Incubated Research

In conjunction with our research strategy to invest in the future, we selectively seed fund new collaborations that cross typical disciplinary boundaries, and that support ambitious research and forward-looking education initiatives.  Our archive of current and previously funded projects represent a broad array of the exciting new computing-related and data-driven research happening across the BU community. All Institute affiliated faculty are eligible to apply for these awards.

Hariri Institute Research Incubation and Digital Health Initiative Research Awards (active awards)

  • BU Research Magazine Highlights a Hariri Institute Research Team’s Work in Machine Learning.

    This past September 2018 a Data Science Faculty Fellow, Hariri Junior Faculty Fellow, and a past Hariri Fellow were highlighted in an article in BU Research magazine for their work developing a machine that can measure public sentiment about a given topic or event online. Where did this all start?... [ More ]

  • Tools for Detection of DNA Genomic Structural Variants and Application to the Analysis of Human Whole Genome Sequencing Datasets

    Pl: Gary Benson, Bioinformatics, Computer Science, Biology, CAS Collaborators: Paola Sebastiani, School of Public Health, SPH; Uwe Beffer, Biology, CAS The project aims to develop the mathematical tools necessary to assess and correct read mapping accuracy in repeat rich genomic regions. Additionally, the goal is to develop efficient algorithms to identify SVs... [ More ]

  • SeCNet: Synthesis and Control for Networks of Trust

    Pl: Wenchao Li, Electrical and Computer Engineering, ENG Co-Pl: Roberto Tron, Mechanical Engineering, ENG By taking advantage of the physical-sensing capabilities of robots, it is possible to craft a cyber-resilient network that can provide strong guarantees on the safety, reliability, security, and performance of the overall system. At the core of the... [ More ]

  • Team Formation: Algorithms and Practical Applications

    Pl: Evimaria Terzi, Computer Science, CAS Co-Pl: Ziba Cranmer, Spark! The project aims to close the loop between the theory and practice of team-formation by developing the necessary computational concepts and eventual software that will enable the application of the team-recommendation algorithms to a variety of educational scenarios. Doing so will then make it... [ More ]

  • Data-Driven Design of Tough 3D Printed Structures

    Pl: Emily Whiting, Computer Science, CAS Co-Pls: Keith Brown, Mechanical Engineering, ENG; Elise Morgan, Mechanical Engineering, ENG The project converges machine learning, physical experimentation, and design to address the general question of how to optimize a design when the fitness function can only be reliably determined through physical experimentation. Using a data-driven approach, it will combine... [ More ]

  • Traveling Back to the Future: Using Network Science to Unravel Evolutionary Conserved RNA Binding Proteins and Complexes Associated with Disease

    Pl: Simon Kasif, Biomedical Engineering, ENG Co-Pls: Mark Crovella, Computer Science, CAS; Andrew Emili, Biochemistry, MED This project aims to advance fundamental knowledge of biology and open new opportunities for developing early diagnostics, prognostics and perhaps even novel therapeutically promising approaches to a devastating disease, Alzheimer’s.The significant cost, time, and effort required for... [ More ]

  • A Scalable and Secure Cyberinfrastructure for the Repeatability of Ecological Research

    Pl: Michael Dietz, Earth & Environment, CAS Co-Pl: Abraham Matta, Computer Science, CAS The goal of this project is to build a scalable, cloud-based system for submitting, generating, archiving, and disseminating multi-model ecological forecasts. Beyond advancing ecological research and socially-useful forecasts, this system will contribute to the more general development of a scalable and... [ More ]

  • Mapping Sound

    Pl: Joanna Davidson, Anthropology, CAS Co-Pl: Marie Abe, Ethnomusicology, CFA Despite the importance of what people say and hear towards understanding complex variations in human perception, experience, narratives, and signifying practices, as of today, there is not a publicly available digital tool to explore and visualize auditory patterns across space and time. [ More ]

  • Fitness Improvement and Tracking Tool (FITT)

    Pl: Deepak Kumar, Physical Therapy & Athletic Training, SAR Co-Pls: Belinda Borrelli, School of Dental Medicine, SDM; Tuhina Neogi, Medicine, MED The project aims to develop an mHealth intervention to increase physical activity (PA) levels in people with knee osteoarthritis (OA) that is responsive to the severity and prevalence of poor sleep, [ More ]

  • Mapping of Posttraumatic Stress Disorder

    Pl: Michael Otto, Psychological & Brain Sciences, CAS The project aims to communicate research results in a new format that allows for better interpretation by clinicians. The project will display qualitative and quantitative information on the efficacy of interventions using a topographical map approach. The topographical map approach is intended to... [ More ]

  • Development of Infrastructure Platform for e-cognitive Studies

    Pl: Honghuang Lin, Medicine, MED Co-Pls: Rhoda Au, Neurology, MED The project aims to explore novel digital devices to monitor cognitive function as part of e-Cognitive Health Initiative (e-CHI), which is built around the lessons learned from the Framingham Cognitive Aging program, the most comprehensive cognitive aging database in the world. The... [ More ]

  • Optimizing Discharge Decisions to Reduce Surgery Re-Admissions

    Pl: Ioannis Paschalidis, Electrical & Computer Engineering, ENG Co-Pls: George Kasotakis, Surgery, MED This project aims to develop predictive analytics to predict re-admissions within 30-days from discharge after surgery. Researchers will begin with a dataset of 5,769 BMC patients and then expand the project’s scope to 2,275,452 patients in order to improve... [ More ]

  • Mobile App for TBI Assessment

    Pl: Anna Hohler, Neurology, MED Co-Pls: Monica Parker-James, Medicine, MED This project is developing a mobile gaming application for those exposed to head trauma. The app would engage users in a fun way while it conducted a preliminary assessment of the head trauma and then used that data to make a recommendation... [ More ]

  • Overdose Prevention Mobile App Prototype

    Pl: Abby Rudolph, Epidemiology, SPH The project aims to develop a prototype for an overdose prevention mobile app. The team will work to expand access to overdose prevention trainings, since most overdose prevention programs train persons who use drugs (PWUD) in-person. The project will increase access to refresher trainings, as needed... [ More ]

  • ExerciseCheck: Remote Monitoring and Evaluation Platform for Home Based Physical Therapy

    Pl: Margrit Betke, Computer Science, CAS Co-Pls: Theresa Ellis, Physical Therapy & Athletic Training, SAR ExerciseCheck is a new digital health system designed to support rehabilitation. Users will exercise in front of a Microsoft Kinect motion sensing interface and a webcam that records the patients’ movement trajectory and provides visual feedback to... [ More ]

  • A Text-Messaging Approach to Improving Self-Management of Chronic Conditions among Boston’s Highest Utilizing Homeless Persons

    Pl: D. Keith McInnes, Health Law, Policy & Management, SPH Co-Pls: Thomas Byrne, Social Welfare Policy, SSW This project aims to develop text messaging interventions for homeless patients that will promote greater access to chronic disease self-management and outpatient care. To do so, the team will work with homeless patients to review... [ More ]

  • Enabling Data Science for Medicine

    Pl: Gerald Denis, Medicine, MED Co-Pls: Naomi Ko, Medicine, MED; Mayank Varia, RISCS This project aims to bridge the gap between available medical data and the regressive infrastructure of clinical data sharing. After analyzing datasets held by researchers at BU’s School of Medicine, the team will establish a common format for clinical... [ More ]

  • Leveraging Smartphone Sensing Technology to Identify Social Isolation in Mental Illness

    Pl: Daniel Fulford, Occupational Therapy, SAR Co-Pls: Richard West, Computer Science, CAS; Yuting Zhang, Computer Science, MET Social isolation occurs as a result of mental health conditions such as depression and schizophrenia, which can lead to further disability and early mortality. Medication can reduce many symptoms of mental health conditions but not... [ More ]

  • Automatic Assessment of Room Clutter for Improved Hoarding Disorder Assessment, Treatment, and Prevention

    Pl: Janusz Konrad, Electrical & Computer Engineering, ENG Co-Pls: Jordana Muroff, Clinical Practice, SSW This project aims to develop an objective, automatic, real-time method for rating room clutter from images according to the CIR scale. Currently, Hoarding Disorder symptoms are examined using a self-report and clinical review. The Clutter Image Rating (CIR) scale... [ More ]

  • Machine Learning-Driven Quantification of Pathological Fibrosis for Prognostic Relevance

    PI: Vijaya Kolachalama, Medicine, MED Co-PIs: Katya Ravid, Medicine, MED; Vipul Chitalia, Medicine, MED; David Salant, Medicine, MED The project proposes to use artificial intelligence (AI) methods to derive quantitative information from the kidney biopsy images that can guide the development of effective treatments.  The burden of chronic kidney disease is enormous both for patients and the... [ More ]

  • Statistical Physics of Nonstationary Long-Range Correlated Neural Time Series

    PI: Gene Stanley, Physics, Chemistry, Biomedical Engineering and Physiology (CAS, ENG & MED) Co-PIs: Marc Howard, Psychological & Brain Sciences, CAS; Howard Eichenbaum, Psychological & Brain Sciences, CAS This project aims to study neural time series in a wide range of animal models and brain regions using sophisticated methods from statistical physics. It will... [ More ]

  • Toward a Cloud-based ‘Reproducibility Engine’ for Human NeuroImaging Research

    PI: David Somers, Psychological & Brain Sciences, CAS Co-PIs: David Osher, Psychological & Brain Sciences, CAS The project proposes the establishment of a reproducibility engine for neuroimagers, employing the power of the Massachusetts Open Cloud (MOC), which will empower researchers to easily and quickly analyze hundreds of subjects and either replicate, or fail... [ More ]

  • Urban Refuge: Putting Aid on the Map

    PI: Noora Lori, International Relations, Pardee School of Global Studies The project seeks to create the backend of the Urban Refuge, beta-test and launch the product in Amman in 2017. Urban Refuge is a smartphone application providing refugees with new tools for navigating insecurity and managing crises. Furthermore, Urban Refuge enhances... [ More ]

  • Social Networks at Microscale

    PI: Kirill Korolev, Physics, CAS Co-PIs: Daniel Segre, Biology, Bioinformatics, and Biomedical Engineering (CAS & ENG) The project aims to develop a computational tool that can use microbial genomes to predict microbial interactions and ultimately ecosystem dynamics. Beyond prediction, this computational tool will be used to develop design principles for artificial communities and... [ More ]

  • Nielsen Retail Scanner Data Database

    PI: Adam Guren, Economics, CAS This project seeks to create a scalable structural database that allows for relational queries to make the Nielsen data more easily used for research. This project will have broader impacts across Boston University as many faculty across the university have expressed interest in extracting from this... [ More ]

  • eMap: Online Mapping Electron Transfer Channels in Proteins

    PI: Ksenia Bravaya, Chemistry, CAS This project is developing a computational platform for automated pre-screening of protein X-ray structure for efficient ET channels from user-defined source residue or co-factor to surface-exposed amino acids and its implementation as a robust web application. The developed web-based application, eMap, will enable prediction of electron... [ More ]

  • The Relationship between Cult and the Natural Landscape in Ancient Greece

    PI: Andrea Berlin, Archaeology, CAS The project aims to develop a model that interrogates the visual and spatial relationships between Greek sanctuaries and the natural landscape. The major innovation of project is the plan to collate, preserve, and present data in an online, interactive platform so that future users can perform... [ More ]

  • IKEA: Product, Pricing, and Exchange Rate Pass-through

    PI: Marianne Baxter, Economics, CAS Co-PI: Margrit Betke, Computer Science, CAS The project seeks to use detailed catalog information on products and page layout to advance an understanding of the decision-making process of IKEA – the world’s largest furniture retailer, with stores in 41 countries and annual revenue estimated at $24 billion. [ More ]

  • Statistically Principled and Scalable Computational Tools for Transforming Research

    PI: Lei Guo (Emerging Media Studies, COM) Co-PIs: Prakash Ishwar (Electrical & Computer Engineering, ENG), Margrit Betke (Computer Science, CAS) Collaborators: Jacob Groshek (Emerging Media Studies, COM), Dino Christenson (Political Science, CAS) This research is part of an ongoing project that is exploring reliable and valid methods to analyze large-scale social data in... [ More ]

  • Imagine All the People: The Origins of Education Reform and the Life Trajectories of Low-Skill Youth

    PI: Cathie Jo Martin (Political Science, CAS) This project uses computational linguistics to evaluate the cultural origins of diverse models of education reform – standards-setting versus social investment – and their implications for socioeconomic inequality. National standards to ensure uniform educational opportunities, in fact, increase the drop-out rates of low-skill youth. [ More ]

  • An Ongoing Streaming Sample Twitter Collection and Analysis Toolkit

    PI: Jacob Groshek (Emerging Media Studies, COM) Collaborators: Manuel Egele (Electrical & Computer Engineering, ENG) This project seeks to develop alternative and robust collection, storage, and analysis capabilities to perform research based on communications sent via Twitter. Twitter is one of the most popular and frequently used online social networks (OSNs), and... [ More ]

  • Enabling High Fidelity Imaging and Quantification of Tissue Mechanical Properties in Vivo through Access to Sophisticated Inverse Problem Solvers

    PI: Paul Barbone (Mechanical Engineering, ENG) This project aims to bring new imaging capabilities, enabled by high-performance computing, to a wide cadre of biomedical researchers through a Biomechanical Imaging Science Gateway (BIG@BU) web portal. The BIG@BU Gateway will provide public access to advanced software to solve inverse problems in Biomechanical Imaging. [ More ]

  • Graph-Based Approaches to Record Linkage in Large Datasets

    PI: Jacob Bor (Global Health, SPH) Collaborators: George Kollios (Computer Science, CAS), Katia Oleinik (IS&T), Lorenzo Orecchia (Computer Science, CAS) This project will develop, implement, validate, and publish graph-based methods for probabilistic record linkage. Researchers will investigate different approaches to integrating information contained in the network structure of the data and assess... [ More ]

  • Coupled Human-Natural Dynamics in Urban Heat Islands: From Big Data to Local Policies

    PI: Lucy Hutyra (Earth & Environment, CAS) Collaborators: Dan Li (Earth & Environment, CAS), Mark Friedl (Earth & Environment, CAS) This project is mining cell data for high-resolution spatio-temporal CO2 emissions models to produce a mutidecadal assessment of trends, drivers, and scaling relationships. In order to inform the design of urban heat... [ More ]

  • Interdisciplinary Development of a Biokinematic Data Acquisition System

    PI: Richard West (Computer Science, CAS) Collaborators: Cara Lewis (Health Sciences, SAR), Sheryl Grace (Mechanical Engineering, ENG) This project is developing an on-body, biokinematic data acquisition and analysis tool that tracks the body position of ice hockey skaters during stride production. This research aims to inform future inquiries in the following areas:... [ More ]

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