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My name is Noa Lubin, recently nominated in Forbes 30 Under 30 list.
I am a data science researcher at Diagnostic Robotics and formerly worked as a researcher at NASA, Amazon, Elbit and IAI.
I love data, and my main focus is on NLP, healthcare and space. I love public speaking, mostly about topics in AI.
I have a Computer Science Master's degree, Bar-Ilan University (Magna Cum Laude), with an NLP thesis advised by Prof. Yoav Goldberg.
And, an Electrical Engineering Bachelor's degree, Technion (Summa Cum Laude).
I am an Analog Astronaut at D-MARS and the founder and president of Space It Up.
I am also the Founder and Chair of the Board of Hydrocephalus Israel Non-profit.

Noa Lubin

Senior Data Scientist
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English, Hebrew, French
Kiryat Ono, Israel
Can also give an online talk/webinar
Paid only. Contact speaker for pricing!


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

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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


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.

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