NLP Summit 2023
Free Online Event | Sept 26-28, 2023
Presented by
Applied Natural Language Processing
Join the wold’s largest applied NLP community at this third edition of the virtual NLP Summit! Three days of immersive content including over 50 technical sessions, with focus days on open source, healthcare, and finance. Attend live Q&A sessions with the speakers, connect with others through networking features, and access all content on-demand after the event.
The second week will feature beginner to advanced live training workshops with certifications. Learn, share, and apply best practices for putting AI to good use!
“Brilliant event with a fantastic variety of topics and great speakers!”
“It was awesome!”
“The event was wonderful thanks for everything.”
“Really enjoyed the look of the conference, nicer flow than other virtual technical events I’ve attended.”
Excellent and informative sessions
“The virtual summit was really helpful. It was great opportunity to learn and interact at the comfort of our home.”
“YOU WERE GREAT! THE BEST SUMMIT!!!” – Clinical Effectiveness Analyst at Pieces
“Absolutely outstanding talks!” – Senior Data Scientist at Fitch Ratings
“My sincere thank you for having me as a speaker at the NLP Summit! It has been a wonderful experience and I had many people from my team/company who learned a lot from the talks. Thank you for this platform.” – Head of Data Science at Brillio
“Amazing job on organising such a fantastic event, congrats! The talk was very enjoyable and it was great to see the audience engage with questions.” – Machine Learning Research Engineer at Hugging Face
“Thank you very much! I love this event. Congratulations!” – Computer Science Engineering Student
Past Speakers
Barret Zoph
Member of the Technical Staff at OpenAI
Vishakha Sharma
Principal Scientist at Roche
Veysel Kocaman
Head of Data Science (Healthcare) at John Snow Labs
Moran Beladev
Machine Learning Manager - NLP & Computer Vision at Booking.com
Omri Allouche
Head of Research at Gong.io
Liam Fedus
Member of the Technical Staff at OpenAI
Lena Pfitzer
Principal Data Scientist at myNEO
David Talby
CTO at John Snow Labs
Sakshi Bhargava
Staff Data Scientist at Chegg
Gary Kazantsev
Head of Quant Technology Strategy, Office of the CTO at Bloomberg
Yishay Carmiel
Chief Executive Officer at Meaning
Maarten Grootendorst
Data Scientist at IKNL and Creator of BERTopic, PolyFuzz, and KeyBERT
Juan Martinez
Lead Data Scientist at John Snow Labs
Robbie Freeman
System VP & Chief Nursing Informatics Officer at Mount Sinai Health System
Joel Lehman
Researcher at Stochastic Labs
John Bohannon
Director of Science at Primer.ai
Suraj Patil
Machine Learning Engineer at Hugging Face
Sanchit Gandhi
Machine Learning Research Engineer at Hugging Face
Olivia Liao
Senior Director of Data Science at Stitch Fix
Daniel Svoboda
NLP Research Scientist at Johnson & Johnson
Usman Naseem
PhD Candidate at University of Sydney
Samuel Konstanty
Data Scientist at Loopback Analytics
Dia Trambitas
Head of Product at John Snow Labs
Brian Ulicny
Senior Technical Scientist at Raytheon Intelligence & Space
Vibhu Jawa
Senior Data Scientist at Nvidia
Mélissa Rollot
Data Science Manager at Quinten Health
Jayant Thomas
Senior Director AI/Machine Learning Engineering at Change Healthcare
Anjali Sreekumar
Engineering Manager at Lending Tree
Timothy Laurent
Principal Engineer - Machine Learning at Invitae
Neelesh Shukla
Research Scientist & Manager AI at State Street Corporation
Isaac Palka
Senior Director of Engineering at Invitae
Zach Wimpee
Clinical Effectiveness Analyst at Pieces
Jennifer D'Souza
Postdoctoral researcher at TIB – Leibniz Information Centre for Science & Technology
Mustafa Jarrar
Professor of Artificial Intelligence at Birzeit University
Tim Santos
Director of Devrel at Graphcore
Ragesh Hajela
Senior AI Engineer and Evangelist at Intel Corporation
Yanjun Gao
Postdoctoral Research Associate at University of Wisconsin-Madison
Harsha Gurulingappa
Head of Text Analytics at Merck KGaA, Darmstadt, Germany
Jacob Wilson
Principal, Products & Technology at PricewaterhouseCoopers (PwC)
Panos Alexopoulos
Head of Ontology at Textkernel BV
Ayush Singh
Sr. NLP ML Engineer at Cigna
Priya Shaji
Data Scientist at Memorial Sloan Kettering Cancer Center
Nandana Mihindukulasooriya
Research Scientist at IBM
Shobha Iyer
Lead Expert Big Data at Merck KGaA, Darmstadt, Germany
Vasanth Sarathy
Senior Researcher at SIFT (Smart Information Flow Technologies)
Vishnu Vettrivel
Founder at Wisecube
Alex Thomas
Principal Data Scientist at Wisecube
Adam Hirsch
Vision Transformers and Automatic Speech Recognition in Spark NLP at Real Chemistry
Sam Schifman
Chief Architect at Diameter Health
Maziyar Panahi
Principal AI/ML Engineer – Senior Team Lead at John Snow Labs
Avinash Pathak
Expert Data Scientist at TomTom
Swati Sharma
AI Lead - Head of Data Science at Brillio
Chandrasekhar Subramanyam
Senior Professor at IFIM Business School
Swagata Ashwani
Senior Data Scientist at Boomi
Matthew Davis
PhD Canidate Biomedical Data Science & Informatics at Medical University of South Carolina
About
The NLP Summit is the gathering place for those putting state-of-the-art natural language processing to good use. This third edition of the virtual conference showcases NLP best practices, real-world case studies, challenges in applying deep learning & transfer learning in practice – and the latest open source libraries, models & transformers you can use today. The NLP Summit brings together the growing NLP community interested in building language understanding applications used in healthcare, life science, finance, eCommerce, media, recruiting, and more.
Topics Covered
- Scaling NLP pipelines
- Machine translation in practice
- De-identification of sensitive free-text data
- Speech-to-text models and applications
- Ethical issues in natural language processing
- Object character recognition (OCR)
- Applications of natural language generation
- Tuning transformers for domain-specific NLP
- Optimizations & benchmarks on deep learning chips
- Multi-lingual NLP models and applications
- Question answering systems
- Conversational AI and dialog systems
- Building knowledge graphs from large document repositories
- Comparing BERT, Albert, Roberta, Ernie & friends
- Applying the “pre-train and fine-tune” paradigm
- Clinical natural language understanding
- Information extraction from natural language documents
Participating Companies
