Data to Knowledge —
Multi-scale Approaches to Complex Data
Complex problems require interdisciplinary solutions. The Rensselaer Data Science Research Center develops the technologies to enable that multidisciplinary research.
The Rensselaer Data Science Research Center acquires, processes, archives, analyzes, model, visualizes, simulates, and disseminates complex data to close the data-to-knowledge gap across multiple time and length scales.
Transforming Data, Joining Disciplines
The DSRC serves as a melting pot of ideas and expertise in research areas such as computer science, biology, engineering, mathematics, physics, environmental science, library and social sciences.
One objective of DSRC investigators is bridging the gaps between mathematical sciences and life sciences by developing data driven models and algorithms. Researchers unlock the power of multiscale models by making complex data accessible to scientists from a broad scope of disciplines.
At the DSRC, researchers add semantics to data—rendering it useful in a variety of machines and programs; use smart storage techniques; mine data to maximize extractable knowledge; build models representing the structure of data, and—using those models—build simulations and visualizations of data to display data in usable ways and predict how the data will change over time.
The DSRC facilitates collaboration and inter- action among not only RPI students, post-docs, and faculty but also investigators from external institutions in academia and industrial research labs. The investigators in the center study data intensive complex problems in diverse application areas including medicine, oceanography, and networks (e.g., telecommunication, data, grid).
Meeting the Need for Data Science Research
The objective of DSRC is to become a center with national and international visibility, and provide support and infrastructure to its members for solving data centric and data intensive research problems by capitalizing on Rensselaer’s super computer center (CCNI) and experimental media and performing arts center (EMPAC). Members of DSRC will collaborate and interact via workshops in specific topics, group meetings, seminars, student internships at industrial research labs. DSRC will offer an educational and training program for graduate students and post-docs to prepare the next generation data scientist and engineers.
The scientific focus of the center is on multiscale approaches to complex data obtained from diverse domains including biomedical, environmental, engineering and social domains. The Center aims to vertically integrate solutions to several core challenges of data science.
Challenges in Data Science
- Data acquisition enhancement and storage
- Data complexity
- Modeling, analysis, learning and knowledge extraction
- Simulation and visualization
- Security and privacy
- Curtis R. Priem Experimental Media and Performing Arts Center—With an impact reaching across the entire spectrum of the Rensselaer experience, EMPAC provides students, researchers, artists, and audiences with opportunities to link the arts with leading-edge research and performance.
- Computational Center for Nanotechnology Innovations—One of the world’s most powerful university-based supercomputing centers, CCNI advances semiconductor technology at the nanoscale, and is enabling key nanotechnology innovations in the fields of energy, biotechnology, new materials, arts, and medicine.
- Center for Biotechnology and Interdisciplinary Studies —The research center ranks among the world’s most advanced facilities focused on the application of engineering and the physical and information sciences to the life sciences.
- Games, Simulation Arts & Sciences Program—As one of the top ranked undergraduate programs of its kind in the country, GSAS is a well spring of talent uniquely qualified to collaborate on projects related to simulation and modeling.
DSRC researchers collaborate with
- Research universities (e.g., Mount Sinai School of Medicine)
- Industrial research labs (e.g., GE Global Research, IBM Research, General Dynamics)
- Non-profit research institutions (e.g., Woods Hole Oceanographic Research Institution, Wadsworth Research Center, MIT Lincoln Labs).
DSRC has also started close collaboration with IDEA.
- The Rensselaer Institute for Data exploration and applications (IDEA) has been recently established to enable research across Rensselaer to access technologies via the development of critical computational methodologies including data-intensive supercomputing, large-scale agent-based simulation, and cognitive computing technologies.