
Sharad Mehrotra - US grants
Affiliations: | Computer Science | University of Illinois, Urbana-Champaign, Urbana-Champaign, IL | |
Information and Computer Science | University of California, Irvine, Irvine, CA |
Area:
Computer Science, Statistics, MathematicsWebsite:
https://ics.uci.edu/~sharad/We are testing a new system for linking grants to scientists.
The funding information displayed below comes from the NIH Research Portfolio Online Reporting Tools and the NSF Award Database.The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Sharad Mehrotra is the likely recipient of the following grants.Years | Recipients | Code | Title / Keywords | Matching score |
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1998 — 2004 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Career: Multimedia Analysis and Retrieval System @ University of Illinois At Urbana-Champaign This research focuses on developing an integrated multimedia information retrieval and database management infrastructure that provides support for multimedia information as first-class objects capable of being stored and retrieved based on their rich internal content. Specifically, techniques are being explored to (1) extract and represent multimedia content at multiple semantic levels useful for retrieval; (2) generalize text-based information retrieval approaches for content-based multimedia retrieval; (3) map high-level queries to lower-level representations supported by the database; (4) perform feature indexing that overcomes the high-dimensionality and non-euclidean nature of multimedia feature spaces; (5) integrate feature indexing mechanisms as access paths in database management systems; and (6) support ranked retrieval in database management systems. Based on the research, a prototype system, entitled Multimedia Analysis and Retrieval System (MARS), that seamlessly integrates multimedia data with structured information traditionally stored in databases is being designed. On the educational front, the existing database curriculum is being modified to incorporate evolving research and development in multimedia information systems. Also, the MARS prototype system is being made available as a teaching, education, and research tool to study human factors issues in supporting content-based retrieval. This research not only has the potential to impact the design of future multimedia information systems but will also prove beneficial to other areas including geographical information retrieval, planning and reasoning applications over database systems. http://www-mars.cs.uiuc.edu |
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2000 — 2004 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-Irvine With the advances in embedded processors, low cost sensor technologies, and wireless communication, unprecedented amounts of diverse types of information about the real world and its activities are being generated. Much of the information is spatio-temporal in nature; concerning objects dispersed in space and time, and interacting and communicating with each other and their surroundings. An infrastructure that facilitates real-time capture, storage, processing, display, and analysis of the information generated will truly revolutionize a wide variety of application domains. Examples of domains that will benefit from this technology include avionics, ground traffic, commercial applications such as ship-ping and transportation, emergency response and disaster relief operations, physical phenomenon such as weather and storm tracking, forest fire tracking, migration patterns of animals/birds, command and control, smart environments, etc. Applications in the above domains require real-time monitoring, tracking and analysis of objects/events/phenomena in space and time. |
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2001 — 2010 | Smyth, Padhraic [⬀] Mehrotra, Sharad |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Data Mining of Digital Behaviour @ University of California-Irvine The goal of this research project is to improve our understanding of how humans behave in information-seeking digital environments such as the Web. The approach consists of using massively large Web logs to infer patterns of behavior. New probabilistic models for modeling human behavior on the Web are under investigation including Markov and switching models, mixture models, and Bayesian hierarchical models. Adaptive statistical techniques form the basis for building up individual user models in an online fashion, automatically learning both the dynamic time-dependent patterns of a user as well as text-vector representations of their interests. Test data sets from large commercial Web sites are being used to develop, validate, and test the models. Data are anonymized to protect individual privacy. The statistical user models are in turn being used to develop two primary software tools. The first tool allows an analyst to explore, cluster, predict, and visualize Web logs with millions of entries, allowing an understanding of dynamic patterns of access and behavior in a manner that is not currently available in research or commercial tools. The second tool, WebMARS, uses adaptive user-models to enhance information retrieval algorithms by interpreting search queries in a personalized manner. More generally, the results from this project will provide tools and techniques to enable a better scientific understanding of modes of human behavior across a broad range of digital environments, with potential applications in wireless information appliances, medical informatics, scientific exploration of massive data sets, and so forth. |
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2002 — 2007 | Veidenbaum, Alexander (co-PI) [⬀] Mehrotra, Sharad Tsudik, Gene (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Itr: Privacy in Database-as-a-Service (Das) Model @ University of California-Irvine Rapid advances in networking and Internet technologies has fueled the emergence of the "software as a service" model for enterprise computing that enables organizations to outsource many Information Technology (IT) services. This model allows organizations to concentrate on their core business instead of sustaining large investments in IT. IT outsourcing results in savings from the economies of scale due to leveraging of hardware, software, personnel, as well as maintenance and upgrade costs. Outsourcing is a common practice in Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) domains and it is gaining popularity in basic services such as email, storage and disaster protection. |
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2003 — 2010 | Butts, Carter (co-PI) [⬀] Eguchi, Ronald Mehrotra, Sharad Venkatasubramanian, Nalini (co-PI) [⬀] Winslett, Marianne (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Information Technology Research (Itr): Responding to the Unexpected @ University of California-Irvine The long-term goals of this project are to radically transform the ability of organizations that respond to man-made and natural disasters to gather, process, manage, use and disseminate information both within the emergency response agencies and to the general public. The project explores a multidisciplinary approach consisting of two interrelated research thrusts: |
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2004 — 2010 | Rao, Ramesh (co-PI) [⬀] El Zarki, Magda Mehrotra, Sharad Venkatasubramanian, Nalini (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
An It Infrastructure For Responding to the Unexpected @ University of California-Irvine Broader Impact: Timely and effective response to natural or man-made disasters can reduce deaths and injuries, contain or prevent secondary disasters, and reduce the resulting economic losses and social disruption. During a crisis, responding organizations confront grave uncertainties in making critical decisions. There is a strong correlation between the quality of these decisions and the accuracy, timeliness, and reliability of the situational information (e.g., state of the civil, transportation and information infrastructures) and the availability of resources (e.g., medical facilities, rescue and law enforcement units) to the decision-makers. Recently, at UCI and UCSD many projects have been launched that address the technological challenges in with the objective of radically transforming the ability of organizations to gather, manage, use and disseminate information when responding to man-made and natural catastrophes. Dramatic improvements in the speed and accuracy at which information about the crisis flows through the disaster response networks has the potential to revolutionize crisis response saving human lives and property. . The purpose of this infrastructure proposal is to establish an campus-level experimental Information Technology infrastructure, called Responsphere, to serve as a platform for development, testing, and validation of our current research efforts on responding to a crisis. |
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2008 — 2010 | Mehrotra, Sharad Venkatasubramanian, Nalini (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Ri-Small: Collaborative Research: Dispatcher's Assistant For Emergency First Response @ University of California-Irvine In crisis response domains, emotional manifestations are very complex and extreme emotions are common. While speech technologies have shown significant progress over the years, recognizing and understanding emotional speech in noisy environments is still a big challenge. Understanding such language is daunting given fragmented and ungrammatical utterances in addition to errors |
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2010 — 2015 | Dutt, Nikil (co-PI) [⬀] Mehrotra, Sharad Venkatasubramanian, Nalini [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Cps: Medium: Collaborative Research: Dependability Techniques For Instrumented Cyber-Physical Spaces @ University of California-Irvine The goal of this project is to develop a semantic foundation, cross-layer system architecture and adaptation services to improve dependability in instrumented cyberphysical spaces (ICPS) based on the principles of "computation reflection". ICPSs integrate a variety of sensing devices to create a digital representation of the evolving physical world and its processes for use by applications such as critical infrastructure monitoring, surveillance and incident-site emergency response. This requires the underlying systems to be dependable despite disruptions caused by failures in sensing, communications, and computation. The digital state representation guides a range of adaptations at different layers of the ICPS (i.e. networking, sensing, applications, cross-layer) to achieve end-to-end dependability at both the infrastructure and information levels. Examples of techniques explored include mechanisms for reliable information delivery over multi-networks, quality aware data collection, semantic sensing and reconfiguration using overlapping capabilities of heterogeneous sensors. Such adaptations are driven by a formal-methods based runtime analysis of system components, resource availability and application dependability needs. Responsphere, a real-world ICPS infrastructure on the University of California at Irvine campus, will serve as a testbed for development and validation of the overall ?reflective? approach and the cross-layer adaptation techniques to achieve dependability. Students at different levels (graduate, undergraduate, K-12) will be given opportunities to gain experience with using and designing real-world applications in the Responsphere ICPS via courses, independent study projects and demonstration sessions. Students will benefit tremendously from exposure to new software development paradigms for the ICPSs that will be a part of the future living environments. |
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2010 — 2011 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Eager-Tc: Limiting Effect of Ram-Scraping Attacks in Dbmss @ University of California-Irvine This proposal explores effective solutions to RAM scraping attacks in |
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2011 — 2015 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Tc: Small: Risk Aware Query Processing in Mixed Security Database Environments @ University of California-Irvine During database query processing, data migrates across different system components each of which may offer different levels of security guarantees and may be susceptible to different attacks. If the underlying data (or part of it) is sensitive, data migration, especially from secure components to those that are relatively insecure could increase risk of data loss. This proposal takes a "risk-based" approach to security wherein instead of designing approaches to prevent attacks, the proposed research controls flow of data during query processing through various components in such a way to strike a balance between risk of exposure and system performance. Risk-aware query processing techniques is explored in two settings: (a) A stand-alone database server where data on disks is stored encrypted (and is hence secure) but is loaded in plaintext into memory during query processing. (b) Cloud computing environment where, during peak load queries (and corresponding data) are shipped from (relatively secure) private storage to be processed at (relatively insecure) public cloud infrastructure, a phenomena known as cloudbursting. In both these settings, techniques to co-optimize query execution to simultaneously minimize both disclosure risks as well as performance costs are explored. The research offers a complementary approach to traditional techniques based on preventing attacks to support practical security in the context of database systems. |
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2011 — 2015 | Carey, Michael Jain, Ramesh (co-PI) [⬀] Mehrotra, Sharad Venkatasubramanian, Nalini (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-Irvine Dr. Sharad Mehrotra and an interdisciplinary team of collaborators at the University of California at Irvine (UCI) will develop I-sensorium, to serve as a "living laboratory" to support research in several related areas of cyber-physical systems: including theoretical foundations and underlying principles of building sentient systems; engineering, software, and systems level challenges; and novel application contexts where such sentient systems can be used. I-Sensorium will serve as a testbed for exploring and testing novel sentient technologies. I-Sensorium augments Responsphere, an existing UCI crisis response test-bed with state-of-the-art storage and computational infrastructure to acquire and process continuous streams of sensory data from Responsphere sensors. The I-Sensorium software will leverage multiple ongoing research projects at UCI on large-scale, heterogeneous sensor databases, sensor middleware platforms for querying and analysis of heterogeneous sensor data, and an event representation system for multi-media data, to provide a high level programming environment for the I-Sensorium allowing a broad group of researchers to participate and benefit from its creation. |
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2011 — 2015 | Mehrotra, Sharad Kalashnikov, Dmitri |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Iii: Small: Query and Goal Driven Entity Resolution Framework @ University of California-Irvine Data cleaning technologies, traditionally designed to improve quality of data in back-end data warehouses, are fast emerging as a vital component of real-time information access. As the Web evolves towards supporting interactive analytics and basic search migrates from simple keyword retrieval to retrieval based on semantically richer concepts (e.g., entities) extracted from web pages, the need for "on-the-fly" cleaning techniques that can help alleviate data quality challenges is rapidly increasing. This project explores three new innovations that will help advance data cleaning towards becoming an embedded enabling technology for real-time information access. The first innovation is "query-aware data cleaning" which is based on the observation that the specificity of the real-time task such as a query can be exploited significantly to bring new optimizations to the data cleaning process. The second innovation is a data cleaning framework that migrates from the "best-effort" adhoc setup of today's systems into a principled approach that exposes and exploits a fundamental tradeoff between the cost of cleaning and quality of results achieved. Finally, since results of cleaning need to be fed to the end-user or analysis code, the proposal postulates and addresses approaches towards how results processed through data cleaning code can be presented to the end-recipient. The primary contribution is mechanisms to hide the uncertainty in the data and determinize the results while maximizing the end application goals. |
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2012 — 2015 | Mehrotra, Sharad Tsudik, Gene (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-Irvine Pervasive computing, such as sensors in smartphones, buildings, automobiles and cities, result in increased sharing of sensor data, whether initiated by users or by other authorities such as service providers, government entities, interest groups, and individuals. Embedded in this data is information which others, even using sophisticated data mining algorithms, can fuse to construct a virtual biography of our activities, revealing private behaviors and lifestyle patterns. Researchers in this project are devising computational methods to let users exercise privacy control over their personal sensory data that is shared. |
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2014 — 2017 | Mehrotra, Sharad Venkatasubramanian, Nalini [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Eager: Scale 2 (Safe Community Awareness and Alerting) - Extending a Smartamerica Challenge Project @ University of California-Irvine SCALE2 explores the design of resilient, inexpensive cyber-physical systems (CPS) technologies to create community-wide smartspaces for public/personal safety. SCALE2 aims to demonstrate that community safety can be realized by augmenting CPS technologies with end-to-end resilience mechanisms. Such a study requires real-world community-scale deployments to understand citizen concerns and can only be achieved through partnerships between various stakeholders - researchers, government agencies, and industry. |
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2015 — 2018 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Iii: Small: Linking and Resolving Entities in Big Data @ University of California-Irvine This project will explore the challenge of cleaning data in the context of analysis pipelines over big data. Data cleaning has traditionally been designed to improve data quality in ETL systems where enterprise data is collected, prepared, staged, transformed, and loaded into a data warehouse to support offline data analysis. In the era of big data, such back-end processes are quickly giving way to interactive exploratory data analysis where analysts immerse themselves in data (possibly collected from heterogeneous data sources) in order to drive online (near-) real-time decision making. Existing systems do not scale to the volume, velocity, or the variability of the dynamically generated data (e.g., social media streams) and the offline architecture is unsuited for the online real-time nature of analysis. The market is abuzz with innovations in data transformation technologies, e.g., TriFacta allows analysts to visually manipulate data to generate complex analytical transformations and Data Tamer is exploring scalable data curation from diverse sources. Data quality (and hence data cleaning technologies) remain at the core of big-data analytics. Many popular media (as well as academic) articles have highlighted challenges such as entity linking and resolution as among the most important and immediate roadblocks for big data analytics. The key insight on which this project is based is that data cleaning to support analytics over big data is not simply a matter of scaling up known approaches to larger data sets by exploiting more hardware. While scale up is important, big data analytics in streaming, real-time, and interactive settings requires a paradigm shift in how data cleaning is performed. This project will significantly impact and change the modern practices of data cleaning and the way cleaning is integrated in the Big Data analysis pipeline and will explore broader impact through: (a) technology transfer opportunities with a relevant industrial partner whose existing products could benefit from the proposed research; and (b) open source effort in the context of the ongoing social media analytics system (SoDAS), currently under development, in which the proposed research algorithms will be integrated. |
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2015 — 2017 | Mehrotra, Sharad Venkatasubramanian, Nalini [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Eager: Exploring Resilience in Smartcity Water Infrastructure @ University of California-Irvine Water is a critical resource and a lifeline service to communities worldwide; the generation, treatment, distribution and maintenance of water workflows is typically managed by local governments and water districts. Recent events such as water supply disruptions caused by Hurricane Sandy in 2012 and the looming California drought crisis clearly indicate society's dependence on critical lifeline services such as water and the far-reaching impacts that its disruption can cause. Over the years, these critical infrastructures have become more complex and often more vulnerable to failures. The ability to view water workflows as a community wide cyber-physical system (CPS) with multiple levels of observation/control and diverse players (suppliers, distributors, consumers) presents new possibilities. Designing robust water systems involves a clear understanding of the structure, components and operation of this CPS system and how community infrastructure dynamics (e.g. varying demands, small/large disruptions) impact lifeline service availabilities and how service level decisions impact infrastructure control. |
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2015 — 2018 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-Irvine he goal of this project is to facilitate timely retrieval of dynamic situational awareness information from field-deployed nodes by an operational center in resource-constrained uncertain environments, such as those encountered in disaster recovery or search and rescue missions. This is an important cyber physical system problem with perspectives drawn at a system and platform level, as well as at the system of systems level. Technology advances allow the deployment of field nodes capable of returning rich content (e.g., video/images) that can significantly aid rescue and recovery. However, development of techniques for acquisition, processing and extraction of the content that is relevant to the operation under resource constraints poses significant interdisciplinary challenges, which this project will address. The focus of the project will be on the fundamental science behind these tasks, facilitated by validation via both in house experimentation, and field tests orchestrated based on input from domain experts. |
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2020 — 2023 | Mehrotra, Sharad Venkatasubramanian, Nalini (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Iii: Small: Enrichdb - Supporting Enrichment in Database Systems @ University of California-Irvine Emerging application domains such as sensor-driven smart spaces and social media platforms require incoming data to be appropriately enriched prior to being consumed by data analysts. Enrichment often requires the use of complex compiled code, declarative queries, and/or expensive machine learning/signal processing modules. Traditionally, enrichment is performed as an offline process prior to making the data available for analysis. The recent trend towards real-time analytics has prompted industrial and research systems to explore enrichment during online data processing. These efforts have focused on optimizing enrichment at the time of data ingestion. This project will develop a new type of data management technology, to support real-time data analytics, entitled EnrichDB, that represents a significant departure from the above ingestion-based enrichment approaches. EnrichDB is based on the premise that enriching data in its entirety at ingestion can be (a) wasteful -- since applications may not require all data to be enriched; (b) result in unacceptable latencies -- if data arrival rates are high, or (c) not be feasible -- if enrichment functions are learned and incorporated into the system at a later time after ingestion. EnrichDB will explore seamlessly integrating data enrichment through the entire data processing pipeline - from ingestion to event-based intermittent enrichment, and progressively during query processing. EnrichDB will benefit real-time data analytics in multiple domains including IoT-enabled smart spaces, text and social media analytics, cybersecurity, network surveillance, etc. |
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2020 — 2021 | Mehrotra, Sharad Venkatasubramanian, Nalini (co-PI) [⬀] Khargonekar, Pramod |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Rapid: An Organizational Scale Approach to Privacy-Enabled Contact Tracing in Covid-19 @ University of California-Irvine Contact tracing has emerged as a key mitigation strategy to prevent the spread of pandemics such as COVID-19. Recently, several efforts have been initiated to track individuals, their movements, and interactions using technologies such as Bluetooth beacons, cellular data records, and smartphone applications. Such solutions can be intrusive, potentially violate individual privacy rights and are often subject to regulations that mandate the need for opt-in policies to gather and use personal information which, as several studies have shown, limits their adoption. This project takes a novel approach to empower organizations to mitigate spread of COVID-19 at their premises by exploiting connection events between mobile devices carried by individuals and the Wi-Fi infrastructure. There are several advantages of the planned approach. First, it takes an organizational perspective and is intended to help organizations, small and large, keep employees safe and ensure safety on their premises by exploiting network data (already being generated by their network infrastructures). Second, it is decentralized, i.e., instead of empowering/trusting a small number of organizations such as mobile OS companies, it empowers organizations to assume joint responsibility to implement safety measures at their premises. Third, it offers a fully privacy-preserving solution based on computationally and informationally secure cryptography with strong security properties guaranteeing privacy of individuals, including those who might be exposed or carriers. This will prevent misuse of the data collected by any entity against the will of the individuals. Fourth, it is based on connectivity events already generated by existing Wi-Fi infrastructure and does not require users of the network to either download any application and/or give explicit permissions (which is known to limit adoption). Finally, it offers a path to implement technology not just for contact tracing but empowers organizations with awareness about effectiveness of their policies/strategies such as social distancing, disinfecting/cleaning schedules, etc. |
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2020 — 2021 | Mehrotra, Sharad Li, Chen Carey, Michael |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Student Support For the 46th International Conference On Very Large Databases (Vldb 2020) @ University of California-Irvine The provided support will enable about 15 US-based students to attend and participate in the 46th International Conference on Very Large Databases (VLDB 2020)to be held in Tokyo Aug. 31st to Sept. 4th, 2020 (https://vldb2020.org/). The VLDB conferences are a premier international technical event centered on various aspects of database research and practice. The VLDB conference provides a forum that promotes students and researchers to identify scientific foundations for building large-scale database management systems that can work ever more effectively. Efforts will be made to broaden the participation of underrepresented students and researchers. The conference will thus contribute directly to training the next generation of scientists who are both consumers and developers of technology in database management system design and implementation. The involvement of US-based students will have a direct impact in creating a highly-qualified workforce who can take on the emerging data science challenges of the future. |
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2021 — 2022 | Mehrotra, Sharad Venkatasubramanian, Nalini [⬀] Levorato, Marco Gago Masague, Sergio |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Iucrc: Uci: Planning Grant: Proposal Planning Grant: Center For Smart Space Research (Cssr) @ University of California-Irvine Smart spaces are characterized by the presence of smart services built on emerging sensing, computing, and communication technologies. This planning grant will create a multi-university Center for Smart Space Research (CSSR) involving Rochester Institute of Technology (RIT) and the University of California, Irvine (UCI). CSSR takes an integrated approach to make them versatile and adaptable to situations by ensuring the availability and accessibility of data, knowledge, and services. This planning grant will identify research challenges to build application-focused smart spaces. Applications encompass health and disease monitoring systems, smart buildings, public spaces and cities, mission-critical systems, transportation, intelligent manufacturing, collaborative robotics, and others. |
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2021 — 2022 | Dutt, Nikil (co-PI) [⬀] Gibbs, Lisa Mehrotra, Sharad Rousseau, Julie Venkatasubramanian, Nalini [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-Irvine Disasters disproportionately impact older adults who experience increased fatality rates; such individuals often live in age-friendly communities and senior health facilities (SHFs). During a crisis, older adults are often unable to shelter safely in place or self-evacuate due to a range of physical conditions (need for life-sustaining equipment, impaired mobility) and cognitive afflictions (e.g. dementia, Alzheimer’s). First responders assisting older adults could benefit from seamless, real-time access to critical life-saving information about the living facilities (e.g., floor plans, operational status, number of residents) and about individual residents (e.g., health conditions such as need for dialysis, oxygen, personal objects to reduce anxiety). Such information, siloed within organizational logs or held by caregivers, is inaccessible and/or unavailable at the time of response. This interdisciplinary project brings together IT, geriatrics and resilience experts with disaster-response agencies and SHF providers to create information preparedness and transform disaster resilience for older adults. |
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2022 — 2023 | Mehrotra, Sharad | N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of California-Irvine The provided support will enable United States-based students to attend and participate in the 48th International Conference on Very Large Databases (VLDB 2022) to be held in Sydney, Australia from September 5, 2022 to September 9, 2022 (https://vldb.org/2022). The VLDB conferences are a premier international technical event centered on various aspects of database research and practice. The VLDB conference provides a forum that promotes students and researchers to identify scientific foundations for building large-scale database management systems that can work ever more effectively. Efforts will be made to broaden the participation of underrepresented students and researchers. The conference will thus contribute directly to training the next generation of scientists who are both consumers and developers of technology in database management system design and implementation. The involvement of United States-based students will have a direct impact in creating a highly-qualified workforce who can take on the emerging data science challenges of the future.<br/><br/>Database research profoundly influences domains that include health sciences, the emerging field of Internet of Things (IoT), service-oriented computing, real-time business analytics, and social computing. The VLDB conference series provides researchers and practitioners from academia, industry and government agencies with an excellent opportunity to share their research and experiences on all aspects of data management and analysis at scale. The aims of the conference are multi-fold: (1) to provide an international forum for sharing research results related to the investigation of major challenges in next-generation database research; (2) to stimulate interactive discussions on research in the database area through panels, posters, tutorials, student scholar roundtables, etc.; and (3) to motivate and engage future generations of researchers via the many conference and workshop presentations, interactive poster sessions, and panel and breakout sessions. The VLDB 2020 Proceedings will be broadly accessible at http://www.vldb.org/pvldb/.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. |
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