HEAVY
LIFTERS
Women researchers who manage, interpret and apply big data
By Susan Messina
Photos by Kat Lawrence
At UNC Charlotte, the interdisciplinary School of Data Science captures the evolution of data science and aims to address the growing demand for data scientists in industries ranging from business, professional sports and health care to social science, public service and more.
Work led by researchers from the College of Computing and Informatics, the Belk College of Business, College of Health and Human Services, College of Science, College of Humanities & Earth and Social Sciences and William States Lee College of Engineering is rising to the data science forefront, informing decisions and new directions for related work in both the public and private sectors.
Globally, female data scientists make up just over 20% of all data scientists. Women at UNC Charlotte engaged in this work are making a mark locally, regionally, nationally and internationally through research collaborations and groundbreaking work – and encouraging others to join them in this fast-growing field.
Yuting (Tina) Chen, Ph.D.
Assistant Professor, Engineering Technology and Construction Management / Affiliate Faculty, School of Data Science
“Building a safer tomorrow means not just constructing structures but nurturing the mental well-being of our construction workers, researching railroad trespassing to prevent tragedies, and championing diverse voices, as every effort becomes a beacon of hope for a resilient and secure future.”
Through her research, Tina Chen aims to enhance the resilience of construction companies to elevate their safety standards, and delves into the nuanced factors that influence the mental well-being of construction workers and crafts tailored interventions as solutions. She also addresses a dearth of research related to preventing pedestrian railroad trespassing. These multifaceted areas of research converge through the prism of data science, utilizing techniques such as statistical modeling, social media text mining and machine learning to drive impactful outcomes.
Liyue Fan, Ph.D.
Assistant Professor, Computer Science
“Privacy protection is an important characteristic of trustworthy AI. By integrating privacy research and education, I train next-generation data scientists to unlock the power of AI while ensuring our personal information remains protected.”
Liyue Fan, a recipient of a 2022 NSF CAREER Award, investigates provable privacy protection for data science and artificial intelligence applications in three key areas.
The first is quantifying the unintended leakage of information in emerging applications related to computer vision, federated analysis and health care. Respectively, these involve a field of artificial intelligence that enables computers to derive information from images, videos and other input, and training machine learning models across several devices without centralized data collection.
Next, her research helps develop rigorous privacy-enhancing methods for data sharing and data analysis. And finally, she aims through her work to maximize the utility of privacy-protecting AI, such as for investigating memorization and generalization in deep generative models — by using deep neural networks to discover the underlying distribution of data.
Read more about Fan’s work.
Laura H. Gunn, Ph.D.
Professor, Department of Public Health Sciences / Affiliate Faculty, School of Data Science / Director, Biostatistics Core / Honorary Research Fellow, Imperial College London, School of Public Health, Faculty of Medicine
“A combined individual and team ‘can do’ attitude inspires me. Individual contributions, discoveries, strengths, challenges and voices are essential for creating collaborative, interdisciplinary and innovative solutions to complex public health and data science challenges. The synergies that result when we weave together passions, talents, qualities, skills, backgrounds, experiences and scientific contributions often propel and lift us to ‘shaping what’s next,’ leading to advancing health and making a difference.”
Laura Gunn, who received the inaugural UNC Charlotte School of Data Science Outstanding Data Science Faculty Research Award in 2021, is focused on solving complex public health, health care and medical problems through biostatistical, epidemiological and data science modeling, interdisciplinary and collaborative work that uses big data at county, state, national and international population levels to identify and address health disparities and advance population health.
Her team’s work on cardiovascular disease risk prediction was the first to demonstrate — over multiple publications using big data — the public health/clinical utility of CVD risk prediction models in UK-based primary care settings. They expanded this work across continents, including North America, informing the development of new CVD risk SMART (Second Manifestations of ARTerial disease)-based monitoring guidelines by the European Society of Cardiology for 21 countries.
In addition, she and her collaborators were first to show positive health outcomes with two large-scale UK-based National Health Service health policy programs to incentivize routine primary care diabetic screenings. And research on biostatistical modeling of youth physical activity is currently funded by a five-year, $2.9 million National Institutes of Health SKyRoCKeT study for which she serves as co-principal investigator with Catrine Tudor-Locke, dean, College of Health and Human Services.
Recent articles about Gunn’s research appear in European Journal of Preventive Cardiology and Journal of the Royal Society of Medicine.
Shaoyu Li, Ph.D.
Associate Professor, Mathematics and Statistics / Affiliate Faculty, School of Data Science
“The evolution of data science reveals its vast potential, from its humble beginnings to its current state and future prospects. Take the plunge into this dynamic field, staying curious, focused, and committed to continuous hard work. In the journey of data science, you hold the key to achieving your aspirations.”
In her research area of statistical genetics and genomics. Shaoyu Li pinpoints the diversity of cells in human tissues and how it relates to human diseases. Using nonnegative matrix factorization, deep neural networks and various machine learning algorithms, she offers crucial insights into disease comprehension, treatment and prevention.
Specifically, Li’s lab has developed computational algorithms to decipher cell-specific transcriptional changes in the brains of patients with Alzheimer’s Disease. Supported by a two-year, National Institutes of Health R01 grant of nearly $600,000, her team is harnessing the wealth of bulk tissue transcriptome data for uncovering key pathways and molecules essential for the exploration and discovery of therapeutic targets to help fill in the knowledge gaps surrounding cell-specific transcriptional changes in Alzheimer’s Disease.
In addition, Li is involved in collaborative research across the Charlotte area, spanning study design, data collection and monitoring, extending to analysis and results interpretation across diverse research domains. In partnership with Donna Kazemi at the University of South Carolina, she is addressing problematic alcohol and cannabis use among college students, an initiative that includes collaboration with a local business, emphasizing the application of digital interventions.
Shannon Reid, Ph.D.
Associate Professor, Criminal Justice and Criminology / Affiliate Faculty, School of Data Science
“Empowering women in data science means understanding the impact of diverse perspectives that drive meaningful change.”
Shannon Reid works at the intersection of technology and public safety with projects that focus on reducing crime, while increasing community buy-in and trust in AI. She serves as chief executive officer of Chimeras, which got its start from an NSF grant that focused on developing AI-based video analytics to increase public safety. This technology is currently being piloted in locations around the Charlotte area, demonstrating the strong partnerships that exist between the University and the community, particularly with law enforcement and public safety entities such as the Charlotte-Mecklenburg Police Department, the Pineville Police Department, the Army Research Office and the National Institute of Justice.
Reid’s research focuses on youth crime and violence, with special attention to youth gangs, online radicalization and polarization, and early interventions for youth violence. Her book, “Alt-Right Gangs: A Hazy Shade of White,” was published by the University of California Press. Her work has been published in journals such as Criminology, the Journal of Interpersonal Violence, Homicide Studies, the Journal of Youth Studies, Legal and Criminal Psychology, and Deviant Behavior. Her research has garnered coverage on National Public Radio and in The Conversation, The Washington Post’s The Monkey Cage and The Crime Report.
Lina Zhou, Ph.D.
Professor of Business Information Systems and Operations Management
“The opportunities for machine intelligence to augment human intelligence are boundless, yet it necessitates governance to prevent misuse.”
Lina Zhou’s research interests span social media analytics, deception detection, knowledge management, biomedical informatics, and intelligent mobile interface. Through her work, she aims to improve decision-making for businesses and individuals by integrating data-driven insights with human expertise and by understanding human behavior and the decision-making process.
In a recent article published in AIS eLibrary, Zhou and her collaborators propose a framework for exploring the inverse of the notion of artificial intelligence empowering machines with human capabilities, that is to use AI to augment human capabilities. The team also aims to identify potential risks and emerging issues in IA design and development to suggest new questions for future IA research and foster its positive impact on humanity.
HEAVY LIFTERS
Women researchers who manage, interpret and apply big data
By Susan Messina
Photos by Kat Lawrence
At UNC Charlotte, the interdisciplinary School of Data Science captures the evolution of data science and aims to address the growing demand for data scientists in industries ranging from business, professional sports and health care to social science, public service and more.
Work led by researchers from the College of Computing and Informatics, the Belk College of Business, College of Health and Human Services, College of Science, College of Humanities & Earth and Social Sciences and William States Lee College of Engineering is rising to the data science forefront, informing decisions and new directions for related work in both the public and private sectors.
Globally, female data scientists make up just over 20% of all data scientists. Women at UNC Charlotte engaged in this work are making a mark locally, regionally, nationally and internationally through research collaborations and groundbreaking work – and encouraging others to join them in this fast-growing field.
Yuting (Tina) Chen, Ph.D.
Assistant Professor, Engineering Technology and Construction Management / Affiliate Faculty, School of Data Science
“Building a safer tomorrow means not just constructing structures but nurturing the mental well-being of our construction workers, researching railroad trespassing to prevent tragedies, and championing diverse voices, as every effort becomes a beacon of hope for a resilient and secure future.”
Through her research, Tina Chen aims to enhance the resilience of construction companies to elevate their safety standards, and delves into the nuanced factors that influence the mental well-being of construction workers and crafts tailored interventions as solutions. She also addresses a dearth of research related to preventing pedestrian railroad trespassing. These multifaceted areas of research converge through the prism of data science, utilizing techniques such as statistical modeling, social media text mining and machine learning to drive impactful outcomes.
Liyue Fan, Ph.D.
Assistant Professor, Computer Science
“Privacy protection is an important characteristic of trustworthy AI. By integrating privacy research and education, I train next-generation data scientists to unlock the power of AI while ensuring our personal information remains protected.”
Liyue Fan, a recipient of a 2022 NSF CAREER Award, investigates provable privacy protection for data science and artificial intelligence applications in three key areas.
The first is quantifying the unintended leakage of information in emerging applications related to computer vision, federated analysis and health care. Respectively, these involve a field of artificial intelligence that enables computers to derive information from images, videos and other input, and training machine learning models across several devices without centralized data collection.
Next, her research helps develop rigorous privacy-enhancing methods for data sharing and data analysis. And finally, she aims through her work to maximize the utility of privacy-protecting AI, such as for investigating memorization and generalization in deep generative models — by using deep neural networks to discover the underlying distribution of data.
Read more about Fan’s work.
Laura H. Gunn, Ph.D.
Professor, Department of Public Health Sciences / Affiliate Faculty, School of Data Science / Director, Biostatistics Core / Honorary Research Fellow, Imperial College London, School of Public Health, Faculty of Medicine
“A combined individual and team ‘can do’ attitude inspires me. Individual contributions, discoveries, strengths, challenges and voices are essential for creating collaborative, interdisciplinary and innovative solutions to complex public health and data science challenges. The synergies that result when we weave together passions, talents, qualities, skills, backgrounds, experiences and scientific contributions often propel and lift us to ‘shaping what’s next,’ leading to advancing health and making a difference.”
Laura Gunn, who received the inaugural UNC Charlotte School of Data Science Outstanding Data Science Faculty Research Award in 2021, is focused on solving complex public health, health care and medical problems through biostatistical, epidemiological and data science modeling, interdisciplinary and collaborative work that uses big data at county, state, national and international population levels to identify and address health disparities and advance population health.
Her team’s work on cardiovascular disease risk prediction was the first to demonstrate — over multiple publications using big data — the public health/clinical utility of CVD risk prediction models in UK-based primary care settings. They expanded this work across continents, including North America, informing the development of new CVD risk SMART (Second Manifestations of ARTerial disease)-based monitoring guidelines by the European Society of Cardiology for 21 countries.
In addition, she and her collaborators were first to show positive health outcomes with two large-scale UK-based National Health Service health policy programs to incentivize routine primary care diabetic screenings. And research on biostatistical modeling of youth physical activity is currently funded by a five-year, $2.9 million National Institutes of Health SKyRoCKeT study for which she serves as co-principal investigator with Catrine Tudor-Locke, dean, College of Health and Human Services.
Recent articles about Gunn’s research appear in European Journal of Preventive Cardiology and Journal of the Royal Society of Medicine.
Shaoyu Li, Ph.D.
Associate Professor, Mathematics and Statistics / Affiliate Faculty, School of Data Science
“The evolution of data science reveals its vast potential, from its humble beginnings to its current state and future prospects. Take the plunge into this dynamic field, staying curious, focused, and committed to continuous hard work. In the journey of data science, you hold the key to achieving your aspirations.”
In her research area of statistical genetics and genomics. Shaoyu Li pinpoints the diversity of cells in human tissues and how it relates to human diseases. Using nonnegative matrix factorization, deep neural networks and various machine learning algorithms, she offers crucial insights into disease comprehension, treatment and prevention.
Specifically, Li’s lab has developed computational algorithms to decipher cell-specific transcriptional changes in the brains of patients with Alzheimer’s Disease. Supported by a two-year, National Institutes of Health R01 grant of nearly $600,000, her team is harnessing the wealth of bulk tissue transcriptome data for uncovering key pathways and molecules essential for the exploration and discovery of therapeutic targets to help fill in the knowledge gaps surrounding cell-specific transcriptional changes in Alzheimer’s Disease.
In addition, Li is involved in collaborative research across the Charlotte area, spanning study design, data collection and monitoring, extending to analysis and results interpretation across diverse research domains. In partnership with Donna Kazemi at the University of South Carolina, she is addressing problematic alcohol and cannabis use among college students, an initiative that includes collaboration with a local business, emphasizing the application of digital interventions.
Shannon Reid, Ph.D.
Associate Professor, Criminal Justice and Criminology / Affiliate Faculty, School of Data Science
“Empowering women in data science means understanding the impact of diverse perspectives that drive meaningful change.”
Shannon Reid works at the intersection of technology and public safety with projects that focus on reducing crime, while increasing community buy-in and trust in AI. She serves as chief executive officer of Chimeras, which got its start from an NSF grant that focused on developing AI-based video analytics to increase public safety. This technology is currently being piloted in locations around the Charlotte area, demonstrating the strong partnerships that exist between the University and the community, particularly with law enforcement and public safety entities such as the Charlotte-Mecklenburg Police Department, the Pineville Police Department, the Army Research Office and the National Institute of Justice.
Reid’s research focuses on youth crime and violence, with special attention to youth gangs, online radicalization and polarization, and early interventions for youth violence. Her book, “Alt-Right Gangs: A Hazy Shade of White,” was published by the University of California Press. Her work has been published in journals such as Criminology, the Journal of Interpersonal Violence, Homicide Studies, the Journal of Youth Studies, Legal and Criminal Psychology, and Deviant Behavior. Her research has garnered coverage on National Public Radio and in The Conversation, The Washington Post’s The Monkey Cage and The Crime Report.
Lina Zhou, Ph.D.
Professor of Business Information Systems and Operations Management
“The opportunities for machine intelligence to augment human intelligence are boundless, yet it necessitates governance to prevent misuse.”
Lina Zhou’s research interests span social media analytics, deception detection, knowledge management, biomedical informatics, and intelligent mobile interface. Through her work, she aims to improve decision-making for businesses and individuals by integrating data-driven insights with human expertise and by understanding human behavior and the decision-making process.
In a recent article published in AIS eLibrary, Zhou and her collaborators propose a framework for exploring the inverse of the notion of artificial intelligence empowering machines with human capabilities, that is to use AI to augment human capabilities. The team also aims to identify potential risks and emerging issues in IA design and development to suggest new questions for future IA research and foster its positive impact on humanity.