Pedro Henrique Ribeiro

Pedro Henrique Ribeiro Email and Phone Number

Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering @ Massachusetts General Hospital
Pedro Henrique Ribeiro's Location
Greater Boston, United States, United States
Pedro Henrique Ribeiro's Contact Details

Pedro Henrique Ribeiro personal email

About Pedro Henrique Ribeiro

A data scientist who combines a passion for science with strong skills in developing data tools and resources. A fast learner who can adapt to new environments, projects, and domains. A collaborative team player and proficient communicator who can work effectively with scientists and engineers from different backgrounds and explain technical concepts in a clear and accessible way. Self-motivated and capable of taking independent ownership of projects and delivering high-quality results.🟣 Machine Learning Research and Software Development: Currently leading development on TPOT2, an open-source Python package that automates the construction and optimization of graph-based machine learning pipelines using genetic algorithms. Based on existing work on the original TPOT, I rebuilt the package from scratch to increase performance, add new features, and make it easier to maintain and extend. Currently working on optimizations for interpretable machine learning.🟣 Strong Communication Skills: Developed through extensive experience working in collaborative, multidisciplinary teams. I have become skilled at effectively communicating complex ideas and concepts. I have presented my research at the national ABRCMS conference and several times at my local institutions. 🟣 Big Data: Worked on machine learning projects using large-scale datasets such as the 3 TB Google AudioSet and the Steinmetz et al. 2019 Neuropixels recordings, which include approximately 30,000 neurons from 42 brain regions.🟣 Consulting: At the University of Pennsylvania, I conducted market research with the Penn Biotech Group. I also participated in the Penn Bio Launch program as a Biotech Fellow. I worked with a multi-disciplinary team during a 10-week workshop to develop a business plan to translate research from a lab into a biotechnology startup.🟣 Neuroscience: Worked in several computational neuroscience labs from 2015 through 2021. This includes three years of graduate-level research at the University of Pennsylvania with Dr. Konrad Kording as well as several internships at top institutions such as MIT, Boston University, Oberlin College, and the University of Florida.🟣 Love of learning: I am always excited to keep up with the latest technologies and learn the best tools for the job. I also make a hobby of learning skills outside my immediate domain. My current side-project is learning interactive graphics and OpenGL.

Pedro Henrique Ribeiro's Current Company Details
Massachusetts General Hospital

Massachusetts General Hospital

View
Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering
Pedro Henrique Ribeiro Work Experience Details
  • Massachusetts General Hospital
    Data Scientist
    Massachusetts General Hospital Nov 2024 - Present
    Boston, Ma, Us
    This position is joint with the Massachusetts General Hospital's Division of Cardiology and Beth Israel Deaconess Medical Center's CardioVascular Institute. I will also have an appointment as a visiting researcher at the Broad Institute, where I will collaborate on projects.• Leading analyses to examine the association of clinical and electrocardiographic traits with cardiovascular outcomes.• Building and refining a pregnancy electronic health record (EHR) cohort dataset.• Co-leading data abstraction, QC, and analyses for a pregnancy cohort of individuals.• Collaborating with a multidisciplinary team of clinicians, scientists, and trainees across various institutions to develop and apply advanced analytics solutions in healthcare.• Leading machine learning-driven analyses for multiple clinical and translational research projects focused on cardiovascular disease.• Leveraging innovative approaches to analyze complex, high-dimensional databases of human data.
    View
  • Beth Israel Deaconess Medical Center
    Data Scientist
    Beth Israel Deaconess Medical Center Nov 2024 - Present
    Boston, Ma, Us
    View
  • Broad Institute Of Mit And Harvard
    Visiting Researcher
    Broad Institute Of Mit And Harvard Nov 2024 - Present
    Cambridge, Ma, Us
    View
  • Cedars-Sinai
    Research Data Scientist
    Cedars-Sinai Jun 2024 - Nov 2024
    Los Angeles, Ca, Us
    View
  • Cedars-Sinai
    Programmer / Analyst
    Cedars-Sinai Jan 2022 - Jun 2024
    Los Angeles, Ca, Us
    Department of Computational Biomedicine and Center for Artificial Intelligence.•Initiated and led the development of TPOT2, an open-source Python package that uses evolutionary algorithms to automate the construction and tuning of machine learning pipelines. Six researchers in our group actively use this tool in their research on topics such as fairness in AI, genetics, data cleaning, evolutionary algorithms, and AutoML. I presented this project at the Genetic Programming Theory And Practice 2023.• Maintained the TPOT Python package for AutoML (over 9,400 stars on GitHub and over 300,000 downloads). Fixed bugs and kept it up-to-date with the latest versions of its dependencies.•Significantly improved workflow and feature development of TPOT2 by developing a modular design pattern, creating a prioritized roadmap of tasks (bugs, optimizations, features), suggesting task assignments based on experience and interest, and developing parallelized benchmarking scripts. Working with three developers and two postdocs on maintaining and improving the package.•Conducting independent research on evolutionary algorithms to optimize TPOT2 to generate interpretable models via improved feature selection and feature engineering.•Collaborated with scientists to enhance their research projects by applying data science techniques and conducting initial exploratory analysis.•Built predictive machine learning models for Amyotrophic Lateral Sclerosis (ALS) severity and predicting major adverse cardiovascular events (MACE).•Used PyTorch deep learning models to segment and detect gallstones using limited imaging data.•Mentored a Master student intern in designing and executing projects on automated data cleaning and feature engineering.•Wrote a comprehensive 22-page document for effectively using our High-Performance Computing cluster, including SLURM, SGE, Linux/Bash, Python, Jupyter notebooks, and VSCode guides.•Tested, benchmarked, and evaluated bioinformatics software.
    View
  • University Of Pennsylvania
    Graduate Research Assistant
    University Of Pennsylvania Aug 2018 - May 2021
    Philadelphia, Pa, Us
    Conducted graduate research under Dr. Konrad Kording. • Developed Pytorch-based deep learning architectures to build predictive models of behavior from neural recordings. Used the models to analyze the representation of behaviors in the brain.• Investigated the patterns of activity of the neurons in the Frontal Eye Field using MATLAB. Work culminated in a Master's Thesis.Other activitiesPenn Biotech Group Healthcare Consulting:• Provided consulting services to a large pharmaceutical company on a disease management project regarding a gastrointestinal disorder.Penn Bio Launch: Biotech Fellow:• Worked with a multi-disciplinary team during a 10-week workshop to develop a business plan to translate research from a lab into a biotechnology startup.
    View
  • Massachusetts Institute Of Technology
    Research Intern
    Massachusetts Institute Of Technology May 2017 - Aug 2017
    Cambridge, Ma, Us
    Worked with graduate student Jenelle Feather in Josh McDermott's Laboratory for Computational Audition as part of the MSRP - Bio summer program at MIT• Developed parallelized Python scripts to extract and preprocess audio from YouTube to create a large 3TB data set of natural sounds (labeled by Google AudioSet). • Built an HDF5 database to store labeled audio clips that will be used broadly by the McDermott lab for deep learning and neuroscience research.• Trained a Tensorflow convolutional deep learning model on a multiclass classification task using the 3TB Google Audioset to identify which of 527 possible natural sound categories were present in audio clips, achieving a 90\% top-15 accuracy.• Work was done on a Linux-based high performance compute (HPC) cluster.• Presented at ABRCMS 2017, and the Oberlin Celebration of Undergraduate Research 2017.
    View
  • Boston University
    Research Intern
    Boston University May 2016 - Aug 2016
    Boston, Ma, Us
    Worked under Ayoub Daliri in Frank Guenther's SpeechLab during the 2016 USPIN summer program.• Implemented a MATLAB-based algorithm to quantitatively assess the biological plausibility and accuracy of computational models of full brain networks through comparison to functional neuroimaging data. Work was done on a high-performance computing cluster.• Presented at ABRCMS 2016 (ABRCMS Travel Award) and the Oberlin Celebration of Undergraduate Research 2016.
    View
  • Oberlin College
    Research Assistant
    Oberlin College Aug 2015 - May 2016
    Oberlin, Oh, Us
    Worked in Leslie Kwakye's multisensory neuroscience lab at Oberlin College.• Designed, developed, and ran participants on a Python based virtual reality attentional cueing task for the Oculus Rift that sought to test whether a realistic, immersive environment would lead to enhanced behavioral responses. Animated stock models and built a 3D forest environment using 3ds Max. • Performed statistical analysis of data which showed stronger responses to visual cues confirming conclusions from other studies that the brain prioritizes visual to auditory cues in spatial location.
    View
  • University Of Florida
    Research Intern
    University Of Florida May 2015 - Aug 2015
    Gainesville, Florida, Us
    Worked in Dr. Paul W Davenport's Physiology lab at the University of Florida• Investigated the activity of central pattern generator neurons involved in breathing and swallowing located in the medulla of a cat. This research could help find treatments for people with difficulty swallowing, dysphagia, due to damage sometimes caused by stroke to this area of the brain.• Used Spike2 to perform waveform analysis on extracellular recordings of a cat during breathing and induced swallowing. Sorted the results based on patterns of activity and analyzed the results.
    View

Pedro Henrique Ribeiro Skills

Microsoft Office Powerpoint Social Media Microsoft Excel Microsoft Word Spanish Portuguese Java Vizard Python C Matlab Research Statistical Modeling Machine Learning Artificial Intelligence Deep Learning Information Theory Data Mining Probabilistic Models Tensorflow Psychophysics Animal Husbandry

Pedro Henrique Ribeiro Education Details

  • University Of Pennsylvania
    University Of Pennsylvania
    Bioengineering And Biomedical Engineering
  • Oberlin College
    Oberlin College
    Computer Science
  • School Year Abroad (Sya)
    School Year Abroad (Sya)
    High School
  • Belmont Hill School
    Belmont Hill School

Frequently Asked Questions about Pedro Henrique Ribeiro

What company does Pedro Henrique Ribeiro work for?

Pedro Henrique Ribeiro works for Massachusetts General Hospital

What is Pedro Henrique Ribeiro's role at the current company?

Pedro Henrique Ribeiro's current role is Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering.

What is Pedro Henrique Ribeiro's email address?

Pedro Henrique Ribeiro's email address is pe****@****ail.com

What schools did Pedro Henrique Ribeiro attend?

Pedro Henrique Ribeiro attended University Of Pennsylvania, Oberlin College, School Year Abroad (Sya), Belmont Hill School.

What skills is Pedro Henrique Ribeiro known for?

Pedro Henrique Ribeiro has skills like Microsoft Office, Powerpoint, Social Media, Microsoft Excel, Microsoft Word, Spanish, Portuguese, Java, Vizard, Python, C, Matlab.

Free Chrome Extension

Find emails, phones & company data instantly

Find verified emails from LinkedIn profiles
Get direct phone numbers & mobile contacts
Access company data & employee information
Works directly on LinkedIn - no copy/paste needed
Get Chrome Extension - Free

Aero Online

Your AI prospecting assistant

Download 750 million emails and 100 million phone numbers

Access emails and phone numbers of over 750 million business users. Instantly download verified profiles using 20+ filters, including location, job title, company, function, and industry.