16 Data Scientists Making Vital Breakthroughs in Healthcare

By PokitDok Team,

Data scientists are some of the healthcare world’s most important people. They’re able to mine huge datasets and develop insights that really matter. Their findings have a profound effect on how we understand, improve, deliver and pay for healthcare.

Here are 16 data scientists doing amazing work to advance the field.

Daniella Perlroth, Lyra Health

Daniella Perlroth is the chief data scientist at Lyra Health, which helps people find care for mental health issues and substance abuse. “Lyra is tackling complex problems,” writes James Slavet at Greylock Partners. “They are applying software and data science to build products that will dramatically lower healthcare costs and improve human lives.”

Severence MacLaughlin, Cognizant Technology Solutions

Dr. MacLaughlin brings a background in competitive intelligence, artificial reproductive technologies, and financial research to Cognizant Technology Solutions, which provides information technology, consulting, and business process services, to help companies build stronger businesses. He joined Cognizant as a master data scientist earlier this year after eight years as a research fellow at the University of South Australia, as well as directorships with the American Red Cross.

Kate Robertus Vilain, Saint Luke's Health System

Kate Robertus Vilain is the manager of data coordination at Saint Luke's Health System, where she focuses on quality-of-life data for cardiovascular treatment. She manages several databases to help Saint Luke’s understand what it’s spending to deliver high-quality healthcare.

Gopinath Sundaramurthy, IBM Watson

Gopinath Sundaramurthy works at IBM Watson Health, developing systems to analyze and act on data from personal health trackers, health records, clinical trials, and other sources. Before joining IBM, he spent seven years as a researcher, developing a framework to identify disease-related genes and biomarkers. He used models and predictive tools to capture emergent biological network properties.


Shameer Khader, Mount Sinai Health System

A data scientist for biomedical and healthcare data at Mount Sinai Health System, Dr. Khader’s work explores human disease biology, personal genomics, biomedical informatics, drug repositioning, and individualized medicine. He is also working on initiatives allowing healthcare providers to implement better electronic medical records.

Paul Bradley, ZirMed

Paul Bradley is the chief data scientist at ZirMed, which helps hospitals, clinics, and providers manage their revenue cycles using predictive modeling. “Predictive modeling empowers organizations to ask fundamentally different questions than they can ask with software built of static, manually created rules,” Bradley told Becker’s Health IT & CIO Review.

Michael Draugelis, Penn Medicine

Michael Draugelis is the chief data scientist at Penn Medicine, where his goal is to “revolutionize patient value through data-driven products.” Draugelis explores a variety of datasets including EHRs, EEGs, and infrared sensors. His years of experience prior to Penn Medicine include system integration, signal processing, and work on the Hubble Space Telescope.

Phillip Wallis, Cambia Health Solutions

A data scientist at Cambia Health Solutions, Phillip Wallis works “to predict life events, identify fraud, waste and abuse, forecast costs / trends, and link records across multiple diverse data sources.” He brings years of healthcare, education, telecom, and energy experience to Cambia Health Solutions. Cambia includes 20 companies, all of which invest in and promote innovations helping to create a “person-focused and economically sustainable system” of healthcare.

Robert Yerex, University of Virginia Health System

Senior data scientist at University of Virginia Health System, Robert Yerex’s career spans more than 30 years in applied statistics, econometrics, and data science. He joined UVA Health System in 2014 after working as a senior data mining scientist at the Nike Sports Research Lab. His work helps care providers and coordinators respond quickly to any patients who are identified as at-risk.

Manuel Amunategui, Providence Health & Services

Manuel Amunategui is a founding member of Providence Health & Services’ Healthcare Intelligence Data Science Group. He focuses on “applying advanced analytic techniques and predictive analytics to important problems within the organization.” Before he moved into using predictive analytics to improve patients’ lives, Amunategui was a developer on Wall Street.


Darcy Davis, Advocate Health Care

Darcy Davis is a data scientist at Advocate Health Care, where she focuses on mining health data to create “value-centric population health solutions.” Her work combines network analysis and data mining to create valuable insights. She uses these insights to explore everything from patient risk to understanding what roles genes play in specific diseases.

Brandon Barber, Valence Health

Brandon Barber leads the analytics and product innovation efforts at Valence Health. Valence provides consulting services, tech platforms, and operational services for healthcare providers. Barber’s work has helped physicians use big data to better manage their patients, assisted executive teams in identifying growth areas, and created accurate pricing models for Valence Health.

Zachary Anglin, Ascension Information Services

Zachary Anglin is helping Ascension create a best-in-class data science center for transforming healthcare. He’s also providing valuable, data-driven insights for Ascension’s clients. Ascension announced it was working with several major healthcare providers and organizations to promote interoperability across the American healthcare system. The coalition of 17 EHR vendors has committed to developing “federally recognized, national interoperability standards and practices and adopt best practices, including those related to privacy and security.”

Casey Bennett, Faros Healthcare & Centerstone Research Institute

Casey Bennett is a data scientist exploring artificial intelligence and robotics. He works with two organizations:

His current interests include using robots to treat elderly patients with chronic illnesses, robots that “can display human-like facial expressions” and using AI to simulate clinical decision-making in chronic illness.

Binal Patel, Jvion

Jvion data scientist and engineer Binal Patel builds enterprise-level data products using statistical modeling, natural language processing, and machine learning. Jvion’s award-winning platform, RegEvis, is designed to predict a patient’s risk of developing an illness or a condition long before the symptoms even occur. The platform, “is built on top of a patient-phenotype big data platform that combines advanced statistics, evidence-based metrics, and deep machine intelligence to predict and stop the loss of lives and waste of resources.”

Bryan Smith, PokitDok

Bryan Smith is changing the data silos of healthcare at PokitDok. With a PhD in neuroscience, he specializes in advanced analytics, machine learning, and interactive data visualization methods. Bryan is instrumental in helping PokitDok extract insight on financial trends and behavioral data patterns in healthcare.

All of these data scientists are in a position to push forward the frontiers of our industry, elevate some important data-driven insights, and ultimately find new ways for care providers to achieve better health outcomes for patients.

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The opinions expressed in this blog are of the authors and not of PokitDok's. The posts on this blog are for information only, and are not intended to substitute for a doctor-patient or other healthcare professional-patient relationship nor do they constitute medical or healthcare advice.

  Tags: Dev, Health Innovation

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