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Vice President, Machine Learning at Epicore | ex-Meta | ex-Philips | ex-eBay | Lecturer on Software Engineering, Python, SQL, Machine Learning, Deep Learning, Reinforcement Learning, and Large Language Models (LMMs)
Dr. Kaitao Yang holds a doctorate degree in Electrical Engineering and a master’s degree in Computer Science, with over 8 years of industry experience in Machine Learning, Data Engineering, and Data Science. This wealth of expertise was cultivated through his work with tech giants such as Meta, Philips, and eBay, as well as with innovative startups like JADS and Epicore Biosystems. Over the course of his career, Dr. Yang has spent 4 years in senior management roles, including as Senior Manager at Philips and Vice President at Epicore Biosystems. Additionally, he founded a Data Science training company in Amsterdam, where he successfully guided more than 500 Data Scientists through training programs covering Machine Learning, Deep Learning, Reinforcement Learning, Data Science, Python, and SQL.
Eindhoven University of Technology
Doctorate in Engineering, Electrical Engineering
January 1, 2012 – January 1, 2016
Xiamen University
Master of Science, Computer Science
January 1, 2009 – January 1, 2012
Minzu University of China
Bachelor of Engineering, Electrical Information Engineering
January 1, 2005 – January 1, 2009
Epicore Biosystems
Vice President, Machine Learning
January 1, 2024 – Present
Cambridge, Massachusetts, United States
Epicore Biosystems
Senior Director, Machine Learning
January 1, 2023 – January 1, 2024
Cambridge, Massachusetts, United States
Meta
Senior Data Engineer
March 1, 2022 – January 1, 2023
Boston, Massachusetts, United States
Philips
Senior Data Scientist, Team lead
December 1, 2019 – November 1, 2021
Amsterdam, North Holland, Netherlands
eBay
Data Scientist (Deep Learning)
September 1, 2017 – December 1, 2019
The Randstad, Netherlands
Jheronimus Academy of Data Science
Data Engineer
May 1, 2016 – August 1, 2017
's-Hertogenbosch
The correlation between the textual news and stock price events (course project)
September 1, 2015 – October 1, 2015
This project was for the course "Web information retrieval and data mining". Key activities: Retrieving stock prices and reducing the dimension of textual features. Key techniques: Machine learning, web information retrieval, feature selection.
Teamwork project (Industrial project)
August 1, 2015 – January 1, 2016
The was an industrial project sponsored by NXP Semiconductors. Key activities: For reasons of confidentiality, the key activities are not mentioned here. Key techniques: System engineering (including electrical, mechanical, and software engineering), and agile project management.
Data analysis on fetal ECG recordings (cooperative project)
July 1, 2015 – September 1, 2015
This was a cooperative project with Ms Olenka Hulsenboom, which facilitates her to analyze a large amount of data recordings. Key activities: Developing MATLAB script to automatize the analysis of data recordings. Key techniques: Software engineering, data crunching.
Optimizing the configurational settings of the ASML wafer scanner platform (course project)
March 1, 2015 – June 1, 2015
This project was for the course "System engineering". Key activities: Optimizing the locations of sub-modules (i.e. conditioning, rotation, and exposure modules) on the platform. Key techniques: Machine learning, optimization, and SysML.
Risk analysis of a new medical device "Ipump" (course project)
March 1, 2015 – May 1, 2015
This project was for the course "Risk Management for Safety Critical Systems". Key activities: Analyzing the risk of a new medical device "Ipump" using the framework learned from this course. Key techniques: Risk Management, Clinical Hazards List, Harms Assessment List, Preliminary Hazard Analysis, Design/Process/Use Failure Mode and Effect Analysis, Risk Assessment and Control Table.
Adaptive Array Signal Processing in audio conferencing (Course project)
February 1, 2015 – April 1, 2015
This project was for the course is for the course "Adaptive Array Signal Processing". Key activities: Enhancing the audio signal of the target speaker and suppressing those of other speakers. Key techniques: Adaptive signal processing (including LMS, NLMS, RLS, FDAF), and array signal processing.
Intelligent fetal ECG monitoring (PDEng graduation project)
September 1, 2014 – March 1, 2016
This project is for my PDEng degree, which is sponsored by Máxima Medisch Centrum. Key activities: Developing signal processing methods for enhancement of direct fetal ECG recordings in order to enable fetal ECG analysis, such as ST analysis. Key techniques: Machine learning, digital filtering, adaptive signal processing, optimization, peak detection, fuzzy logic.
Electrohysterogram (EHG) analysis toolbox design
April 1, 2014 – August 1, 2015
Key activities: Designing a toolbox using MATLAB/GUI for processing EHG signals and visualizing uterine electrical activities. Key techniques: Biomedical signal processing, software engineering, GUI design, and data visualization.
Modeling the electrode-skin-interface (ESI) for motion artifacts reduction
January 1, 2014 – April 1, 2014
Key activities: Modeling the electrode-skin-interface by injecting a known signal into skin and measuring the output. Key techniques: Biomedical signal acquisition & processing, and physical modelling.
Motion artifacts reduction in capacitive biopotential measurements
May 1, 2013 – January 1, 2014
Key activities: Evaluating and comparing the performance of two existing methods for reducing motion artifacts in capacitive biopotential measurements. Key techniques: Biomedical signal processing, dynamic modelling.
Fetal arrhythmia detection on abdominal fetal ECG
September 1, 2012 – May 1, 2013
Key activities: Detecting the fetal arrhythmia according to the fetal heart rate variability. Key techniques: Biomedical signal processing, wavelet, and peaks detection.
Research on ECG pre-processing and QRS detection (Master graduation project)
July 1, 2011 – July 1, 2012
Key activities: I proposed a new type of zero phase shift filter based on the discrete cosine transform to filter ECG. The QRS detection consisted of a band-pass filter, a sample-by-sample differentiation, and an adaptive threshold. Key techniques: Biomedical signal processing, peaks detection.
Automated detection of Myocardial Infarction (MI) on 12-lead ECG (University project)
October 1, 2010 – June 1, 2011
Key activities: Classifying ECG recordings into MI and non-MI using three types of classifiers (i.e. SVM, NN, and GMM). Key techniques: Machine learning, pattern recognition, and biomedical signal processing.
Intelligent television (Industrial project).
September 1, 2009 – October 1, 2010
Key activities: I developed two face detection algorithms (Skin-color Segmentation, Adaboost) and two face recognition algorithms (Eigenface, Hidden Markov model) for this project. Key techniques: Machine learning, pattern recognition, image processing.
Wireless image transmission (Bachelor graduation project)
July 1, 2008 – July 1, 2009
Key activities: Transmitting images wirelessly to monitor the growth process of plants. Key techniques: Circuit design, wireless communication, automated control, and image acquisition.
Automated human detection system (Undergraduate research & training project)
June 1, 2006 – June 1, 2007
Key activities: Detecting the people inflow and outflow of a classroom to calculate the current number of people in the classroom. Key techniques: Circuit design, wireless communication, and automated control.
Risk management for safety critical systems
Eindhoven University of Technology
June 24, 2026 – Present
Training in Writing Articles and Abstracts
Eindhoven University of Technology
June 24, 2026 – Present
Training in Intercultural Communication & Cooperation
Eindhoven University of Technology
June 24, 2026 – Present
Medical Ethics 2015
The school of Medical Physics and Engineering Eindhoven of Eindhoven University of Technology
June 24, 2026 – Present
Scientific Integrity for TOIO's
Eindhoven University of Technology
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a strong academic background with multiple degrees and a diverse project portfolio spanning biomedical signal processing, machine learning, and system engineering. Their professional experience includes roles at Meta, Philips, and eBay, indicating adaptability to different corporate cultures and industries. The progression from Data Scientist to Senior Director and VP of Machine Learning demonstrates ambition and a drive for growth. However, the target role of 'Data Analyst' might be a step down from their recent leadership positions, potentially indicating a mismatch in career trajectory or a desire for a more focused technical role. The breadth of skills and project types suggests an ability to integrate into diverse teams and contribute across various technical domains.
Soft Skills & Operational Fit
The candidate's experience as a team lead and VP suggests strong leadership, communication, and collaboration skills. The project descriptions, while concise, indicate an ability to work on complex, interdisciplinary problems. The certifications in 'Risk management for safety critical systems' and 'Intercultural Communication & Cooperation' further support a structured and collaborative approach to work. However, without specific psychometric test results, a detailed assessment of work attitude, stress handling, and team collaboration is limited.