key components of effective model monitoring, including the monitoring metrics pyramid, establishing control groups, and implementing A/B testing frameworks. Through practical examples and case studies, we will highlight the importance of continuous monitoring in ensuring model performance, reliability in real-world environments.
Latest Trends in NLP
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Harnessing Data to Improve Healthcare
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Big Data Small Planets
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Aligning Vector-spaces with Noisy Supervised Lexicons
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When Life Meets Your Career
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Ethics in NLP
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The Initiative Behind Opportunity
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The Closest I Got to Mars
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X-AI
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When Data Scientist Get It Wrong
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Once Upon a Data
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Keeping Watch: Effective Strategies for Machine Learning Model Monitoring
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