Pedro Henrique Ribeiro
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Pedro Henrique Ribeiro Email & Phone Number

Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering at Massachusetts General Hospital
Location: Greater Boston, United States 10 work roles 4 schools
1 work email found @seas.upenn.edu LinkedIn matched
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Role
Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering
Location
Greater Boston, United States

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Pedro Henrique Ribeiro is listed as Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering at Massachusetts General Hospital, based in Greater Boston, United States. AeroLeads shows a work email signal at seas.upenn.edu and a matched LinkedIn profile for Pedro Henrique Ribeiro.

Pedro Henrique Ribeiro previously worked as Data Scientist at Massachusetts General Hospital and Data Scientist at Beth Israel Deaconess Medical Center. Pedro Henrique Ribeiro holds Master Of Science In Engineering, Bioengineering And Biomedical Engineering from University Of Pennsylvania.

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Profile bio

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.

Listed skills include Microsoft Office, Powerpoint, Social Media, Microsoft Excel, and 19 others.

Current workplace

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Massachusetts General Hospital
Massachusetts General Hospital
Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering
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10 roles

Pedro Henrique Ribeiro work experience

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Data Scientist

Current

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.

Nov 2024 - Present

Research Data Scientist

Los Angeles, Ca, Us

Jun 2024 - Nov 2024

Programmer / Analyst

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.

Jan 2022 - Jun 2024

Graduate Research Assistant

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.

Aug 2018 - May 2021

Research Intern

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.

May 2017 - Aug 2017

Research Intern

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.

May 2016 - Aug 2016

Research Assistant

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.

Aug 2015 - May 2016

Research Intern

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.

May 2015 - Aug 2015
4 education records

Pedro Henrique Ribeiro education

Master Of Science In Engineering, Bioengineering And Biomedical Engineering

University Of Pennsylvania

Bachelor'S Degree, Computer Science

Oberlin College

High School

School Year Abroad (Sya)

Education record

Belmont Hill School
FAQ

Frequently asked questions about Pedro Henrique Ribeiro

Quick answers generated from the profile data available on this page.

What company does Pedro Henrique Ribeiro work for?

Pedro Henrique Ribeiro works for Massachusetts General Hospital.

What is Pedro Henrique Ribeiro's role at Massachusetts General Hospital?

Pedro Henrique Ribeiro is listed as Data Scientist @ MGH, BI | Clinical Research, Automated Interpretable Machine Learning, Evolutionary Algorithms | UPenn MSE Bioengineering at Massachusetts General Hospital.

What is Pedro Henrique Ribeiro's email address?

AeroLeads has found 1 work email signal at @seas.upenn.edu for Pedro Henrique Ribeiro at Massachusetts General Hospital.

Where is Pedro Henrique Ribeiro based?

Pedro Henrique Ribeiro is based in Greater Boston, United States while working with Massachusetts General Hospital.

What companies has Pedro Henrique Ribeiro worked for?

Pedro Henrique Ribeiro has worked for Massachusetts General Hospital, Beth Israel Deaconess Medical Center, Broad Institute Of Mit And Harvard, Cedars-Sinai, and University Of Pennsylvania.

How can I contact Pedro Henrique Ribeiro?

You can use AeroLeads to view verified contact signals for Pedro Henrique Ribeiro at Massachusetts General Hospital, including work email, phone, and LinkedIn data when available.

What schools did Pedro Henrique Ribeiro attend?

Pedro Henrique Ribeiro holds Master Of Science In Engineering, Bioengineering And Biomedical Engineering from University Of Pennsylvania.

What skills is Pedro Henrique Ribeiro known for?

Pedro Henrique Ribeiro is listed with skills including Microsoft Office, Powerpoint, Social Media, Microsoft Excel, Microsoft Word, Spanish, Portuguese, and Java.

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