TALENT

Valentina (Valya) Kuskova

Kuskova is the Managing Director of Notre Dame AnalytiXIN site in Indianapolis. Her main responsibility is to coordinate and execute the implementation of the Notre Dame AnalytiXIN interface with industry stakeholders. In this role, she is tasked with bringing Notre Dame AI/ML and advanced data analytics talent into direct interaction with CICP companies through a structured set of activities, including strategic initiatives, research projects, student internships, corporate/faculty exchanges, and many educational and networking events.Dr. Kuskova has extensive corporate and academic experience. After an MBA from Boise State University she had worked in a variety of corporate roles, from programmer/analyst to senior strategic planning analyst at major Fortune-200 companies.

Dr. Kuskova and her team are currently working with outside organizations on data science projects, to learn more and to see if her team can engage in your company’s efforts, please contact her at vkuskova@nd.edu

Fanny Ye, PhD

Dr. Yanfang (Fanny) Ye is a Collegiate Associate Professor of Computer Science and Engineering at the University of Notre Dame. Her research interests include Cybersecurity, Data Mining, Machine Learning, and Health Intelligence. Her proposed techniques by advancing capabilities of AI have been incorporated into popular commercial cybersecurity products that protect millions of users worldwide. She has also expanded her research to health intelligence focusing on combating opioid epidemic and COVID-19 crisis.

Yong Suk Lee, PhD

Dr. Yong Lee is Assistant Professor of Technology, Economy and Global Affairs at University of Notre Dame. His research focuses on how new technologies affect labor and firms, and the governance and ethical issues related to AI, employing econometric analysis and machine learning. Previously, Lee was at Stanford University and worked in industry for 5 years. He received his PhD in Economics from Brown University, MPP from Duke University, and BS and MS from Seoul National University.

Robert Landers, PhD

Dr. Robert G. Landers is a Collegiate Professor in the Department of Aerospace and Mechanical Engineering at the University of Notre Dame. He was previously a Curators’ Distinguished Professor at the Missouri University of Science and Technology and served for three years as a program manager at the National Science Foundation. He received his Ph.D. degree in Mechanical Engineering from the University of Michigan. His research interests are in the areas of modeling, analysis, monitoring, and control of manufacturing processes, and in the estimation and control of lithium ion batteries and hydrogen fuel cells.

Dr. Monisha Ghosh

Dr. Monisha Ghosh is a Professor of Electrical Engineering at the University of Notre Dame. She is also the Policy Outreach Director for SpectrumX, the first NSF Center for Spectrum Innovation. Her research interests are in the development of next generation wireless systems: cellular, Wi-Fi and IoT, with an emphasis on spectrum sharing and coexistence and applications of machine learning to improve network performance. Prior to joining the University of Notre Dame in 2022, she was the Chief Technology Officer at the Federal Communications Commission, a Program Director at the National Science Foundation, Research Professor at the University of Chicago and spent 24 years in industry research at Bell Labs, Philips Research and Interdigital. She obtained her B.Tech from IIT Kharagpur and Ph.D. from USC. She is a Fellow of the IEEE.

Nuno Moniz

Nuno Moniz is an Associate Research Professor at the Lucy Family Institute for Data & Society. Moniz’s research is primarily focused on machine learning, looking into problems such as rare event detection, data privacy and model interpretability. He is particularly interested in interdisciplinary efforts to understand the real-world impact of intelligent systems. Before joining the Lucy Family Institute, Nuno was a Senior Researcher in INESC TEC (Portugal). He holds a PhD in Computer Science from the University of Porto.

Matt Sick

Matthew L. Sisk is an Associate Professor of the Practice in the Lucy Family Institute for Data & Society where he focuses on the use of GIS and spatial tools in Data Science. He received his B.S. from the University of South Carolina in Marine Science and Anthropology and his M.A. and Ph.D. in Paleolithic Archaeology from Stony Brook University in 2011.  His research focuses on human- environment interactions, the spatial scale of environmental toxins and community data.

Yang Yang

Yang is an Assistant Professor of IT, Analytics, and Operations. Yang holds a PhD in Computer Science from the University of Notre Dame. He was a Research Assistant Professor at Northwestern Institute on Complex Systems (NICO) and Kellogg School of Management. His principal research interest lies in the areas of data mining/machine learning, computational social science and science of science. Yang is interested in studying how social networks affect individuals’ success. Specifically, he has studied the link between social network and leadership attainment. He also focuses on research in the context of science and innovation. He studies the effect of team composition on performance and innovation, as well as the role of media and social media in shaping public access to science. His work has been published in journals and conference proceedings, such as Proceedings of the National Academy of Sciences, KDD, ICDM, WWW and Knowledge and Information Systems. His papers have been mentioned by Forbes, Fortune, The Washington Post, BBC, Psychology Today, The Hill, WIRED, and Harvard Business Review.

Karla Badillo-Urquiola

Professor Badillo-Urquiola conducts human-computer interaction research to design technology-driven solutions that empower people and protect the well-being of youth and marginalized communities. Her current work uses human-centered and participatory design methods to study adolescent online safety for teens in foster care situations.

As a Latina woman in STEM, professor Badillo-Urquiola is also determined to advance the principles of diversity, inclusion, and equity in computing. She is an active member of the SIGCHI Latin American HCI Community (LAIHC) and an advocate for minority HCI faculty and students.

She is a fellow of Notre Dame’s Lucy Family Institute for Data and Society, where she conducts research and collaborates with the community to build better futures for youth.

Her areas of interest include:

• Human-computer Interaction
• Social Computing
• Online Safety, Usable Privacy and Security
• Digital Youth, Child Welfare
• Latino Populations, Marginalized Populations

Nick Berente

Nick Berente studies how digital innovations like artificial intelligence technologies drive change in organizations and institutions. He teaches courses on Strategic Business Technology and is Co-Director of the GAMA Lab. Prof. Berente received his PhD from Case Western Reserve University and conducted postdoctoral studies at the University of Michigan. He was an entrepreneur prior to his academic career, founding two technology companies. He is the principal investigator for a number of U.S. National Science Foundation projects and has won multiple awards for his teaching and his research. Prof. Berente is a senior editor for MIS Quarterly.

Toby Jai-Jun Li

Prof. Li works at the intersection of Human-Computer Interaction (HCI), End-User Software Engineering, Machine Learning (ML), and Natural Language Processing (NLP) applications.  He uses human-centered methods to design, build, and study interactive systems to empower individuals to create, configure, and extend AI-powered computing systems.

His recent work seeks to address the societal challenges in the future of work through a bottom-up, human-AI collaborative approach that helps individuals automate and augment their tasks with AI systems.

Prof. Li is committed to diversity, equity, and inclusion in computing education and research.

Lizhen Lin

Robert and Sara Lumpkins Associate Professor

Bayesian Asymptotics, Bayesian Nonparametrics, Big Data Analysis , Geometry and Statistics, Network Analysis, Probabilistic Graphical Models, Topological Data Analysis

Ph.D., The University of Arizona, 2012
B.S., Sichuan University, 2006

Xiangliang (Lynn) Zhang

Professor Xiangliang Zhang’s research focuses on machine learning, data mining and their application in knowledge discovery.

She targets challenging problems that include:

• learning from complicated and dynamic environments;
• learning with missing and noisy data;
• understanding the risk of machine learning models under threats of attacks;
• discovering novel knowledge in various application domains via knowledge representation learning, extraction and inference.