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Marco Wu, Ph.D.

a versatile and accomplished statistician and data scientist with a wealth of experience and expertise. With over a dozen publications and patents (pending) to his name, he is a highly respected engineer, scholar, and inventor.

As a devoted dad, Marco is passionate about using his skills and knowledge to tell compelling stories with data from multiple perspectives. He has excelled in a variety of roles and teams, and his core competencies include data science, signal processing, and optimization strategy.


✔ Cutting-edge engineering methods
✔ Team-focused
✔ Exceptional delivery

My philosophy is to build long-term relationships with my clients by providing exceptional service and ensuring their satisfaction. I have been trusted by my clients for the following key reasons:

  • Affordable project packages: I offer competitive pricing, includes data analysis, results, improvement suggestions, source codes, a report, and meetings.

  • Confidentiality: I always sign a non-disclosure agreement to protect my clients' sensitive information.

  • Fast response times: I prioritize timely communication and respond quickly to my clients' inquiries.

  • Clear explanations: I present results in a clear and easy-to-understand manner, avoiding technical jargon.

  • Personalized approach: I take a tailored approach to each project, ensuring that my solutions are specific to the clients' needs and problems.

  • Expertise: I have a strong theoretical background and extensive industry experience, which I use to deliver high-quality results.

Overall, my goal is to provide my clients with the best possible consulting experience and help them achieve their goals.


Vikash Gayah
Assistant Professor
Penn State U.

I had Marco help me on a javascript project. He is very knowledgeable in programming and used only a few hours to complete the task. Marco earns my recommendation.

Daniel Marlow,
Crawford Evans Class of 1911 Professor of Physics
Princeton University

Marco took on a small project to analyze data from a radiotelescope that we use for educational purposes. He did a fantastic job of it and delivered a script that worked perfectly right out of the box. The approach Marco took was highly creative and reduced the run time relative to the previous algorithm by more than a factor of 100.

Whelton Miller,
Assistant Professor,
Loyola University
School of Medicine

Marco always amazed me with his industry insight and unique approaches to solving problems. He is wonderful to work with, and has unique expertise in Python, MATLAB, Machine Learning and data analysis. He helped me on a National Science Foundation proposal and will be my data scientist if the funding is approved.

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Recent Projects

Most projects are required Non-disclosure agreements (NDA), so I cannot disclosure any information. The following are some recent projects that no NDA was required.

1 / Human brain signal (EEG) classification for Brain-Computer interface

We identified patterns in EEG signals that can be used to control devices, improving the accuracy and reliability of brain-computer interfaces. Our findings have the potential to benefit people with disabilities and enable them to achieve greater independence and autonomy. By applying our research to the development of new control mechanisms, we can unlock the full potential of the human brain and enhance the capabilities of assistive technology.

2 / Data analysis of Moon to Earth Distance using spectrogram

We used the reflection signal of electromagnetic waves to transform the signal into a time-power spectrum. By identifying the characteristics in the spectrum, we were able to accurately calculate the distance between the Moon and Earth.

3 / Detection of obstructive sleep apnea through SpO2 signal features

We developed a deep learning model that uses blood oxygen level (SpO2) data to classify cases of obstructive sleep apnea. Our approach leverages advanced neural network techniques to achieve high levels of accuracy and reliability. This innovative model has the potential to improve the diagnosis and management of sleep apnea, and could have far-reaching implications for the field of sleep medicine.

4 / A comprehensive review of MACD technical indicator in US Stock market  

We used optimization models to identify the best indicator to pair with the Moving Average Convergence Divergence (MACD) indicator, and also found the optimal time windows for using these indicators together. Our research revealed valuable insights that can help traders make more informed decisions

5 / Predict different lower limb actions based on hip joint movement

We developed a predictive model that uses hip kinematics data to accurately classify and predict lower limb movements. Our approach leverages multi-level machine learning classifiers to achieve high levels of accuracy and robustness. This innovative model has the potential to improve the diagnosis and treatment of movement disorders and other conditions that affect lower limb function.

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