I’m grateful for every opportunity to share my work. I can talk about:
- machine learning systems design
- machine learning in production at scale
- machine learning interviews and recruiting pipeline
- community building and developer relations
- deep learning fundamentals, applications, and trends
- challenges of hand-labeling data
- TensorFlow, PyTorch, and high-level frameworks
My bios and photos can be found here. Below is the selected list of my talks.
On sharing events on social media
I feel self conscious when sharing anything on social media. I get nervous when an organizer asks me to do so. Please don’t expect me to promote your event if I agree to speak. Thank you!
Jan 20, 2021: Machine learning is going real-time
Nov 19, 2020: Machine learning production
NLPOSS @ EMNLP
Nov 18, 2020: Machine learning production
TMLS Annual Conference & Expo
Aug 20, 2020: Machine Learning Production
Jul 22, 2020: Machine Learning Production Pipeline
Challenges in Deploying and Monitoring Machine Learning Systems @ ICML (Vienna, Austria)
Nov 2, 2019: Machine Learning Interivews (talk) | AI In Industry and Vietnam (panel)
VietAI Summit (Ho Chi Minh City, Vietnam)
Jan 25, 2018: TensorFlow Tutorial
Guest lecture for Stanford’s CS224N class (Stanford, USA)
Dec 9, 2017: Mitigating the spread of fake news by identifying and disrupting echo chambers
Spotlight talk at NIPS Workshop on Prioritising Online Content (Long Beach, USA)
Aug 5, 2012: Traveling is an equal opportunity
[email protected] (Hanoi, Vietnam)
I occasionally write papers and/or support my coworkers with their papers. My research focuses on the intersection between Natural Language Processing and Deep Learning.
For the full list of papers, see my Google Scholar profile.
NeMo: a toolkit for building AI applications using Neural Modules
Oleksii Kuchaiev, Jason Li, Huyen Nguyen, Oleksii Hrinchuk, Ryan Leary, Boris Ginsburg, Samuel Kriman, Stanislav Beliaev, Vitaly Lavrukhin, Jack Cook, Patrice Castonguay, Mariya Popova, Jocelyn Huang, Jonathan M Cohen Accepted to Machine Learning Systems workshop at NeurIPS 2019.
The Propagation of Lies: Impeding the Spread of Misinformation
H Nguyen, C Huyi, P Warren
Detect echo chambers and recommend content of different perspectives. Spotlight talk at Prioritising Online Content workshop, NIPS 2017. Americas’ regional winner for Ericsson Innovation Awards 2018.
MEWR: Automatic Machine Translation Evaluation without Reference Texts
H Nguyen, J Chang
Unsupervised translation score with strong correlation with BLEU score and human evaluation. Poster at Women in Machine Learning 2017.
Neural Networks for Automated Essay Grading
H Nguyen, L Dery
Automatically grade essays using bi-directional LSTM. Achieved a QW-Kappa score of 0.945 compared to 0.814, Kaggle winner.