Kun-Hua (Eric) Tu Email and Phone Number
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Visionary AI practitioner who adopts fast, thinks strategically, approaches systematically and delivers thoughtfully. Influential scientist with 21 top-tier research papers cumulated more than 1000 citations. Detail-oriented engineer, committed in delivering clean, self-explained production code. Cross-functional communicator, critical thinker, 0 to 1 creator, and solid contributor of research and engineering teams.
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Senior Machine Learning Research ScientistBuoy Health Jan 2021 - PresentBoston, Ma, UsBuoy builds a free digital health tool that helps people – from the moment they get sick – start their health care on the right foot. Started by a team of doctors and computer scientists working at the Harvard Innovation Laboratory in Boston MA, Buoy was developed in direct response to the downward spiral we’ve all faced when we attempt to self-diagnose our symptoms online. Buoy leverages artificial intelligence – powered by advanced machine learning and proprietary granular data - to resemble an exchange you would have with your favorite doctor – to provide consumers with a real-time, accurate analysis of their symptoms and help them easily and quickly embark on the right path to getting better. -
Machine Learning Research ScientistBuoy Health Jan 2018 - Jan 2021Boston, Ma, Us -
Artificial Intelligence FellowInsight Data Science Sep 2017 - Dec 2017San Francisco, Ca, UsBuilt a cat photo analyzer as a marketing tool for a collaborated company, Snappr.- Trained and tweaked a Inception-Resnet model that can identify cat breed among 42 classes, as well as the alertness, cuteness and emotion of a cat.- Achieved 90% top-1 accuracy and 98% top-3 accuracy in classifying cat breed.- Utilized Amazon Rekognition API to prevent people from tricking the model with non-cat pictures.- Delivered an engaging, fun web app (Snapcat) for people to play with. -
Research AssistantMassachusetts Institute Of Technology (Mit) Sep 2012 - Aug 2017Cambridge, Ma, UsModeled the thermodynamic behavior of block-copolymer.- Developed a convolutional neural net model that recognizes three different copolymer patterns with the accuracy over 99%.- Performed image analysis and measured the pattern quality of each experiment.- Built a regression model that predicts the pattern quality with given time-series experimental parameters, which helps us find the optimal experiment setup and reduce the pattern defect density by ~20x.Developed scalable lithography method at 10 nm node for future magnetic devices such as bit-patterned media and magnetic random access memory, and exploring the nanoscale magnetism in a statistical manner. -
Graduate ResearcherNational Taiwan University Sep 2009 - Jun 2011Taipei, Northern Taiwan, TwOriginated and illustrated the idea of all-carbon based solar cell that generates energy in a sustainable way.
Kun-Hua (Eric) Tu Skills
Kun-Hua (Eric) Tu Education Details
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Massachusetts Institute Of TechnologyMaterials Science And Engineering -
National Taiwan UniversityMaterials Science -
National Taiwan UniversityMaterials Science
Frequently Asked Questions about Kun-Hua (Eric) Tu
What company does Kun-Hua (Eric) Tu work for?
Kun-Hua (Eric) Tu works for Buoy Health
What is Kun-Hua (Eric) Tu's role at the current company?
Kun-Hua (Eric) Tu's current role is Senior Machine Learning Research Scientist at Buoy Health.
What is Kun-Hua (Eric) Tu's email address?
Kun-Hua (Eric) Tu's email address is kt****@****mit.edu
What is Kun-Hua (Eric) Tu's direct phone number?
Kun-Hua (Eric) Tu's direct phone number is +161785*****
What schools did Kun-Hua (Eric) Tu attend?
Kun-Hua (Eric) Tu attended Massachusetts Institute Of Technology, National Taiwan University, National Taiwan University.
What are some of Kun-Hua (Eric) Tu's interests?
Kun-Hua (Eric) Tu has interest in Snowboarding, Machine Learning, Baseball, Optoelectronics, Photography, Spintronics, Deep Learning, Neuromorphic Computing, Nanofabrication.
What skills is Kun-Hua (Eric) Tu known for?
Kun-Hua (Eric) Tu has skills like Machine Learning, Deep Learning, Artificial Neural Networks, Data Analysis, Python, Nanotechnology, Scanning Electron Microscopy, Image Analysis, Nanomaterials, Algorithms, Latex, Atomic Force Microscopy.
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