Constantine E. Kontokosta

DIRECTOR, URBAN INTELLIGENCE LAB; Associate Professor of Urban Science and Planning; Director, Civic Analytics Program

Bartosz Bonczak

Associate Research Scientist

Nicholas Johnson

Postdoctoral Associate

Boyeong Hong

Postdoctoral Associate

Sokratis Papadopoulos

PhD Candidate

Yuan Lai

Ph.D. Candidate

yuan.lai@nyu.edu
646.997.0612

Tabitha Julien

Civic Analytics Fellow


Pablo Mandiola

Civic Analytics Fellow


Cyrus Blankinship

Civic Analytics Fellow


Awais Malik

Ph.D Candidate, Civil & Urban Engineering (NYU Tandon) and NYU CUSP

awais.malik@nyu.edu
646.997.0544

Stanislav Sobolevsky

Associate Professor of Practice, NYU CUSP

sobolevsky@nyu.edu
646.997.0527

Martin Traunmueller

Civic Analytics Fellow

Tashay Green

Civic Analytics Graduate Student Fellow

Emily Hansen

Graduate Research Assistant


Jack Lundquist

Civic Analytics Graduate Student Fellow


Unisse Chua

Graduate Research Assistant


Daniel Marasco

Senior Computer Scientist, MITRE Corp.


Geoff Perrin

Civic Analytics Graduate Student Fellow

Xinshi Zheng

Civic Analytics Graduate Student Fellow

Kristi Korsberg

Civic Analytics Graduate Student Fellow

Ian Stuart

Graduate Research Assistant, Building Informatics

Ian Wright

Graduate Research Assistant

Ryan Sims

Undergraduate Research Assistant

Raka Dey

Undergraduate Research Assistant

Constantine E. Kontokosta

DIRECTOR, URBAN INTELLIGENCE LAB; Associate Professor of Urban Science and Planning; Director, Civic Analytics Program

ckontokosta@nyu.edu

Prof. Kontokosta brings training urban planning, data science, economics, and systems engineering to the data-driven study of cities.

Constantine E. Kontokosta is an Associate Professor of Urban Science and Planning and Director of the Civic Analytics program at the NYU Marron Institute of Urban Management. He also directs the Urban Intelligence Lab and holds cross-appointments at the Center for Urban Science and Progress (CUSP) and the Department of Civil and Urban Engineering (CUE). He is affiliated faculty at the Wagner School of Public Service, Visiting Professor of Computer Science at the University of Warwick (UK), and a Senior Scholar at the New York Academy of Medicine. Previously, he served as the inaugural Deputy Director of CUSP and Assistant Professor of Urban Informatics at CUSP and CUE, where he was part of the Center’s founding leadership team and designed and launched the first graduate program in urban informatics. He is the founding Principal Investigator of the Quantified Community research initiative that integrates hyperlocal urban sensors with city-scale data analytics to understand neighborhood dynamics and well-being, and is one of the largest community-driven IoT projects in New York City. He is a 2017 recipient of the National Science Foundation CAREER Award for his research in urban informatics for sustainable cities.

Trained in urban planning and computational methods (Columbia), finance and economics (NYU), and systems science and engineering (UPenn), Constantine brings an inter-disciplinary perspective to urban science that integrates fundamental research with impact-driven, use-inspired needs. His work leverages large-scale data with computational methods to understand and drive change in energy efficiency and climate policy, neighborhood change and the impacts of urban development, and community-driven air quality monitoring and environmental justice. Recent projects include research with NYC311 and Kansas City to measure bias in citizen complaint reporting for predictive analytics; with a homeless shelter provider to apply machine learning algorithms to identify at-risk homeless families; and with the City of New York, Washington, DC, and the UN to leverage large-scale data analytics for building energy and climate policy. Constantine’s research groups – the Civic Analytics Program and the Urban Intelligence Lab – are motivated by a desire to bring evidence to policy-making, to democratize knowledge through information transparency, and to uncover discrimination and bias in data-driven decision-making.

Constantine’s research is funded by the National Science Foundation (NSF), MacArthur Foundation, Sloan Foundation, the U.S. Department of Transportation, the NYC Mayor’s Office of Sustainability, the Lincoln Institute of Land Policy, and the U.S. Department of Housing and Urban Development, among others, and he has received several honors for his work, including the IBM Faculty Award, the Google IoT Research Award, the UN Data for Climate Action Challenge Award,  the Goddard Junior Faculty Fellowship, the Charles Abrams Award for Social Justice Research, and NYU awards for Teaching Excellence and Outstanding Service. Constantine has published more than 70 peer-reviewed publications in leading academic journals and conferences – in fields ranging from urban planning to signal processing – and has two forthcoming books on urban analytics and data-driven climate action. His research has been featured in the New York Times, the Wall Street Journal, the Economist, FastCompany, CityLab, Wired, CNN, NPR, and other media outlets. He holds a PhD, M.Phil, and M.S. from Columbia University, a M.S. from New York University, and a B.S.E. from the University of Pennsylvania.

He serves or has served on committees and advisory boards at the National Academies, DARPA, the NSF Northeast Big Data Hub, the UNEP Sustainable Buildings and Climate Council, and the Royal Institution of Chartered Surveyors, and was the Vice Chair and a Commissioner of the Suffolk County (NY) Planning Commission. In addition to his academic work, Constantine is an accomplished entrepreneur.

Recent Projects

The Impact of Mandatory Energy Audits on Energy Use in Buildings

View Project

Estimating Bias in 311 Service Request Data

View Project

Analyzing the Impacts of Urban Land Use Dynamics

View Project

Benchmarking, Feedback, and Behavior Change for Commercial Office Building Tenants

View Project

Data Quality and Reliability Metrics for Building Energy Disclosure Data

View Project

CommunitySense

View Project

Using Machine Learning and Small Area Estimation to Predicting Building-level Waste Generation and Recycling

View Project

Machine Learning Approaches to Predict and Target Building Energy Retrofits

View Project

Using LiDAR to Analyze the Impact of Urban Morphology on Energy Use

View Project

The Resilience to Emergencies and Disasters Index (REDI)

View Project

The QC Urban Sensing Array

View Project

Recent Publications

Journal of the American Planning Association

Energy Cost Burdens for Low-Income and Minority Households: Evidence From Energy Benchmarking and Audit Data in Five US Cities

Kontokosta, C. E., Reina, V. J., & Bonczak, B. (2019). Energy Cost Burdens for Low-Income and Minority Households: Evidence From Energy Benchmarking and Audit Data in Five US Cities. Journal of the American Planning Association, 1-17.

Computers, Environment and Urban Systems

Topic Modeling to Discover the Thematic Structure and Spatial-temporal Patterns of Building Renovation and Adaptive Reuse in Cities

Lai, Y., & Kontokosta, C. E. (2019). Topic modeling to discover the thematic structure and spatial-temporal patterns of building renovation and adaptive reuse in cities. Computers, Environment and Urban Systems, 78, 101383.

Health & Place

The Impact of Urban Street Tree Species on Air Quality and Respiratory Illness: A Spatial Analysis of Large-Scale, High Resolution Urban Data

Lai, Yuan and Constantine E. Kontokosta, 2019. “The Impact of Urban Street Tree Species on Air Quality and Respiratory Illness: A Spatial Analysis of Large-Scale, High Resolution Urban Data,” Health & Place, in press.

Computers, Environment, and Urban Systems

Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data

Bonczak, Bartosz and Constantine E. Kontokosta. 2018. “Large-scale Parameterization of 3D Building Morphology in Complex Urban Landscapes Using Aerial LiDAR and City Administrative Data,” Computers, Environment, and Urban Systems, in press.

Journal of Planning Education and Research

Urban Informatics in the Science and Practice of Planning

Kontokosta, Constantine E. 2018. “Urban Informatics in the Science and Practice of Planning,” Journal of Planning Education and Research.

Computers, Environment, and Urban Systems

Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities.

Kontokosta, C. E., Hong, B., Johnson, N. E., & Starobin, D. (2018). Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities. Computers, Environment and Urban Systems.

Transport Policy

A data-driven methodology for equitable value-capture financing of public transit operations and maintenance

Falcocchio, J. C. G., Malik, A., & Kontokosta, C. E. (2018). A data-driven methodology for equitable value-capture financing of public transit operations and maintenance. Transport Policy.

Sustainable Cities and Society

The Resilience to Emergencies & Disasters Index: Applying Big Data to Benchmark and Validate Neighborhood Resilience Capacity

Kontokosta, C. E., & Malik, A. (2018). The Resilience to Emergencies and Disasters Index: Applying big data to benchmark and validate neighborhood resilience capacity. Sustainable Cities and Society, 36, 272-285

Bartosz Bonczak

Associate Research Scientist

bartosz.bonczak@nyu.edu
646.997.0530

Bartosz Bonczak is an Associate Research Scientist at CUSP working with Quantified Community and Building Informatics teams.

In his research, he applies data-driven approaches to improve building energy efficiency and the analysis of urban topography.

Bartosz received M.S. in Urban Informatics from CUSP (2015) and completed a B.S. (2009) and a M.S. (2011) in Geography with the focus on tourism at University of Lodz in his home country of Poland. Prior to joining CUSP he was Assistant Research Scientist at the Department of Geographical Sciences at University of Lodz.

Recent Projects

Benchmarking, Feedback, and Behavior Change for Commercial Office Building Tenants

View Project

Data Quality and Reliability Metrics for Building Energy Disclosure Data

View Project

CommunitySense

View Project

Machine Learning Approaches to Predict and Target Building Energy Retrofits

View Project

Using LiDAR to Analyze the Impact of Urban Morphology on Energy Use

View Project

The QC Urban Sensing Array

View Project

Recent Publications

Journal of the American Planning Association

Energy Cost Burdens for Low-Income and Minority Households: Evidence From Energy Benchmarking and Audit Data in Five US Cities

Kontokosta, C. E., Reina, V. J., & Bonczak, B. (2019). Energy Cost Burdens for Low-Income and Minority Households: Evidence From Energy Benchmarking and Audit Data in Five US Cities. Journal of the American Planning Association, 1-17.

Computers, Environment, and Urban Systems

Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data

Bonczak, Bartosz and Constantine E. Kontokosta. 2018. “Large-scale Parameterization of 3D Building Morphology in Complex Urban Landscapes Using Aerial LiDAR and City Administrative Data,” Computers, Environment, and Urban Systems, in press.

Nicholas Johnson

Postdoctoral Associate

Nicholas.johnson@nyu.edu

Nicholas E. Johnson is a Postdoctoral Associate in Civic Analytics at the NYU Marron Institute of Urban Management.

He obtained his PhD in Computer Science/Urban Science at University of Warwick’s Institute for the Science of Cities in 2018. Previously, Nicholas received a Masters degree from NYU’s Interactive Telecommunications Program in 2013 centering his work on exploring the impact and pervasiveness of waste streams in urban environments through physical computing and interaction design.  He has launched several citizen science initiatives and continues citizen-driven research as an organizer for the Public Laboratory for Open Technology and Science.  Nicholas’s current research focuses on the design and development of cyber-physical systems for monitoring urban environments and data-driven analyses to understand urban phenomena including waste generation and urban mobility,

Recent Projects

CommunitySense

View Project

Using Machine Learning and Small Area Estimation to Predicting Building-level Waste Generation and Recycling

View Project

The QC Urban Sensing Array

View Project

Recent Publications

Computers, Environment, and Urban Systems

Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities.

Kontokosta, C. E., Hong, B., Johnson, N. E., & Starobin, D. (2018). Using machine learning and small area estimation to predict building-level municipal solid waste generation in cities. Computers, Environment and Urban Systems.

Boyeong Hong

Postdoctoral Associate

boyeong.hong@nyu.edu

My research interests focus on how to apply urban informatics to real world problems in urban planning and operations.

I hold a master degree in Applied Urban Science and Informatics from NYU Center for Urban Science and Progress (CUSP) and a PhD in Civil Engineering (Urban Informatics) from NYU Tandon. While at CUSP, I was a Graduate Research Assistant in identifying E-Waste (Electronic waste) generation in New York City in addition to working on data analytics for capital planning with NYC Department of City Planning as part of my capstone. I also worked at the Pratt Center for Community Development translating geospatial data into problem solving insight through GIS mapping and analysis. Prior to CUSP, I have participated in various research projects related to urban planning and data analytics in Seoul, South Korea. In addition to my PhD and CUSP MS degree, I hold a Bachelor’s degree in Architecture from Yonsei University and a Master of City Planning degree from Seoul National University.

Recent Projects

Estimating Bias in 311 Service Request Data

View Project

Analyzing the Impacts of Urban Land Use Dynamics

View Project

Using Machine Learning and Small Area Estimation to Predicting Building-level Waste Generation and Recycling

View Project

Recent Publications

Sokratis Papadopoulos

PhD Candidate

sokratis.papadopoulos@nyu.edu
646.705.3295

Sokratis is a PhD candidate in Civil and Urban Engineering at NYU’s Tandon School of Engineering and NYU CUSP.

He holds an MSc in Engineering Systems and Management from Masdar Institute, UAE (2015). His research interests lie between applied data science and optimization of building energy performance, with an emphasis on human actions.

Recent Projects

The Impact of Mandatory Energy Audits on Energy Use in Buildings

View Project

Benchmarking, Feedback, and Behavior Change for Commercial Office Building Tenants

View Project

Machine Learning Approaches to Predict and Target Building Energy Retrofits

View Project

Recent Publications

Yuan Lai

Ph.D. Candidate

yuan.lai@nyu.edu
646.997.0612

Yuan Lai is currently a Ph.D. candidate in Urban Systems in the Department of Civil and Urban Engineering at the NYU Tandon School of Engineering and CUSP.

Yuan Lai is a Ph.D. candidate in Urban Systems at NYU Tandon School of Engineering. His research focuses on urban informatics and data-driven city development. He holds a M.S. in Urban Informatics from NYU CUSP and a M.S. in Urban Planning, specializing in urban design and GIS, from State University of New York at Buffalo. Prior to joining CUSP, he practiced as an architect with Moshe Safdie on large-scale building design and master planning projects. He is an Accredited Professional of Leadership in Energy & Environmental Design specialized in neighborhood development.

 

Recent Projects

Analyzing the Impacts of Urban Land Use Dynamics

View Project

The QC Urban Sensing Array

View Project

Recent Publications

Computers, Environment and Urban Systems

Topic Modeling to Discover the Thematic Structure and Spatial-temporal Patterns of Building Renovation and Adaptive Reuse in Cities

Lai, Y., & Kontokosta, C. E. (2019). Topic modeling to discover the thematic structure and spatial-temporal patterns of building renovation and adaptive reuse in cities. Computers, Environment and Urban Systems, 78, 101383.

Health & Place

The Impact of Urban Street Tree Species on Air Quality and Respiratory Illness: A Spatial Analysis of Large-Scale, High Resolution Urban Data

Lai, Yuan and Constantine E. Kontokosta, 2019. “The Impact of Urban Street Tree Species on Air Quality and Respiratory Illness: A Spatial Analysis of Large-Scale, High Resolution Urban Data,” Health & Place, in press.

Tabitha Julien

Civic Analytics Fellow


Tabitha F. Julien is a PhD candidate in Epidemiology at the NYU School of Medicine – Sackler Institute. As a spatial and social epidemiologist, her aim is to be at the forefront of neighborhood-based research, with an interdisciplinary approach to applied epidemiology to inform policy. Prior to being accepted to the Civic Analytics fellowship, she was awarded a NIH Diversity Supplement that investigates the effects of second-hand smoke on lower-respiratory infections among NYC public housing residents and examine the extent to which racial/ethnic and socioeconomic disparities exists between lower respiratory infections and second-hand smoke exposures in the context of multiunit housing.

Pablo Mandiola

Civic Analytics Fellow


Pablo is an MS candidate at NYU Center for Urban Science and Progress. He holds a Master of Public Administration from Columbia University and a BS in Industrial Engineering with a professional degree in Information Technology from Universidad Católica in Chile. Prior to his graduate studies, he was policy analyst and project manager for digital innovation initiatives at the Chilean Ministry of Housing and Urban Development, and also worked designing and leading technology projects for a large eCommerce company.

Cyrus Blankinship

Civic Analytics Fellow


Cyrus Blankinship is a Graduate Student at NYU’s Center for Urban Science and Progress (CUSP). His work focuses on data-driven approaches to urban design decision making. Prior to NYU, Cyrus was a GIS Analyst and Web Developer working in technology and real estate (Apple & CBRE). He holds his bachelors degree in architecture from the University of California, Berkeley.

Awais Malik

Ph.D Candidate, Civil & Urban Engineering (NYU Tandon) and NYU CUSP

awais.malik@nyu.edu
646.997.0544

Awais Malik is a Ph.D. Candidate in Civil and Urban Engineering at NYU Tandon and a Research Assistant at NYU CUSP.

He graduated from Dartmouth College in 2013 with an A.B. in Engineering Sciences with Honors and a B.E. in Mechanical Engineering. He was a member of Dartmouth’s $300 House Initiative, and received the Dean of Faculty grant to design and test affordable housing solutions for Haiti. Awais joined CUSP’s inaugural class of graduate students in 2013, and was one of the first research assistants at the Kontokosta Research Group. Awais received a Master of Science in Applied Urban Science and Informatics from CUSP in 2014. For the past two years, he has worked on forming a unified, multi-factor index of resilience capacity for New York City neighborhoods: the Resilience to Emergencies and Disasters Index (REDI). Awais’ current research focuses on understanding urban resilience by measuring near real-time neighborhood activity.

Recent Projects

CommunitySense

View Project

Machine Learning Approaches to Predict and Target Building Energy Retrofits

View Project

The Resilience to Emergencies and Disasters Index (REDI)

View Project

The QC Urban Sensing Array

View Project

Recent Publications

Stanislav Sobolevsky

Associate Professor of Practice, NYU CUSP

sobolevsky@nyu.edu
646.997.0527

Stanislav Sobolevsky is an Associate Professor of Practice at the Center for Urban Science and Progress at New York University and a Research Affiliate at the MIT Senseable City Lab.

Holds PhD (1999) and Doctor of Science habilitation degree (2009) in Mathematics. Dr. Sobolevsky teaches various data science and machine learning courses and applies his fundamental quantitative background to studying human behavior in urban context through its digital traces – spatio-temporal big data created by various aspects of human activity. His research interests cover network science, big data analytics, modeling of complex systems and the theory of differential equations. Authored one monograph, two textbooks and over 60 peer-reviewed papers in pure and applied mathematics, network science and mathematical modeling. His former professional experience includes research at MIT as well as research, teaching and administrative positions at Belarusian State University and Academy of Sciences of Belarus.

Martin Traunmueller

Civic Analytics Fellow

martin.traunmueller@nyu.edu

Martin is an architect and digital urbanist from Austria who is a Civic Analytics Fellow with the Urban Intelligence Lab..

After his architecture studies in Vienna, Martin worked as design architect professionally in Dubai and Vienna before he joined the MSc Adaptive Architecture and Computation course at The Bartlett / UCL in 2011. His interested in investigating the physical and digital relationships between an urban environment and it’s inhabitants, especially in the field of urban pedestrian navigation, led him to an award of an Intel sponsorship for his PhD at the ICRI Cities / Department of Computer Science, UCL. After graduation, Martin joined CUSP / NYU as Civic Analytics Fellow where he currently focus on modelling pedestrian flows in urban environments.

Tashay Green

Civic Analytics Graduate Student Fellow

tg1478@nyu.edu

Tashay is a M.S. candidate at NYU Center for Urban Science + Progress and Civic Analytics Graduate Student Fellow.

She holds a B.S. in Biology with a minor in Chemistry from Howard University. Prior to joining CUSP, Tashay was a secondary educator in Biological Science and Conceptual Physics. She also served as a Program Manager for a non-profit organization that teaches front-end web development to under-resourced students in New York City. Her current research focuses on using data analytics to address critical operational and policy challenges, and drive positive social impact within city agencies.

Emily Hansen

Graduate Research Assistant


Emily Hansen is a Graduate Research Assistant on the Quantified Community team. She is currently pursuing an M.S. in Applied Urban Science and Informatics at CUSP. She received a B.S. in Geophysical Sciences in 2017 from the University of Chicago, where she performed research in cryospheric remote sensing and archaeological applications of machine learning. Her current research interests include urban mobility and integrating social and data-driven strategies to analyze the effects of environmental conditions on urban activity.

Recent Projects

The QC Urban Sensing Array

View Project

Jack Lundquist

Civic Analytics Graduate Student Fellow


Jack is an M.S. candidate at NYU’s Center for Urban Science + Progress, and a Civic Analytics Graduate Student Fellow. He graduated from Stanford University in 2017 with a B.S. in Environmental Systems Engineering (Urban Track). Prior to joining CUSP and the Urban Intelligence Lab, he was a teaching and research assistant with Stanford’s Sustainable Urban Systems Initiative. Jack’s current research focuses on the development of data structures and models for the Women in Need (Win) shelter network.

Unisse Chua

Graduate Research Assistant


I hold a BS degree in Computer Science specializing in Software Technology with 5 years of work experience as a software engineer and a front-end developer. I have always been interested in using technology for urban development which is why I am pursuing further studies in Applied Urban Science and Informatics at New York University.

Daniel Marasco

Senior Computer Scientist, MITRE Corp.


Geoff Perrin

Civic Analytics Graduate Student Fellow

gtp232@nyu.edu

Geoff Perrin graduated from the University of Michigan with a BS in Economics and Mathematics, and is currently pursuing an MS in Applied Urban Science and Informatics at NYU’s Center for Urban Science and Progress. He’s built machine learning algorithms relating to various topics, from predicting Medicare fraud to predicting Levi’s jeans sales.

Recent Projects

Using Machine Learning and Small Area Estimation to Predicting Building-level Waste Generation and Recycling

View Project

Xinshi Zheng

Civic Analytics Graduate Student Fellow

xz1845@nyu.edu

Xinshi is a Master student and a Civic Analytics Graduate Student Fellow in the Urban Intelligence Lab.

He holds a M.S. in Civil Engineering from University of Illinois at Urbana-Champaign (2015), and a B.Eng in Architectural Environment Engineering from University of Nottingham, UK (2013). His research interests include developing data science applications for urban infrastructure planning and optimization, as well as geospatial analysis.

Recent Projects

Benchmarking, Feedback, and Behavior Change for Commercial Office Building Tenants

View Project

Using Machine Learning and Small Area Estimation to Predicting Building-level Waste Generation and Recycling

View Project

Machine Learning Approaches to Predict and Target Building Energy Retrofits

View Project

Kristi Korsberg

Civic Analytics Graduate Student Fellow

kk3374@nyu.edu

Kristi is a graduate student at New York University’s Center for Urban Science and Progress, pursuing a Masters of Science in Applied Urban Science and Informatics.

Her primary research interest is using data to improve operations and service delivery in the health care and criminal justice domains. Prior to joining CUSP, Kristi received her Bachelor of Arts from Harvard College in Government and Global Health and Health Policy.

Ian Stuart

Graduate Research Assistant, Building Informatics

is1480@nyu.edu

Ian is currently pursuing a MS in Applied Urban Science and Informatics from NYU CUSP.

His primary research interests involve the application of data analysis to urban sustainability challenges and resource efficiency. He is also studying the potential for emerging, data-intensive technologies to bring about drastic change in urban systems like transportation, housing, and energy.

Ian’s experience includes work in urban design, environmental consulting, and civic technology. HIs study of cities began with a BA in Urban Studies from Stanford University. He also holds a Master’s of Environmental Management from Duke.

Ian Wright

Graduate Research Assistant

iw453@nyu.edu

Ian's research and career interests are in next-gen power grids, microgrids, energy storage technologies, and renewables in the urban environment.

Ian received his B.S. in Mechanical Engineering (2011) from the University of Alberta, Canada, and is currently working towards an M.S. at NYU’s CUSP. Previously, he worked as a design engineer at an architectural firm, Dialog, designing building systems and modelling energy usage in buildings. Most recently he transitioned to the technology sector as a data analyst and strategist at a Vancouver company called Hootsuite.

Recent Projects

Benchmarking, Feedback, and Behavior Change for Commercial Office Building Tenants

View Project

Machine Learning Approaches to Predict and Target Building Energy Retrofits

View Project

Ryan Sims

Ryan Sims

Undergraduate Research Assistant

rts347@nyu.edu

As a Summer Research Student at CUSP, Ryan Sims works closely with PhD Candidate, Nicholas E. Johnson and Dr. Constantine E. Kontokosta to further the development of the Quantified Communities (QC). Ryan’s research goals are to understand, replicate, and improve the sensors which collect data from the QCs.

In addition to his research at CUSP, Ryan Sims is in route, as a college junior, to complete his undergrad at Northern Illinois University with a B.S. in Energy and Environmental Engineering Technology

Recent Projects

CommunitySense

View Project

The QC Urban Sensing Array

View Project

Raka Dey

Undergraduate Research Assistant

raka.dey@nyu.edu

Raka Dey is a rising senior at the NYU Tandon School of Engineering currently pursuing her BS in Sustainable Urban Environments. She is at CUSP for the summer doing research on the Qualified at Hudson Yards project. Aside from engineering, she has focused her studies on architecture, public policy, and urban planning. Through her research here, she hopes not only to gain skills in data science, but also combine her various academic interests. Raka will continue her research on this project during the school year through her Smart Cities class.

Recent Projects

CommunitySense

View Project

The QC Urban Sensing Array

View Project