1. Campus P–16 STEM Education Outreach
- CAREER: Bayesian Models for Lexicalized Grammars
- CAREER: Investigation of DNA-Binding Protein Dynamics With High-Resolution Optical Traps
- CAREER: Large-Scale Recognition Using Shared Structures, Flexible Learning, and Efficient Search
- CAREER: Theory and Application of Reflective Microring Resonators
- Collaborative Research: Variability-Aware Software for Efficient Computing with Nanoscale Devices
- Girls Adventures in Mathematics, Engineering and Science (G.A.M.E.S.)
- Metasearch Gateway Services for the Distributed NSDL Community
CAREER: Bayesian Models for Lexicalized Grammars
Natural language processing (NLP) is a key technology for the digital age. At the core of most NLP systems is a parser, a program which identifies the grammatical structure of sentences. Parsing is an essential prerequisite for language understanding. But despite significant progress in recent decades, accurate wide-coverage parsing for any genre or language remains an unsolved problem. This project will advance the state of art in NLP technology through the development of more accurate statistical parsing models.
Since language is highly ambiguous, parsers require a statistical model which assigns the highest probability to the correct structure of each sentence. The accuracy of current parsers is limited by the amount of available training data on which their models can be trained, and by the amount of information the models take into account. This project aims to advance parsing by developing novel methods of indirect supervision to overcome the lack of labeled training data, as well as new kinds of models which incorporate information about the prior linguistic context in which sentences appear. It employs Bayesian techniques, which give robust estimates and allow rich parametrization, and applies them to lexicalized grammars, which provide a compact representation of the syntactic properties of a language.
Education Component: This project will also train graduate students in NLP and develop materials that can be used to teach middle and high school students about NLP and to inspire them to pursue an education in computer science.
CAREER: Investigation of DNA-Binding Protein Dynamics With High-Resolution Optical Traps
A broad class of DNA-binding protein interacts with the genome in a non-sequence-specific manner. These proteins act mechanically on their substrates, altering DNA conformation by bending, twisting, or stretching the molecule, and oligomerizing to form long filaments. These nucleoprotein complexes often serve as substrates upon which genome maintenance processes occur. Thus, they are involved in all aspects of DNA metabolism, in replication, recombination, and repair, and are important regulators of cellular processes. Single-stranded DNA binding proteins (SSB) serve as a model system for features common to this class of proteins. This project will use a synthesis of techniques from traditional biochemistry and molecular biology, in combination with single-molecule biophysics and computational biology to investigate: (1) how SSBs induce conformational rearrangement of nucleic acids, (2) how they oligomerize into nucleoprotein filaments, and (3) how these protein clusters recruit and modulate the activity of other proteins involved in nucleic acid processing. Specifically, high-resolution optical trapping in combination with single-molecule fluorescence techniques will be used to reveal dynamic protein-DNA interactions, going beyond the limitations of current methods. This work will shed light on fundamental aspects of genome maintenance.
Education Component: The PI has a deep commitment to interdisciplinary education of young scientists and outreach towards underrepresented groups. In particular, he sees in biophysics a unique opportunity to recruit women, who have traditionally been drawn to biology over physics, into the quantitative sciences. The outreach and education components of the project synthesize these themes into a broad plan targeting middle and high school, undergraduate, and graduate education. Specifically, the PI will: (1) develop a lab camp for a girls' summer program to teach middle and high school girls about physics and its impact on biological problems and to provide hands-on experience with biophysics, (2) improve the teaching of an introductory undergraduate physics course for life science students (the majority of whom are women) to better connect physics concepts with biology and medicine, (3) develop a lab course devoted to the training of the next generation of biophysicists in advanced technologies as part of the NSF Center for the Physics of the Living Cells (CPLC), and (4) participate in yearly minority conferences. This project is jointly supported by the Genes and Genome Systems Cluster and the Biomolecular Systems Cluster in the Division of Molecular and Cellular Biosciences.
CAREER: Large-Scale Recognition Using Shared Structures, Flexible Learning, and Efficient Search
This research investigates shared representations, flexible learning techniques, and efficient multi-category inference methods that are suitable for large-scale visual recognition. The goal is to produce visual systems that can accurately describe a wide range of objects with varying precision, rather than being limited to identifying objects within a few pre-defined categories. The main approach is to design object representations that enable new objects to be understood in terms of existing ones, which enables learning with fewer examples and faster and more robust recognition.
The research has three main components: (1) Designing appearance and spatial models for objects that are shared across basic categories; (2) Investigating algorithms to learn from a mixture of detailed and loose annotations and from human feedback; and (3) Designing efficient search algorithms that take advantage of shared representations.
The research provides more detailed, flexible, and accurate recognition algorithms that are suitable for high-impact applications, such as vehicle safety, security, assistance to the blind, household robotics, and multimedia search and organization. For example, if a vehicle encounters a cow in the road, the vision system would localize the cow and its head and legs and report "four-legged animal, walking left," even if it has not seen cows during training.
Education Component/Dissemination: The research also provides a unique opportunity to involve undergraduates in research, promote interdisciplinary learning and collaboration, and engage in outreach. Research ideas and results are disseminated through scientific publications, released code and datasets, public talks, and demonstrations for high school students.
CAREER: Theory and Application of Reflective Microring Resonators
The objectives of this program are to characterize, model, and utilize reflective microring reflectors. The PI proposes engineering novel device functionality by integrating a Bragg reflector in a microring resonator. The microring amplifies grating reflection, creating a compact mirror with high reflectivity, narrow linewidth, and no side lobe ripple. These benefits would reduce channel crosstalk and potentially result in lower power, higher data rate communication systems.
The research will advance scientific understanding of the device and demonstrate its potential as a fundamental element to the photonics community. The PI proposes to leverage his preliminary results in device theory, experience in lasers, sensors, and nanofabrication, and experimental capabilities and resources. This potentially transformative research may unlock new lines of research (new devices and models) and enable diverse applications (interferometry, metrology, RF photonics, and communications). Two specific applications will be explored: as cavities for on-chip absorption spectroscopy and as mirrors for tunable lasers.
The broader impacts will be to create novel devices for next generation communications and consumer electronics.
Education Component: Research and teaching will be integrated through the development of two courses: Principles of Experimental Research and Modeling of Photonic Devices. Recruitment, retention, and participation of students from underrepresented groups will be addressed through mentoring, REU internships, and a new electrical engineering summer camp for 10th-12th grade girls. Results from both research and teaching will be published to enhance the current understanding of reflective microring devices and engineering education/outreach methodologies.
Collaborative Research: Variability-Aware Software for Efficient Computing with Nanoscale Devices
As semiconductor manufacturers build ever smaller components, circuits and chips at the nano scale become less reliable and more expensive to produce, no longer behaving like precisely chiseled machines with tight tolerances. Modern computing is effectively ignorant of the variability in behavior of underlying system components from device to device, their wear-out over time, or the environment in which the computing system is placed. This makes them expensive, fragile and vulnerable to even the smallest changes in the environment or component failures. We envision a computing world where system components—led by proactive software— routinely monitor, predict, and adapt to the variability of manufactured systems. Changing the way software interacts with hardware offers the best hope for perpetuating the fundamental gains in computing performance at lower cost. The Variability Expedition fundamentally rethinks the rigid, deterministic hardware-software interface to propose a new class of adaptive, highly energy efficient computing machines which will be able to discover the nature and extent of variation in hardware, develop abstractions to capture these variations, and drive adaptations in the software stack from compilers, runtime to applications. The resulting computer systems will continue working though components vary in performance or grow less reliable over time and across technology generations. A fluid software-hardware interface will mitigate the variability of manufactured systems and make machines robust, reliable and responsive to changing operating conditions.
The Variability Expedition marshals resources of researchers at Illinois and other universities. With expertise in process technology, architecture, and design tools on the hardware side, and in operating systems, compilers and languages on the software side, the team also has the system implementation and applications expertise needed to drive and evaluate the research as well as transition research accomplishments into practice via application drivers in wireless sensing, software radio and mobile platforms.
A successful Expedition will dramatically change the computing landscape. Re-architecting software to work in a world where monitoring and adaptation are the norm will achieve more robust, efficient and affordable systems able to predict and withstand hardware failures, software bugs, and even attacks. The new paradigm will apply across the entire spectrum of embedded, mobile, desktop and server-class computing machines, yielding particular gains in sensor information processing, multimedia rendering, software radios, search, medical imaging and other important applications.
Education Component: Transforming the relationship between hardware and software presents valuable opportunities to integrate research and education, and this Expedition will build on established collaborations with educator-partners in formal and informal arenas to promote interdisciplinary teaching, training, learning and research. Strong industrial and community outreach ties will ensure success and outreach to high-school students through a combination of tutoring and summer school programs. The Expedition will engage undergraduate and graduate students in software, hardware, and systems research, while promoting participation by underrepresented groups at all levels and broadly disseminating results within academia and industry.
G.A.M.E.S. participants working in lab.
University of Illinois / Urbana, Illinois – Girls Adventures in Mathematics, Engineering, and Science (G.A.M.E.S) Summer Camp is an annual week-long residential camp designed to give academically talented middle school girls an opportunity to explore math, science, and engineering careers through demonstrations, classroom presentations, hands-on activities, and contact with women in these technical fields.