Thanh Tung Vu
ML/AI/Optimization Researcher & Practitioner
I'm a researcher and practitioner bridging the gap between cutting-edge machine learning research and real-world applications. With a background in mathematical optimization and deep learning, I help organizations solve complex problems while mentoring the next generation of ML engineers.
TTV
Profile Photo
My Journey
From academia to industry - a path of continuous learning and impact
2024
Independent Researcher & Consultant
Self-employed
Launched consulting practice helping organizations implement ML/AI solutions while continuing research collaborations and mentoring.
2020-2024
Senior Research Scientist
Tech Research Labs - San Francisco, CA
Led research initiatives in optimization algorithms and deep learning, published 12+ papers, and mentored junior researchers.
2018-2020
Postdoctoral Researcher
Stanford University - Stanford, CA
Conducted research on scalable optimization methods for large-scale machine learning systems.
2014-2018
Ph.D. in Computer Science
MIT - Cambridge, MA
Dissertation on 'Adaptive Optimization Methods for Deep Neural Networks'. Awarded Best Thesis Award.
2010-2014
B.S. in Mathematics & Computer Science
University of California, Berkeley - Berkeley, CA
Graduated summa cum laude. First exposure to machine learning through undergraduate research.
Expertise & Research Interests
Areas where I can help you achieve breakthrough results
Machine Learning & Deep Learning
Building and deploying production ML systems, from classical algorithms to state-of-the-art deep neural networks.
Machine LearningDeep LearningPyTorchTensorFlow
Mathematical Optimization
Formulating and solving complex optimization problems including linear, nonlinear, and mixed-integer programming.
OptimizationOperations ResearchConvex Optimization
Time Series & Forecasting
Developing forecasting models for demand prediction, financial modeling, and resource planning.
Time SeriesForecastingDeep Learning
MLOps & Production Systems
Designing scalable ML infrastructure, CI/CD pipelines, and monitoring systems for production deployments.
MLOpsPythonDockerKubernetes
Credentials & Achievements
Numbers that reflect years of dedicated work in research and practice
25
Publications
1,200+
Citations
$2.5M+
Funding Secured
5
Awards
10+
Years Experience
30
Students Mentored
Selected Awards & Recognition
Best Paper Award
NeurIPS - 2023
For research on scalable optimization methods
Outstanding Dissertation Award
MIT EECS - 2018
Top thesis in Computer Science department
Rising Star in AI
Forbes 30 Under 30 - 2021
Best Tutorial Award
ICML - 2022
For tutorial on practical optimization in deep learning
NSF CAREER Award
National Science Foundation - 2020
My Philosophy
Core beliefs that guide my approach to research, teaching, and collaboration
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Research with Impact
I believe the best research solves real problems. Every project I take on must have a clear path from theory to practice.
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Teach to Learn
Teaching forces clarity of thought. By explaining concepts to others, I deepen my own understanding and discover new perspectives.
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Collaboration Over Competition
The most impactful work comes from diverse teams. I actively seek collaborators who bring different skills and viewpoints.
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Continuous Learning
ML/AI evolves rapidly. I dedicate time each week to exploring new papers, tools, and techniques to stay at the frontier.
Beyond Work
A few things that keep me balanced and inspired
🏃
Marathon Runner
I've completed 5 marathons and find long runs are my best thinking time for research problems.
☕
Coffee Enthusiast
I roast my own coffee beans. The optimization problem of the perfect roast profile is surprisingly complex!
🎹
Amateur Pianist
Jazz piano helps me relax. I see parallels between improvisation and creative problem-solving.
📚
Science Fiction Reader
From Asimov to Liu Cixin - I love exploring how authors imagine technology's future impact on society.
Let's Work Together
Whether you need research collaboration, consulting expertise, career mentoring, or ML education, I'm here to help.