Faculty Research & Focus Areas
WPI Data Science researchers are exploring every aspect of this burgeoning field. Together, they innovate Data Science techniques and technologies, and their applications fuel breakthroughs that have direct, real-world impact. These state-of- the-art analytics tools allow users to explore data spurring advances in digital health, genetic analysis, educational software, financial trading, and more. Talented graduate students also have frequent opportunities for paid research positions, fellowships and industrial sponsorships. The students are privileged to participate in big data research projects and gain in-the- field experience, learning to turn raw data into actionable information.
Research Focus Areas
Faculty across disciplines work on shared research projects in data science areas as diverse as:
- High performance data analytics
- Bioinformatics and genomic databases
- Business intelligence and predictive analytics
- Data mining and knowledge discovery
- Digital Health
- Deep Learning algorithms
- Educational data mining
- Fake news detection
- Financial decision-making
- Fraud detection
- Generative artificial intelligence
- Healthcare data analytics
- Large-scale data management and infrastructure
- Natural Language Processing (NLP)
- Numerical and statistical data analysis
- Optimization and prescriptive analytics
- Urban computing
- Signal processing and information theory
- Social media analytics
- Statistical and machine learning
- Visual analytics of large data sets
Faculty News & Research Highlights
AI and Fairness:
When it comes to fairness, artificial intelligence (AI) is imperfect.
But Elke Rundensteiner, William Smith Dean's Professor in the Department of Computer Science and founding director of the Data Science program at WPI, and her students are developing a way to address this problem with algorithms that help ensure fairness in aggregated rankings that impact people in profound ways. The work has been supported by a grant of nearly $500,000 from the National Science Foundation.
NSF Grant to Study How Humans Interact With Artificial Intelligence
Roee Shraga, assistant professor of computer science and data science at Worcester Polytechnic Institute (WPI), has received $175,000 from the National Science Foundation to scrutinize the human aspects of data discovery and integration. The research project aims to explore the critical role of human involvement in data preparation processes to identify and address biases that automated systems may fail to detect.
Seyed Zekavat Leads $1.1 Million Project to Develop System That Will Create Soil Moisture Maps for Farmers
Seyed (Reza) Zekavat and a team of researchers are bringing together drones, ground-penetrating radar, and artificial intelligence (AI) algorithms to develop a low-cost system that will rapidly map root-zone soil moisture levels on large farms and help farmers irrigate more efficiently.
Professor Paffenroth Receives a 3-Year Grant to Develop Data Science Driven Approaches for Chemical Identification
Prof. Paffenroth, Core Data Science Faculty Member and Associate Professor of Mathematical Sciences, and his Data Science PhD student Cate Dunham recently received a $1,000,000 over 3-year project with the Defense Threat Reduction Agency and the US Army DEVCOM-SC to develop state-of-the-art methods to develop deep neural networks for the generation of synthetic chemical signatures.
DS Professor Yanhua Li Recognized by WPI
Yanhua Li has been awarded tenure and promoted to associate professor in the Department of Computer Science. Li is a data science expert who joined the faculty in 2015 and focuses his research on spatial-temporal data science and artificial intelligence with applications in smart cities. He has led or supported research funded with $8.1 million. As a principal investigator, he has secured $4.6 million from industry and the NSF, including prestigious NSF CAREER and CRII awards. Li has taught a range of undergraduate to graduate courses and developed a new course in reinforcement learning, a type of machine learning concerned with how intelligent agents take actions to maximize the notion of cumulative reward.
Help Nonprofits Find Resources and Talent, and Create Community Connections
Seeking to support the efforts of nonprofits to match resources and assets with client demand and operational needs, an interdisciplinary team of researchers at Worcester Polytechnic Institute (WPI) and Rensselaer Polytechnic Institute (RPI) has received a four-year, $1,849,994 award from the National Science Foundation (NSF) to design and implement a new algorithm-based community “collective ecosystem” tool that nonprofit organizations can use to find and share resources—such as event space, transportation for supplies, donations for clients, or even a staff member experienced in grant writing or a volunteer lawyer to review documents.
WPI Mathematician Creates Chemical Sensors For Army Soldiers
WORCESTER, Mass. (WBZ NewsRadio) — A WPI mathematician is working with the U.S. Army to develop tiny, wearable chemical sensors that help them detect harmful chemicals quickly.
WBZ NewsRadio's Laurie Kirby spoke with Randy Paffenroth, an associate professor of mathematical sciences, computer science, and data science at WPI, about the project, on which he served as principal investigator.
Professor Lane Harrison to Support Data Visualization Studies with NSF Grant
Whether it’s polling numbers or voter turnout displays on a news website, public health COVID-19 vaccine messaging, or artificial intelligence interfaces, how data visualizations are presented can inform and influence important, and often critical, decisions.
Determining whether those presentations are effective—whether people got the message—takes time and an empirical approach. Associate Computer Science Professor Lane Harrison hopes to speed up that process by putting better tools into the hands of researchers who study the graphical representation of information using charts, graphs, animations, or maps.
AI and Fairness:
When it comes to fairness, artificial intelligence (AI) is imperfect.
But Elke Rundensteiner, William Smith Dean's Professor in the Department of Computer Science and founding director of the Data Science program at WPI, and her students are developing a way to address this problem with algorithms that help ensure fairness in aggregated rankings that impact people in profound ways. The work has been supported by a grant of nearly $500,000 from the National Science Foundation.
NSF Grant to Study How Humans Interact With Artificial Intelligence
Roee Shraga, assistant professor of computer science and data science at Worcester Polytechnic Institute (WPI), has received $175,000 from the National Science Foundation to scrutinize the human aspects of data discovery and integration. The research project aims to explore the critical role of human involvement in data preparation processes to identify and address biases that automated systems may fail to detect.
Seyed Zekavat Leads $1.1 Million Project to Develop System That Will Create Soil Moisture Maps for Farmers
Seyed (Reza) Zekavat and a team of researchers are bringing together drones, ground-penetrating radar, and artificial intelligence (AI) algorithms to develop a low-cost system that will rapidly map root-zone soil moisture levels on large farms and help farmers irrigate more efficiently.
Professor Paffenroth Receives a 3-Year Grant to Develop Data Science Driven Approaches for Chemical Identification
Prof. Paffenroth, Core Data Science Faculty Member and Associate Professor of Mathematical Sciences, and his Data Science PhD student Cate Dunham recently received a $1,000,000 over 3-year project with the Defense Threat Reduction Agency and the US Army DEVCOM-SC to develop state-of-the-art methods to develop deep neural networks for the generation of synthetic chemical signatures.
DS Professor Yanhua Li Recognized by WPI
Yanhua Li has been awarded tenure and promoted to associate professor in the Department of Computer Science. Li is a data science expert who joined the faculty in 2015 and focuses his research on spatial-temporal data science and artificial intelligence with applications in smart cities. He has led or supported research funded with $8.1 million. As a principal investigator, he has secured $4.6 million from industry and the NSF, including prestigious NSF CAREER and CRII awards. Li has taught a range of undergraduate to graduate courses and developed a new course in reinforcement learning, a type of machine learning concerned with how intelligent agents take actions to maximize the notion of cumulative reward.
Help Nonprofits Find Resources and Talent, and Create Community Connections
Seeking to support the efforts of nonprofits to match resources and assets with client demand and operational needs, an interdisciplinary team of researchers at Worcester Polytechnic Institute (WPI) and Rensselaer Polytechnic Institute (RPI) has received a four-year, $1,849,994 award from the National Science Foundation (NSF) to design and implement a new algorithm-based community “collective ecosystem” tool that nonprofit organizations can use to find and share resources—such as event space, transportation for supplies, donations for clients, or even a staff member experienced in grant writing or a volunteer lawyer to review documents.
WPI Mathematician Creates Chemical Sensors For Army Soldiers
WORCESTER, Mass. (WBZ NewsRadio) — A WPI mathematician is working with the U.S. Army to develop tiny, wearable chemical sensors that help them detect harmful chemicals quickly.
WBZ NewsRadio's Laurie Kirby spoke with Randy Paffenroth, an associate professor of mathematical sciences, computer science, and data science at WPI, about the project, on which he served as principal investigator.
Professor Lane Harrison to Support Data Visualization Studies with NSF Grant
Whether it’s polling numbers or voter turnout displays on a news website, public health COVID-19 vaccine messaging, or artificial intelligence interfaces, how data visualizations are presented can inform and influence important, and often critical, decisions.
Determining whether those presentations are effective—whether people got the message—takes time and an empirical approach. Associate Computer Science Professor Lane Harrison hopes to speed up that process by putting better tools into the hands of researchers who study the graphical representation of information using charts, graphs, animations, or maps.
AI and Fairness:
When it comes to fairness, artificial intelligence (AI) is imperfect.
But Elke Rundensteiner, William Smith Dean's Professor in the Department of Computer Science and founding director of the Data Science program at WPI, and her students are developing a way to address this problem with algorithms that help ensure fairness in aggregated rankings that impact people in profound ways. The work has been supported by a grant of nearly $500,000 from the National Science Foundation.
WPI Researchers Awarded $2 Million Grant to Use Science to Combat Wildlife Trafficking
WPI will partner with researchers from Florida International University and the University of Maryland on the four-year, $2 million grant. For Kyumin Lee, professor of computer science, and Renata Konrad, a professor in The Business School at WPI, the new grant represents an evolution of work they started in 2020 to use a mix of artificial intelligence, physical tools, and supply chain, financial, and social media data to deter illegal wildlife trade.
DS - AI Faculty Research
Understanding Brain Networks using Deep Learning
WPI Prof. Xiangnan Kong discusses their current research related to AI.
Faster, Fairer, and More Accurate AI Models with Graph Data
WPI Prof. Fabricio Murai discusses their current research related to FRV AI.
Extracting Knowledge with Natural Language Processing
WPI Prof. Kyumin Lee describes his research information retrieval and AI.
Better Data for Better AI Results
WPI Prof. Roee Shraga describes his work to improve the data used b AI systems and algorithms.
Understanding Brain Networks using Deep Learning
WPI Prof. Xiangnan Kong discusses their current research related to AI.
Faster, Fairer, and More Accurate AI Models with Graph Data
WPI Prof. Fabricio Murai discusses their current research related to FRV AI.
Extracting Knowledge with Natural Language Processing
WPI Prof. Kyumin Lee describes his research information retrieval and AI.
Better Data for Better AI Results
WPI Prof. Roee Shraga describes his work to improve the data used b AI systems and algorithms.
Understanding Brain Networks using Deep Learning
WPI Prof. Xiangnan Kong discusses their current research related to AI.
Faculty Profiles
Professor Zou's research focuses on financial time series and spatial statistics with applications to epidemiology, public health and climate change. His most recent research on statistical theory and methodology addressed a wide range of challenges including high dimensionality, complex dependencies, and space and time variations. His research in high-frequency financial data tackled problems with high dimensionality, which is currently a hot topic in statistics.
As founding Head of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, and new educational initiatives to our innovative industry-sponsored and mentored Graduate Qualifying projects at the graduate level.
During his doctoral research efforts, Dr. Ghoshal developed three novel methods to expand the usability of convolutional neural networks beyond image data. He earned his Ph.D. in Engineering Science with a Computer Science major from the University of Mississippi in 2020. He then joined Lyon College as a Visiting Assistant Professor and led the development of their brand new data science program. His research interests include feature engineering, deep learning, and natural language processing.
Information visualization is a powerful means for understanding data and informing human minds. As people begin to rely on visualizations to make high-impact and even life-critical decisions, there is a growing need to ensure that information can be perceived accurately and precisely.
Professor Kong’s research interests focus on data mining and machine learning, with emphasis on addressing the data science problems in biomedical and social applications. Data today involves an increasing number of data types that need to be handled differently from conventional data records, and an increasing number of data sources that need to be fused together. Dr. Kong is particularly interested in designing algorithms to tame data variety issues in various research fields, such as biomedical research, social computing, neuroscience, and business intelligence.
Nima Kordzadeh is an Assistant Professor of Information Systems at the WPI Business School. He is also affiliated with the Data Science Program. Joining WPI in 2017, Professor Kordzadeh was drawn by the university's commitment to blending theory with practice, aligning perfectly with his educational philosophy.
Dr. Lee’s research interests are in social computing, artificial intelligence, machine learning, natural language processing, and information retrieval, over large-scale systems like the Web and social media. He focuses on threats to these systems and design methods to mitigate negative behaviors (e.g., misinformation, hate speech), and look for positive opportunities to mine and analyze these systems for developing next generation algorithms and architectures (e.g., recommender system, natural language understanding).
Yanhua Li is an Associate Professor in the Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI). His research interests focus on artificial intelligence (AI) and data science, with applications in smart cities in many contexts, including spatial-temporal data analytics, urban planning and optimization.
Dr. Xiaozhong Liu is an Associate Professor at Computer Science and Data Science, WPI. Before that, he was Associate Professor at School of Informatics, Computing and Engineering Indiana University Bloomington. His research interests include natural language processing (NLP), text/graph mining, information retrieval/recommendation, metadata, and computational social science. His dissertation at Syracuse University (advisor Dr. Elizabeth D. Liddy) explored an innovative ranking method that weighted the retrieved results by leveraging dynamic community interests.
I design and analyze optimization and Markov Chain Monte Carlo sampling algorithms, with provable runtime, robustness, and privacy guarantees for applications in Machine Learning, Data Science, and Statistics. In doing so, I aim to introduce new mathematical tools from physics and geometry to the design and analysis of optimization and sampling algorithms used in ML.
Before joining WPI Data Science/Computer Science, Fabricio Murai was an Associate Professor in the Department of Computer Science at the Universidade Federal de Minas Gerais, Brazil. He received his Ph.D. in Computer Science at University of Massachusetts, Amherst in 2016. His research lies in the application of mathematical modeling, statistics and machine learning to computer, informational and social networks. He has published in top scientific journals such as Data Mining and Knowledge Discovery, ACM TKDD and PLOS ONE.
My research focuses on compressed sensing, machine learning, signal processing, and the interaction between mathematics, computer science and software engineering. My interests range from theoretical results to algorithms for tackling practical applied problems, and I enjoy problems most when mathematical results lead to efficient software implementations for big data. I am looking forward to working with students at all levels and backgrounds who share an interest in mathematics, software, or data.
Carolina Ruiz is the Associate Dean of Arts and Sciences and the Harold L. Jurist ’61 and Heather E. Jurist Dean's Professor of Computer Science. She joined the WPI faculty in 1997. Prof. Ruiz’s research is in Artificial Intelligence, Machine Learning, and Data Mining, and their applications to Medicine and Health. She has worked on several clinical domains including sleep, stroke, obesity and pancreatic cancer. Prof.
Before joining WPI, Roee Shraga was a Postdoctoral fellow at the Khoury College of Computer Science at Northeastern University in Boston. His research mainly revolves around data discovery and integration and combines techniques from data management, machine learning, information retrieval and human-in-the-loop. His research has been published in top-tier conferences such as SIGMOD, VLDB, SIGIR, WWW, and ICDE. He is a recipient of the Council for Higher Education [VATAT] scholarship for outstanding data science postdocs.
I am Professor of Operations and Industrial Engineering at Worcester Polytechnic Institute (WPI), with courtesy appointments in Mathematical Sciences, Data Science, and Computer Science. I hold a Ph.D. in Industrial Engineering from the University of Pittsburgh. My objective is to use science and technology to assist real human need by improving systems that serve vulnerable peoples, such as refugees and asylum seekers, survivors of human trafficking, and children in the foster care system.
Daniel N. Treku teaches blockchain-related courses, business intelligence, and data science at the Business School at Worcester Polytechnic Institute, Massachusetts. His ongoing research lies at the intersection of network technologies (such as blockchain technology), digital platforms, data analytics, and fintech (AI-, cryptocurrency- and NFT-related, and ESG). Mainly, his research utilizes conceptual and empirical approaches toward broader aims of financial inclusivity and social good.
Seyed A. (Reza) Zekavat received his PhD from Colorado State University in 2002. He is the Author of the textbook "Electrical Engineering: Concepts and Applications" published by Pearson, and the editor of the book “Handbook of Position Location: Theory, Practice and Advances,” published by Wiley/IEEE. He holds a patent on an active Wireless Remote Positioning System.
Professor Zou's research focuses on financial time series and spatial statistics with applications to epidemiology, public health and climate change. His most recent research on statistical theory and methodology addressed a wide range of challenges including high dimensionality, complex dependencies, and space and time variations. His research in high-frequency financial data tackled problems with high dimensionality, which is currently a hot topic in statistics.
As founding Head of the interdisciplinary Data Science program here at WPI, I take great pleasure in doing all in my power to support the Data Science community in all its facets from research collaborations, and new educational initiatives to our innovative industry-sponsored and mentored Graduate Qualifying projects at the graduate level.
During his doctoral research efforts, Dr. Ghoshal developed three novel methods to expand the usability of convolutional neural networks beyond image data. He earned his Ph.D. in Engineering Science with a Computer Science major from the University of Mississippi in 2020. He then joined Lyon College as a Visiting Assistant Professor and led the development of their brand new data science program. His research interests include feature engineering, deep learning, and natural language processing.
Information visualization is a powerful means for understanding data and informing human minds. As people begin to rely on visualizations to make high-impact and even life-critical decisions, there is a growing need to ensure that information can be perceived accurately and precisely.
Professor Kong’s research interests focus on data mining and machine learning, with emphasis on addressing the data science problems in biomedical and social applications. Data today involves an increasing number of data types that need to be handled differently from conventional data records, and an increasing number of data sources that need to be fused together. Dr. Kong is particularly interested in designing algorithms to tame data variety issues in various research fields, such as biomedical research, social computing, neuroscience, and business intelligence.
Nima Kordzadeh is an Assistant Professor of Information Systems at the WPI Business School. He is also affiliated with the Data Science Program. Joining WPI in 2017, Professor Kordzadeh was drawn by the university's commitment to blending theory with practice, aligning perfectly with his educational philosophy.
Dr. Lee’s research interests are in social computing, artificial intelligence, machine learning, natural language processing, and information retrieval, over large-scale systems like the Web and social media. He focuses on threats to these systems and design methods to mitigate negative behaviors (e.g., misinformation, hate speech), and look for positive opportunities to mine and analyze these systems for developing next generation algorithms and architectures (e.g., recommender system, natural language understanding).
Yanhua Li is an Associate Professor in the Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI). His research interests focus on artificial intelligence (AI) and data science, with applications in smart cities in many contexts, including spatial-temporal data analytics, urban planning and optimization.
Dr. Xiaozhong Liu is an Associate Professor at Computer Science and Data Science, WPI. Before that, he was Associate Professor at School of Informatics, Computing and Engineering Indiana University Bloomington. His research interests include natural language processing (NLP), text/graph mining, information retrieval/recommendation, metadata, and computational social science. His dissertation at Syracuse University (advisor Dr. Elizabeth D. Liddy) explored an innovative ranking method that weighted the retrieved results by leveraging dynamic community interests.
I design and analyze optimization and Markov Chain Monte Carlo sampling algorithms, with provable runtime, robustness, and privacy guarantees for applications in Machine Learning, Data Science, and Statistics. In doing so, I aim to introduce new mathematical tools from physics and geometry to the design and analysis of optimization and sampling algorithms used in ML.
Before joining WPI Data Science/Computer Science, Fabricio Murai was an Associate Professor in the Department of Computer Science at the Universidade Federal de Minas Gerais, Brazil. He received his Ph.D. in Computer Science at University of Massachusetts, Amherst in 2016. His research lies in the application of mathematical modeling, statistics and machine learning to computer, informational and social networks. He has published in top scientific journals such as Data Mining and Knowledge Discovery, ACM TKDD and PLOS ONE.
My research focuses on compressed sensing, machine learning, signal processing, and the interaction between mathematics, computer science and software engineering. My interests range from theoretical results to algorithms for tackling practical applied problems, and I enjoy problems most when mathematical results lead to efficient software implementations for big data. I am looking forward to working with students at all levels and backgrounds who share an interest in mathematics, software, or data.
Carolina Ruiz is the Associate Dean of Arts and Sciences and the Harold L. Jurist ’61 and Heather E. Jurist Dean's Professor of Computer Science. She joined the WPI faculty in 1997. Prof. Ruiz’s research is in Artificial Intelligence, Machine Learning, and Data Mining, and their applications to Medicine and Health. She has worked on several clinical domains including sleep, stroke, obesity and pancreatic cancer. Prof.
Before joining WPI, Roee Shraga was a Postdoctoral fellow at the Khoury College of Computer Science at Northeastern University in Boston. His research mainly revolves around data discovery and integration and combines techniques from data management, machine learning, information retrieval and human-in-the-loop. His research has been published in top-tier conferences such as SIGMOD, VLDB, SIGIR, WWW, and ICDE. He is a recipient of the Council for Higher Education [VATAT] scholarship for outstanding data science postdocs.
I am Professor of Operations and Industrial Engineering at Worcester Polytechnic Institute (WPI), with courtesy appointments in Mathematical Sciences, Data Science, and Computer Science. I hold a Ph.D. in Industrial Engineering from the University of Pittsburgh. My objective is to use science and technology to assist real human need by improving systems that serve vulnerable peoples, such as refugees and asylum seekers, survivors of human trafficking, and children in the foster care system.
Daniel N. Treku teaches blockchain-related courses, business intelligence, and data science at the Business School at Worcester Polytechnic Institute, Massachusetts. His ongoing research lies at the intersection of network technologies (such as blockchain technology), digital platforms, data analytics, and fintech (AI-, cryptocurrency- and NFT-related, and ESG). Mainly, his research utilizes conceptual and empirical approaches toward broader aims of financial inclusivity and social good.
Seyed A. (Reza) Zekavat received his PhD from Colorado State University in 2002. He is the Author of the textbook "Electrical Engineering: Concepts and Applications" published by Pearson, and the editor of the book “Handbook of Position Location: Theory, Practice and Advances,” published by Wiley/IEEE. He holds a patent on an active Wireless Remote Positioning System.
Professor Zou's research focuses on financial time series and spatial statistics with applications to epidemiology, public health and climate change. His most recent research on statistical theory and methodology addressed a wide range of challenges including high dimensionality, complex dependencies, and space and time variations. His research in high-frequency financial data tackled problems with high dimensionality, which is currently a hot topic in statistics.