Davon Norris

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I try to understand how our tools for determining what is valuable, worthwhile, or good are implicated in patterns of inequality with an acute concern for racial inequality. Often, this means my work investigates the functioning and consequences of a range of scores or ratings, from the less complex government credit ratings to the extremely complex algorithmic scores like consumer credit scores.

In related work, as a part of a multi-university team of researchers, I am using administrative credit report data from one of the largest credit reporting agencies to study credit and debt outcomes for millions of consumers in the United States.

Stefanus Jasin

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My research focus the application and development of new algorithms for solving complex business analytics problems. Applications vary from revenue management, dynamic pricing, marketing analytics, to retail logistics. In terms of methodology, I use a combination of operations research and machine learning/online optimization techniques.

 

Wentao Wang

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Dr. Wentao Wang is currently a research faculty in the Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor, MI, United States. He obtained his Ph.D. degree in 2016 from Harbin Institute of Technology, supervised by Prof. Hui Li and Prof. Jerome P. Lynch

Ben Green

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Ben studies the social and political impacts of government algorithms. This work falls into several categories. First, evaluating how people make decisions in collaboration with algorithms. This work involves developing machine learning algorithms and studying how people use them in public sector prediction and decision settings. Second, studying the ethical and political implications of government algorithms. Much of this work draws on STS and legal theory to interrogate topics such as algorithmic fairness, smart cities, and criminal justice risk assessments. Third, developing algorithms for public sector applications. In addition to academic research, Ben spent a year developing data analytics tools as a data scientist for the City of Boston.

Tayo Fabusuyi

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Tayo Fabusuyi is an assistant research scientist in the Human Factors Group at UMTRI. His research interests are in Urban Systems and Operations Research, specifically designing and implementing initiatives that support sustainable and resilient communities with a focus on efficiency and equity issues. Drawing on both quantitative and qualitative data, his research develops and applies hard and soft Operations Research methods to urban systems issues in a manner that emphasizes theory driven solutions with demonstrated value-added. A central theme of his research activities is the use of demand side interventions, via information and pricing strategies in influencing the public’s travel behavior with the objective of achieving more beneficial societal outcomes. Informed by the proliferation of big data and the influence of transportation in the urban sphere, these research activities are categorized broadly into three overlapping and interdependent areas – intelligent transportation systems (ITS), emerging mobility services and urban futures. Before joining the research faculty at UMTRI, Dr. Fabusuyi was a Planning Economist at the African Development Bank and an adjunct Economics faculty member at Carnegie Mellon University, where he received his Ph.D. in Engineering and Public Policy.

Anthony Vanky

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Anthony Vanky develops and applies data science and computational methods to design, plan, evaluate cities, emphasizing their applications to urban planning and design. Broadly, his work focuses on the domains of transportation and human mobility; social behaviors and urban space; policy evaluation; quantitative social sciences; and the evaluation of urban form. Through this work, he has extensively collaborated with public and private partners. In addition, he considers creative approaches toward data visualization, public engagement and advocacy, and research methods.

 

Anthony Vanky’s Cityways project analyzed 2.2 million trips from 135,000 people over one year to understand the factors that influence outdoor pedestrian path choice. Factors considered included weather, urban morphology, businesses, topography, traffic, the presence of green spaces, among others.

 

View Faculty Research Pitch, Fall 2021

Robert Manduca

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Professor Manduca’s research focuses on urban and regional economic development, asking why some cities and regions prosper while others decline, how federal policy influences urban fortunes, and how neighborhood social and economic conditions shape life outcomes. He studies these topics using computer simulations, spatial clustering methods, network analysis, and data visualization.

In other work he explores the consequences of rising income inequality for various aspects of life in the United States, using descriptive methods and simulations applied to Census microdata. This research has shown how rising inequality has lead directly to lower rates of upward mobility and increases in the racial income gap.

9.9.2020 MIDAS Faculty Research Pitch Video.

MIDAS Faculty Research Pitch, Fall 2021

Screenshot from “Where Are The Jobs?” visualization mapping every job in the United States based on the unemployment insurance records from the Census LODES data. http://robertmanduca.com/projects/jobs.html

Joshua P Newell

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I work in the area of urban sustainability, with research questions at multiple scales and environmental and socio-economic systems. My work uses spatial analysis (esp. GIS and remote sensing) and mass-balance accounting (life cycle assessment, material flow analysis). My lab is starting to use big data from a range of sources (Zillow, Twitter, etc) and I am interested in collaborating with data sciences of various stripes on sustainability and equity challenges.

Robert Hampshire

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He develops and applies operations research, data science, and systems approaches to public and private service industries. His research focuses on the management and policy analysis of emerging networked industries and innovative mobility services such as smart parking, connected vehicles, autonomous vehicles, ride-hailing, bike sharing, and car sharing. He has worked extensively with both public and private sector partners worldwide. He is a queueing theorist that uses statistics, stochastic modeling, simulation and dynamic optimization.