Our Team

The Sustain project is a collaboration between Colorado State University, Arizon State University, University of California — Irvine, and the University of Maryland – Baltimore County.

The project includes an advisory board that includes representation from academia, industry, and citizen science.

Shrideep Pallickara is a Professor of Computer Science at Colorado State University. Pallickara’s research encompasses methodological and algorithmic innovations in three broad areas: (1) spatiotemporal data management and analytics, (2) file systems, and (3) stream processing for Internet-of-Things and Cyber Physical Systems settings. Systems software resulting from these research efforts have been deployed in domains such as brain computer interfaces, epidemiology, earthquake science, environmental and ecological monitoring, health care systems, high energy physics, defense applications, geosciences, GIS, and commercial internet conferencing systems. Pallickara is a recipient of the Monfort Professorship and the National Science Foundation’s CAREER award.

 Mazdak Arabi is a Borland Chair and Professor in the Department of Civil and Environmental Engineering at Colorado State University. Arabi’s research is primarily focused on development of decision support systems for management of water resources at the watershed scale. To make informed decisions, policy makers should have the tools necessary to identify areas that are most vulnerable to erosion and contaminant transport, and subsequently assess tradeoffs between environmental and economic impacts of management actions. Arabi has developed and demonstrated optimization-based approaches to facilitate development of watershed management plans that achieve water quality goals at significantly lower costs. He has published analytical and computational methods to support both deterministic and probabilistic evaluation of watershed-scale benefits of best management practices

Jay Breidt, Professor of Statistics at Colorado State University, is an expert in survey sampling, time series, nonparametric regression, and uncertainty quantification for complex scientific models. Breidt has been an associate editor for eight journals and reviews editor for Journal of the American Statistical Association and The American Statistician.  He has served on six review committees for the National Academy of Sciences.  He is past Chair of the American Statistical Association National Committee on Energy Statistics, has served two terms on the Federal Economic Statistics Advisory Committee, and is currently a member of the Census Scientific Advisory Committee.  Breidt has been recognized with a national prize in environmental statistics and elected membership in the International Statistical Institute.  He is an elected Fellow of the American Statistical Association and an elected Fellow of the Institute of Mathematical Statistics.

Sudipto Ghosh is a Professor of Computer Science at Colorado State University. He received the Ph.D. degree in Computer Science from Purdue University in 2000. His research interests are in the areas of modeling and testing software in the object-oriented, aspect-oriented, and component-based paradigms. Specific topics include data warehouse testing, fault localization, model-based software development, mutation testing and higher order mutation, and regression test selection. Ghosh is on the editorial boards of IEEE Transactions on Reliability, Software Quality Journal, and Information and Software Technology

Sangmi Pallickara is a Cochran Family Professor and an Associate Professor in the Computer Science Department at Colorado State University. Pallickara’s research interests are in the area of Big Data for the sciences with an emphasis on issues related to predictive analytics, storage, retrievals, and metadata management. She is the Associate Editor of the IEEE Transactions on Parallel and Distributed Systems and serves on the editorial board of the Journal of Big Data, Springer. She is a recipient of the IEEE TCSC Award for Excellence in Scalable Computing (Mid-Career) and the National Science Foundation’s CAREER award.

Mikhail Chester is an Associate Professor of Civil, Environmental, & Sustainable Engineering at the Arizona State University. Chester’s research focuses on the increasingly complex challenges for infrastructure in the Anthropocene. A key goal in Chester’s research is to provide insights into how we can transition the management and design of infrastructure in the face of increasing complexity characterized by accelerating and increasingly uncertain conditions such as emerging and disruptive technologies (including artificial intelligence), climate change, financing, and cybersecurity/warfare. This work has led to recommendations for transitioning how we govern, educate for, and build infrastructure for the future.

Amir AghaKouchak is a Professor of Civil and Environmental at the University of California, Irvine. His research aims to bridge between the disciplines of hydrology, climatology, and remote sensing to address critical global water resource issues. AghaKouchak is particularly interested in combining remote sensing techniques and physically-based and statistical approaches in order to develop more reliable models of large-scale hydrologic systems. The long-term research objective is to utilize continuously growing satellite data along with ground-based observations to develop/improve integrated drought, flood and landslide modeling, prediction and decision support systems.

Claire Welty is a Professor of Environmental Engineering and the Director, Center for Urban Environmental Research and Education at the University of Maryland Baltimore County. Welty’s interests are in developing an end-to-end system of field-deployed sensors and fully coupled groundwater-surface water mathematical models to quantify and predict the urban hydrologic cycle and coupled biogeochemical cycles from neighborhood to regional scales. A key goal is to be able to assimilate sensor data into hydrologic and water quality models in near-real time for predicting flow paths, fluxes and stores of water and chemicals on land surfaces and in the subsurface. Welty works in collaboration with the NSF Baltimore Ecosystem Study Long-Term Ecological Research Site and the USGS MD-DE-DC Water Science Center. While methods are being developed using place-based research in Baltimore area, the methods are widely applicable to other urban areas.


Caleb Carlson
Daniel Rammer
Daniel Reynolds
Keegan Millard
Kevin Bruhwiler
Laksheen Mendis
Menuka Warushavithana
Saptashwa Mitra
Sanket Mehrotra
Thilina Buddhika
Walid Budgaga

Caleb is pursuing a Master’s degree at CSU directly after obtaining a Bachelor’s degree in May 2020. His area of interests include distributed systems, high-capacity storage solutions, and high-performance networking. Beginning fall of 2020, Caleb will be working on containerizing and orchestrating the SUSTAIN components to allow for improved scalability and high availability.

Daniel Rammer is pursuing his Ph.D. in Computer Science at Colorado State University. His work on the Sustain project targets analytics over data sketches. In particular, this includes support for constructs such as RDDs, DataFrames, and Datasets that span multiple machines to facilitate high-performance analyses. He is also interested in supporting data wrangling operations over satellite data with diverse coordinate projection systems.

Daniel Reynolds is an undergraduate student in Computer Science at Colorado State University. His research on the Sustain project has focused on supporting scalable visual analytics over spatiotemporal datasets.,Daniel Reynolds is an undergraduate student in Computer Science at Colorado State University. His research on the Sustain project has focused on supporting scalable visual analytics over spatiotemporal datasets.

Kevin Bruhwiler is a graduate student at Colorado State University’s Department of Computer Science. He is especially interested in the ways in which data can be used to learn about complex phenomena, such as the human and economic impacts of climate change or the ways in which information disseminates over various networks. The primary goal of his research is to create systems in which huge amounts of data can be stored and easily interacted with to facilitate rational decision making and scientific discovery.

Laksheen Mendis is a graduate student in Computer Science department at Colorado State University. Her main interests are in Big Data and Machine Learning. She is currently working on (KNN) queries over data sketches.

Menuka Warushavithana is pursuing his Ph.D. in Computer Science at Colorado State University. His research is focused on facilitating queries over multi-feature, voluminous spatial datasets based on geometry and predicate logic.

Paahuni Khandelwal is pursuing her Ph.D. in Computer Science at Colorado State University. She completed her bachelor’s degree in Computer Science from Delhi University, India.  Her research interests are in analyzing satellite imagery and developing efficient time-series prediction models.

Samuel Armstrong is pursuing his Ph.D. in Computer Science. His research interests are in the area of Big Data with a focus on advanced neural network architectures, predictive analytics, and high-performance distributed systems.In particular, his efforts focus on the development of Generative Adversarial Networks that are scalable, use state-of-the-art training methods, and learn from data in real time.

sanket mehrotra - grad-student

Sanket Mehrotra is pursuing his M.S in Computer Science, working in projects relating to tuning the performance of Big Data applications and Time Series outlier detection. His interests lie in natural language problems, web development of responsive applications and machine learning. He helped make this site and is having a blast dealing with web-platform design.

Saptashwa is pursuing his Ph.D. in. Computer Science at Colorado State University. His research has focused on supporting visualization at scale over spatiotemporal datasets.