Yanping Lu
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Yanping Lu Email & Phone Number

Senior Applied Research Scientist at Stradigi AI
Location: Montreal, Quebec, Canada 4 work roles 4 schools
1 work email found @usherbrooke.ca LinkedIn matched
✓ Verified Jul 2026 4 data sources Profile completeness 100%

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Work email y****@usherbrooke.ca
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Current company
Role
Senior Applied Research Scientist
Location
Montreal, Quebec, Canada
Company size

Who is Yanping Lu? Overview

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Quick answer

Yanping Lu is listed as Senior Applied Research Scientist at Stradigi AI, a with 86 employees, based in Montreal, Quebec, Canada. AeroLeads shows a work email signal at usherbrooke.ca and a matched LinkedIn profile for Yanping Lu.

Yanping Lu previously worked as Senior Machine Learning Researcher at Nebula Ai Inc. and Software Developer at Hitachi Id Systems, Inc.. Yanping Lu holds Doctor Of Philosophy - Phd, Computer Science from Université De Sherbrooke.

Company email context

Email format at Stradigi AI

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{first}.{last}@usherbrooke.ca
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Profile bio

About Yanping Lu

-- Ph.D. in machine learning-- Over 8 years of educational and industrial experience in Machine/Deep Learning, Natural Language Understanding (NLU), Parameter optimization-- Expertise in ML frameworks such as tensorflow, keras, scikit-learn; experience with Pytorch, multi-GPUs programming.-- Programming: Python, C++, Java

Listed skills include C++, Java, Mysql, Linux, and 10 others.

Current workplace

Yanping Lu's current company

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Stradigi AI
Stradigi Ai
Senior Applied Research Scientist
montréal, quebec, canada
Website
Employees
86
AeroLeads page
4 roles

Yanping Lu work experience

A career timeline built from the work history available for this profile.

Senior Applied Research Scientist

Current

Montreal, Canada Area

• Conduct experiments for cutting edge pre-trained language models (e.g. BERT, XLNet) and compressed models (e.g. ALBERT) for different NLP tasks, such as text classification, semantic text similarity etc. • Propose domain adapted language models to improve performance of text classification in the finance/law domains • Conduct experiments for diversity of embeddings, strategies for imbalance data, optimize single deep learning models, different ensembles to improve performance of… Show more • Conduct experiments for cutting edge pre-trained language models (e.g. BERT, XLNet) and compressed models (e.g. ALBERT) for different NLP tasks, such as text classification, semantic text similarity etc. • Propose domain adapted language models to improve performance of text classification in the finance/law domains • Conduct experiments for diversity of embeddings, strategies for imbalance data, optimize single deep learning models, different ensembles to improve performance of multi-label industry/topic classification, Strong implementation of codes, implement prototypes to test new ideas and algorithms using tensorflow • Actively implement new prototypes for company’s ML library and new features for Kepler platform. Owner of text pipelines (text classification and semantic text similarity) in NLP framework design and deep experience in text annotation, text augmentation, text standarization, embedding reduction and ML models (CNNs, RNNs, Transformer and language models etc.) for text pipelines, experience with big data using dask • Experience with multiple language text: English, Spain, Portuguese, French etc., experience with Git, AWS, Dask etc. Show less

Oct 2018 - Present

Senior Machine Learning Researcher

Nebula Ai Inc.

Montreal, Canada Area

• Sentiment analysis: use NLTK to preprocess raw twitter text, initialize word embeddings (glove and word2vec), improve existing ML models such as CNN, LSTM with attentions, Transformer for text classification• Machine translation: employ Byte Pair Encoding to learn joint sub words out of the full vocabulary, implement ML models such as seq2seq, RNN, Transformer for machine translation, adapt codes in tensorflow for multi-GPUs• Ethereum price prediction: difference time series data to… Show more • Sentiment analysis: use NLTK to preprocess raw twitter text, initialize word embeddings (glove and word2vec), improve existing ML models such as CNN, LSTM with attentions, Transformer for text classification• Machine translation: employ Byte Pair Encoding to learn joint sub words out of the full vocabulary, implement ML models such as seq2seq, RNN, Transformer for machine translation, adapt codes in tensorflow for multi-GPUs• Ethereum price prediction: difference time series data to remove its trend, transform time series prediction to supervised learning issue, propose an ensemble of non-linear regression algorithms for ETH price prediction• Implementing the machine learning models with Python, based on frameworks (tensorflow, scikit-learn and pytorch)• Experience with multi-GPUs programming Show less

Jan 2017 - Sep 2018

Software Developer

Montreal, Canada Area

• Implement E-Commerce web site using Java 8, Spring MVC, J2EE, Hibernate, Eclipse, MySQL • Use Freemarker and JSP to implement the code generator module to automatically generate Java and JSP files, which largely speed up the speed

Mar 2015 - Aug 2016

Assistant Professor

Xiamen University

Xiamen, Fujian, China

• Dedicate to natural language processing, and image processing and recognition• Propose new machine learning algorithms and apply to detect abnormal ECG, in order to work with physicians to reduce costs and improve precision of early detection of heart diseases.• Adapt and improve existing machine learning models for machine translation using C++• Have publications in top AI journals such as Machine Learning, IEEE Transactions on Biomedical Engineering• Particle Swarm Optimizer… Show more • Dedicate to natural language processing, and image processing and recognition• Propose new machine learning algorithms and apply to detect abnormal ECG, in order to work with physicians to reduce costs and improve precision of early detection of heart diseases.• Adapt and improve existing machine learning models for machine translation using C++• Have publications in top AI journals such as Machine Learning, IEEE Transactions on Biomedical Engineering• Particle Swarm Optimizer for Variable Weighting in Clustering High-dimensional Data, Machine Learning, 82: 43-70, 2011.• ECG Analysis Using Multiple Instance Learning for Myocardial Infarction Detection, IEEE Transactions on Biomedical Engineering, 59(12), 2012 Show less

Oct 2009 - Feb 2015
Team & coworkers

Colleagues at Stradigi AI

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4 education records

Yanping Lu education

Doctor Of Philosophy - Phd, Computer Science

-- Major in machine learning and data mining -- Dedicate to data analysis, feature extraction, classification and clustering sparsely.

Doctor Of Philosophy - Phd, Artificial Intelligence

- Parameter optimization for neural networks

FAQ

Frequently asked questions about Yanping Lu

Quick answers generated from the profile data available on this page.

What company does Yanping Lu work for?

Yanping Lu works for Stradigi AI.

What is Yanping Lu's role at Stradigi AI?

Yanping Lu is listed as Senior Applied Research Scientist at Stradigi AI.

What is Yanping Lu's email address?

AeroLeads has found 1 work email signal at @usherbrooke.ca for Yanping Lu at Stradigi AI.

Where is Yanping Lu based?

Yanping Lu is based in Montreal, Quebec, Canada while working with Stradigi AI.

What companies has Yanping Lu worked for?

Yanping Lu has worked for Stradigi Ai, Nebula Ai Inc., Hitachi Id Systems, Inc., and Xiamen University.

Who are Yanping Lu's colleagues at Stradigi AI?

Yanping Lu's colleagues at Stradigi AI include Corey Williams, Anne Hopkins, Fanzen Achoui, and Sam Mhanna.

How can I contact Yanping Lu?

You can use AeroLeads to view verified contact signals for Yanping Lu at Stradigi AI, including work email, phone, and LinkedIn data when available.

What schools did Yanping Lu attend?

Yanping Lu holds Doctor Of Philosophy - Phd, Computer Science from Université De Sherbrooke.

What skills is Yanping Lu known for?

Yanping Lu is listed with skills including C++, Java, Mysql, Linux, Algorithms, Data Mining, Junit, and Tomcat.

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