About
18
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Introduction
My research currently focuses on knowledge graphs and the semantic web with an emphasis on data normalization as a means to solve complex information integration problems.
Concurrently, I am investigating methods to leverage machine and deep learning techniques to establish automatic information extraction tools for scientific modeling.
Publications
Publications (18)
Understanding customers demands and needs is one of the keys to success for large enterprises. Customers come to a large enterprise with a set of requirements and finding a mapping between the needs they are expressing and the scale of available products and services within the enterprise is a complex task. Formalizing the two sides of interaction...
Historical maps provide rich information for researchers in many areas, including the social and natural sciences. These maps contain detailed documentation of a wide variety of natural and human-made features and their changes over time, such as changes in transportation networks or the decline of wetlands or forest areas. Analyzing changes over t...
Capturing domain knowledge is a time-consuming procedure that usually requires the collaboration of a Subject Matter Expert (SME) and a modeling expert to encode the knowledge. This situation is further exacerbated in some domains and applications. The SME may find it challenging to articulate the domain knowledge as a procedure or a set of rules b...
Historical maps contain detailed geographic information difficult to find elsewhere covering long-periods of time (e.g., 125 years for the historical topographic maps in the US). However, these maps typically exist as scanned images without searchable metadata. Existing approaches making historical maps searchable rely on tedious manual work (inclu...
Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature–human systems (e.g., the dynamics of the wildland–urba...
We present Viola, an open-domain dialogue system for spoken conversation that uses a topic-agnostic dialogue manager based on a simple generate-and-rank approach. Leveraging recent advances of generative dialogue systems powered by large language models, Viola fetches a batch of response candidates from various neural dialogue models trained with d...
Major societal and environmental challenges involve complex systems that have diverse multi-scale interacting processes. Consider, for example, how droughts and water reserves affect crop production and how agriculture and industrial needs affect water quality and availability. Preventive measures, such as delaying planting dates and adopting new a...
Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urba...
Historical maps provide a rich source of information for researchers in the social and natural sciences. These maps contain detailed documentation of a wide variety of natural and human-made features and their changes over time, such as the changes in the transportation networks and the decline of wetlands. It can be labor-intensive for a scientist...
Historical maps provide a rich source of information for researchers in the social and natural sciences. These maps contain detailed documentation of a wide variety of natural and human-made features and their changes over time, such as the changes in the transportation networks and the decline of wetlands. It can be labor-intensive for a scientist...
Understanding the impacts of climate change on natural and human systems poses major challenges as it requires the integration of models and data across various disciplines, including hydrology, agriculture, ecosystem modeling, and econometrics. While tactical situations arising from an extreme weather event require rapid responses, integrating the...
Scientific models often depend on complex, interrelated datasets, and finding, preparing, and cleaning these datasets often dominates the time devoted to scientific inquiry. We are addressing these problems by creating a Data Catalog that provides a central clearinghouse for metadata about scientific datasets, supports fuzzy searching for data vari...
Data-intensive models have become critical to understanding the world. In order to reuse or combine datasets to support modeling, scientists must select, understand, and align them manually, a laborious process that requires understanding different domains and formats. To assist the modeling process, we present an unsupervised approach that identif...