I’m grateful for every opportunity to share my work. I can talk about:
- weak supervision and programmatic labeling
- machine learning systems design
- challenges of machine learning in production
- machine learning interviews and recruiting pipeline
- deep learning fundamentals, applications, and trends
- data and privacy
- machine translation and evaluation metrics
- open-source and open-core for machine learning
- TensorFlow, PyTorch, and high-level frameworks
My bios and photos can be found here. Below is the selected list of my upcoming and previous talks.
Note 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 because it makes me feel obligated. Please don’t expect me to promote your event if I agree to speak. Thank you!
Nov 12, 2020: TBD
MLSys Seminar Series @ Stanford (Virtual)
Nov 18, 2020: TBD
TMLS Annual Conference & Expo
Nov 19, 2020: TBD
NLPOSS @ EMNLP (Virtual)
Aug 20, 2020: Machine Learning Production
Jul 22, 2020: Machine Learning Production Pipeline
Challenges in Deploying and Monitoring Machine Learning Systems @ IMCL (Vienna, Austria)
Nov 2, 2019: Machine Learning Interivews (talk) | AI In Industry and Vietnam (panel)
VietAI Summit (Ho Chi Minh City, Vietnam)
Apr 20, 2019: MEWR - Machine Translation Evaluation without Reference Texts
GDG Cloud SF’s IWD Celebration (San Francisco, USA)
Jan 26, 2019: Understanding evaluation metrics for language model and their implications
Google DevFest 2018 (San Francisco, USA)
Dec 2, 2018: Mixed-precision training in TensorFlow with OpenSeq2Seq
NVIDIA Expo at NeurIPS (Montreal, Canada)
Apr 20, 2018: AI for developing countries
SVAI Download (Mountain View, USA)
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.