Apr 20th - Apr 22nd

Natural Language Processing Track

Learn the latest models, advancements, and trends from the top practitioners and researchers behind NLP
Register your interest

NLP has seen rapid advances in recent years. With some of the sharpest minds in data science presenting, get the latest insights, natural language processing training, trends, and discoveries in data science languages, tools, topics – and beyond.

Connect with some of the most innovative people and ideas in the world of data science, while learning first-hand from core practitioners and contributors. Learn about the latest advancements and trends in NLP, including pre-trained models, with use-cases focusing on deep learning, speech-to text, and semantic search.

Some of Our Current NLP Speakers

Director of AnalyticsTamr

Julia Neagu, PhD

Julia is the Director of Analytics at Tamr, where she is expanding the company’s analytics and data science solutions. Before joining Tamr, she led end-to-end modeling and development of data science products at Aon’s Intellectual Property Solutions group. Her previous experience includes technology-focused litigation consulting, quantitative finance, and private equity. Julia has a PhD in Physics from Harvard.

The Healthy Approach – Organic Data Enrichment Through Entity Extraction(Talk)

DataOps EngineerTamr

Ian Bakst, PhD

Ian is a DataOps Engineer at Tamr, where he works on designing and implementing Tamr’s data solutions for clients. Before Tamr, Ian applied machine learning models to research properties of materials. His previous work includes high-throughput modeling of superelasticity in a novel class of intermetallic crystals. Ian has a PhD in Mechanical Engineering from Colorado State University.

The Healthy Approach – Organic Data Enrichment Through Entity Extraction(Talk)

Machine Learning EngineerNovetta

Amber Chin

Amber is a Machine Learning Engineer at Novetta and a student at the University of Texas at San Antonio. Her primary interests are in natural language processing and applying deep learning to analyze digital communication. Prior to starting at Novetta, Amber worked in UTSA’s Digital Politics Studio examining the effects of political incivility on social media platforms and developing methods for detecting uncivil language online. Amber will graduate from UTSA this spring with Bachelor’s degrees in Psychology and English.

Narrative Extraction for Disinformation Detection(Talk)

Senior Data Scientist, AI&ML Instructor QBE Insurance, DataCamp

Thushan Ganegedara

Thushan is a Senior Data Scientist at QBE Insurance, Australia, where he works on marrying artificial intelligence with business acumen to solve business problems. He has extensive knowledge of deep learning techniques, that has been poured into two books and a video course on deep learning (TensorFlow). In his free time, Thushan answers questions on StackOverflow, creates YouTube content or presents at local meetups. He obtained his PhD from the University of Sydney, specializing in deep learning and reinforcement learning. When not indulging in the world of data science, Thushan enjoys meditation, swimming and hiking.

Art of BERT: Unlock the Full Potential of BERT for Domain-Specific Tasks(TensorFlow)(Workshop)

Cloud ArchitectGoogle

Elliott Ning

Elliott Ning is a passionate technology advisor of Google for data analytics, infrastructure modernization, and AI to bring organizations business opportunities into reality. Previously he has worked in leading technology companies including Oracle and Huawei to transform enterprises by developing solutions and strategies on cloud platforms and data centers. Elliott holds two MS degrees in Software Engineering and Manufacturing Management, and extensive industrial certifications in IT and cloud.

Accelerating The Journey To Document Understanding AI(Talk)

Lead Instructorideai.io

Leonardo De Marchi

Leonardo De Marchi holds a Master in Artificial intelligence and has worked as a Data Scientist in the sports world, with clients such as the New York Knicks and Manchester United, and with large social networks, like Justgiving. His previous experience includes Head of Data Science and Analytics in Bumble, the largest dating site with over 500 million users, heading the team through an acquisition and an IPO.

He is also the lead instructor at ideai.io, a company specialized in Reinforcement Learning, Deep Learning and Machine Learning training. He is also a contractor for several companies and for the European Commission, as an expert in AI and Machine Learning. As an author he wrote “Hands On Deep Learning” and he authored an online training course for O’Reilly, Introduction to Reinforcement Learning. In the academic world, he also helped set up the PhD center on Interactive Artificial Intelligence and will take part in the Inner Assessment Board to assign funding to Irish research in AI.

NLP Fundamentals(Full-Day Training)

Machine Learning Research EngineerAxel Springer

Francesco Cardinale

Francesco received his MS degree in Computational Mathematics in 2017 from the Department of Mathematics at the Technical University of Berlin. After a research experience in Bayesian machine learning, he pivoted into deep learning with generative models and computer vision. In his current position as a machine learning research engineer, he works on NLP and speech synthesis and has presented and authored a few open source projects related to these topics.

Brand Voice: Deep Learning for Speech Synthesis(Workshop)

Digital Research and Scholarship LibrarianNorth Carolina State University Libraries

Scott Bailey

Scott Bailey is the Digital Research and Scholarship Librarian at the NC State University Libraries, where he collaborates with faculty and other scholars in applying digital and computational tools and methods to open new possibilities in research and learning. He regularly teaches workshops using programming languages like Python and R to introduce data analysis and visualization, machine learning, and computational approaches to text data. He was previously the Head of Social Science Data and Software in the Center for Interdisciplinary Digital Research (CIDR) at Stanford Libraries, where he oversaw a group of Ph.D. students in delivering expert consultation on statistical computing, organized and taught in the CIDR workshop series, and collaborated with colleagues across Stanford University to provide better access to data and support for data-driven research.

Exploratory Text Analysis in Python Using spaCy and textacy(Workshop)

Chief Scientist and Head of Conversational AIGot It AI

Chandra Khatri

Chandra Khatri is the Chief Scientist and Head of AI at Got It AI, wherein, his team is transforming the AI space by leveraging state-of-the-art technologies in order to deliver Self-Discovering, Self-Training, and Self-Optimizing products. Under his leadership, Got It AI is democratizing Conversational AI and related ecosystems through automation. Prior to Got-It, Chandra was leading various kinds of applied research projects at Uber AI such as Conversational AI, Multi-modal AI, and Recommendation Systems.

Prior to Uber AI, he was the founding member of the Alexa Prize Competition at Amazon, wherein he was leading the R&D and got the opportunity to significantly advance the field of Conversational AI, particularly Open-domain Dialog Systems, which is considered as the holy-grail of Conversational AI and is one of the open-ended problems in AI. Prior to Alexa AI, he was driving NLP, Deep Learning, and Recommendation Systems related Applied Research at eBay. He graduated from Georgia Tech with a specialization in Deep Learning in 2015 and holds an undergraduate degree from BITS Pilani, India.

His current areas of research include Artificial and General Intelligence, Democratization of AI, Reinforcement Learning, Language Understanding, Conversational AI, Multi-modal and Human-agent Interactions, and Introducing Common Sense within Artificial Agents

Advances in Conversational AI and NLP through Large Scale Language Models such as GPT-3(Workshop)

Senior Machine Learning EngineerAxel Springer

Christian Schäfer, PhD

Christian Schäfer is driving AI research within the Axel Springer group and helps to integrate machine learning systems in production. His goal is to create products that are both smart and pretty, so that everyone will like them. Having an academic background in theoretical physics, Chris is interested in understanding complex phenomena, and his professional interests moved from network theory over neuroscience to deep learning, which all share some interesting similarities.

Brand Voice: Deep Learning for Speech Synthesis(Workshop)

Data ScientistMediaMath

Jayeeta Putatunda

Jayeeta is a Data Scientist with 5+ years of industry experience. She recently led six-week NLP workshops in association with Women Who Code, Data Science track. Jayeeta has also been a speaker at International Conference on Machine Learning (ICML 2020), MLConf EU, WomenTech Global Conference, and Data Summit Connect. She works extensively on NLP projects where she gets to explore a lot of state-of-the-art models and build cool products and firmly believes that data is the best storyteller. Recently, Jayeeta joined MediaMath, a leader in the programmatic AdTech domain. Prior to this, she worked at Indellient, Omnicom, Deloitte, and Volvo Group. Jayeeta is also engaged with some amazing organizations to promote and inspire more women to take up STEM. Jayeeta received her Master of Science in Quantitative Methods and Modeling from City University of New York, NY, and Bachelor of Science in Economics and Statistics from West Bengal State University, India.
Website – https://jayeetap.wixsite.com/helloworld

Build a Question Answering System using DistilBERT in Python(Workshop)

Machine Learning EngineerNovetta

Carlos Martinez

Carlos is a Machine Learning Engineer at Novetta and a graduate student in Computational Linguistics at Montclair State University. His primary interests are in natural language processing, linguistics, and voice application development. Prior to working at Novetta, Carlos worked as a voice app developer for Voicefirst Tech and as a NLP research assistant for the Montclair State University research lab detecting censored language on Chinese social media.

Narrative Extraction for Disinformation Detection(Talk)


Some of Our Previous NLP Speakers

Chief Science OfficerHugging Face 🤗

Thomas Wolf, PhD

Thomas leads the Science Team at Huggingface Inc., a Brooklyn-based startup working on Natural Language Generation and Natural Language Understanding.

After graduating from Ecole Polytechnique (Paris, France), he worked on laser-plasma interactions at the BELLA Center of the Lawrence Berkeley National Laboratory (Berkeley, CA). Got accepted for a PhD at MIT (Cambridge, MA) but ended up doing his PhD in Statistical/Quantum physics at Sorbonne University and ESPCI (Paris, France), working on superconducting materials for the French DARPA (DGA) and Thales.

Thomas is interested in Natural Language Processing, Deep Learning, and Computational Linguistics. Much of his research is about Natural Language Generation (mostly) and Natural Language Understanding (as a tool for better generation).

An Introduction to Transfer Learning in NLP and HuggingFace Tools(Workshop)

Senior Data Scientist, InstructorMetis

Kimberly Fessel, PhD

Kimberly Fessel is a Senior Data Scientist at Metis, the industry’s only accredited, full-time, immersive data science bootcamp. Prior to joining Metis as an instructor, Kimberly worked in digital advertising at MRM//McCann where she focused on helping clients understand their customers by leveraging unstructured data with modern NLP techniques. She holds a Ph.D. in applied mathematics from Rensselaer Polytechnic Institute and completed an NSF-funded postdoctoral fellowship in math biology at the Ohio State University. She is passionate about data visualization and about harnessing the power of language to tell compelling data stories.

Level Up: Fancy NLP with Straightforward Tools (Talk)

Principal Data ScientistLinc Global

Joan Xiao, PhD

Joan Xiao is a Principal Data Scientist at Linc Global, a commerce-specialized customer care automation company. In her role, she applies novel natural language processing and machine learning techniques to improve customer experience. Previously she led machine learning and data science teams at various companies ranging from startup to Fortune 100. Joan received her Ph.D in Mathematics and MS in Computer Science from University of Pennsylvania.

Transfer Learning in NLP(Talk)

Head of AI EngineeringBloomberg

Dr. Anju Kambadur

Dr. Prabhanjan (Anju) Kambadur heads the AI Engineering group at Bloomberg. Anju leads a group of 100+ researchers and engineers who build solutions for Bloomberg clients in the areas of machine learning, natural language processing (NLP) and natural language understanding, information extraction, knowledge graphs, question answering, and table understanding. Previously, Anju was a research staff member in the Business Analytics and Mathematical Sciences Department at IBM Research’s Thomas J. Watson Research Center, where he worked on problems in machine learning, such as matrix sketching, genome-wide association studies, temporal causal modeling, and high-performance computing. He received his PhD from Indiana University. Anju has published peer-reviewed articles in the fields of high-performance computing, machine learning, and natural language processing.

AI Research at Bloomberg(Talk)


More talks, hands-on workshop and training sessions
See all sessions

You Will Meet

  • Some of the world’s best data science speakers

  • The brains and authors behind today’s most popular open data science tools, topics, and languages

  • Hundreds of attendees focused on data science

  • Chief Data Scientists

  • Thought leaders working in data science

  • Data Scientists and Analysts

  • Software Developers

  • CEOs, CTOs, CIOs

  • Data Visualization professionals

  • Venture Capitalists and Investors

  • Startup Founders and Executives

  • Attendees from Healthcare, Finance, Education, Business, Intelligence, and other industries

  • Big data and data science innovators

Why Attend?

Several of the best minds and biggest names in data science will be presenting

Network with attendees from leading data science companies to learn how others are tackling similar problems

Gain quality training in the hottest data science topics, tools, and languages

Learn the latest in data science from industry leaders without having to make room in the budget — tickets are surprisingly inexpensive

What You'll Learn

Talks & Workshops on these topics:

Topics

  • Natural Language Processing

  • NLP Transformers

  • Pre-trained Models

  • Text Analytics

  • Natural Language Understanding

  • Sentiment Analysis

  • Natural Language Generation

  • Speech Recognition

  • Named Entity Extraction

Models

  • BERT

  • XLNet

  • GPT-2

  • Transformers

  • Word2Vec

  • Deep Learning Models

  • RNN & LSTM

  • Machine Learning Models

  • ULMFiT

  • Transfer Learning

Tools 

  • Tensorflow 2.0

  • Hugging Face Transformers

  • PyTorch

  • Theano 

  • SpaCy

  • NLTK

  • AllenNLP

  • Stanford CoreNLP

  • Keras

  • FLAIR 

ODSC EAST 2022 | April 20th-22nd

Register your interest
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