Shan Wan
Senior Research And Training Partner at ByteDance
Singapore
Summary
👤
Senior🎓
Top SchoolShan Wan is a research-oriented senior professional based in Singapore with 11 years' experience at the intersection of machine learning, organizational culture, and global strategy, currently serving as Senior Research and Training Partner at ByteDance. With a unique background that blends an MPhil in Psychology from Cambridge and strong empirical research skills, Shan applies data-driven methods to leadership development, change management, and employee engagement across global teams. Technically fluent in LLMs, speech and video understanding, Shan has hands-on ML engineering experience—contributing local attention mechanisms and multi-GPU optimizations to the well-known Nematus neural machine translation project. This combination of rigorous social-science research and practical ML engineering enables Shan to "bridge mind and world," translating human-centered insights into scalable AI-informed organizational solutions. Colleague-facing roles and cross-cultural projects across Cambridge, Boston University, and ByteDance underscore a rare mix of academic rigor, product-minded engineering, and global change leadership.
11 years of coding experience
2 years of employment as a software developer
Master of Philosophy - MPhil, Biological Science (Psychology), Master of Philosophy - MPhil, Biological Science (Psychology) at University of CambridgeJapanese Language and Literature, 4.0/4.0, Japanese Language and Literature, 4.0/4.0 at 美国波士顿大学Bachelor’s Degree with Honors, Psychology, 3.9/4.0, Bachelor’s Degree with Honors, Psychology, 3.9/4.0 at Boston University
Chinese, English, Japanese
Github Skills (11)
machine-translation10
machine-learning10
tensorflow10
nmt10
python10
neural-machine-translation10
n9
rnn-model9
nlp9
sequence-to-sequence9
theano8
Programming languages (7)
Github contributions (5)
EdinburghNLP/nematus
Jan 2017 - Jun 2017
Open-Source Neural Machine Translation in Tensorflow
Role in this project:
ML Engineer
ML EngineerContributions:21 commits, 5 PRs, 5 comments in 4 months
Contributions summary:Shan primarily focused on adding and refining local attention mechanisms within the neural machine translation framework. Their contributions included implementing a new `gru_local` layer with associated parameter initialization and attention mechanisms, and fixing bugs related to this local attention implementation. Furthermore, the user made enhancements to the translation pipeline, enabling multi-GPU processing, suggesting work that involved adapting and optimizing the system for improved performance. This indicates a focus on improving the core machine translation capabilities of the project.
machine-translationtranslationnmttensorflowsequence-to-sequence
cshanbo/leetcode
Jul 2016 - Jan 2020
Contributions:59 pushes, 1 branch in 3 years 6 months
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