Rui Yan

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Rui Yan
About me

Rui Yan has graduated from RPI in May 2018 with his PhD degree in Computer Science. He is now working at Microsoft as a data scientist. For Rui Yan's latest profile, please visit his linkedin profile.

Publications

McCusker, J., Dumontier, M., Yan, R., He, S., Dordick, J., and McGuinness, D.L. 2017. Finding melanoma drugs through a probabilistic knowledge graph. PeerJ Computer Science

Yan, R., Greaves, M.T., Smith, W., and McGuinness, D.L. 2016. Remembering the Important Things: Semantic Importance in Stream Reasoning. In Proceedings of Stream Reasoning Workshop 2016 at International Semantic Web Conference (ISWC) 2016 (October 18 2016, Kobe, Japan).

Yan, R., Praggastis, B., Smith, W., and McGuinness, D.L. 2016. Towards A Cache-Enabled, Order-Aware, Ontology-Based Stream Reasoning Framework. In Proceedings of WWW 2016 (April 11-15 2016, Montreal, Canada).

Yan, R., Praggastis, B., Smith, W., and McGuinness, D.L. 2015. Towards Smart Cache Management for Ontology Based, History-Aware Stream Reasoning. In Proceedings of International Semantic Web Conference (ISWC) 2015 (October 11-15 2015, Bethlehem, PA, US).

Erickson, J.S., Chastain, K., Patton, E.W., Fry, Z., Yan, R., and McGuinness, D.L. 2014. Identifying First Responder Communities Using Social Network Analysis (POSTER ABSTRACT). In Proceedings of International Semantic Web Conference (ISWC) 2014 (October 19-23 2014, Riva del Garda, Trentino, Italy).

McCusker, J., Yan, R., Solanki, K., Erickson, J.S., Chang, C., Dumontier, M., Dordick, J., and McGuinness, D.L. 2014. A Nanopublication Framework for Biological Networks using Cytoscape.js. In Proceedings of International Conference on Biomedical Ontologies (ICBO 2014) (October 6-9 2014, Houston, TX).

Erickson, J.S., Chastain, K., McCusker, J., Fry, Z., Yan, R., and McGuinness, D.L. 2014. Technical Report: Identifying First Responder Communities through Social Network Analysis of Disaster-Related Traffic.

Erickson, J.S., McCusker, J., McGuinness, D.L., Fry, Z., Chastain, K., and Yan, R. 2013. Technical Report: Requirements Gathering through First Responder Social Network Analysis.

Project Collaborator

First Responders logoFirst Responders Requirements Metholodology (FirstResponders)
Principal Investigator: Deborah L. McGuinness
Co Investigator: John S. Erickson
Description: The purpose of this project is to design and prototype a requirements-gathering methodology driven by the first responders community. The methodology will include examining the current state of collecting and synthesizing responder requirements, assessing the effectiveness of that process, evaluating existing candidate platforms for use within this community, and producing a roadmap that can be used by NIST and others to achieve a solution enabling the responder community to more effectively dialogue with key stakeholders. A prototype implementation of the methodology will be developed using the roadmap and will be available for testing and evaluation and requirements gathering.
FUSE LogoForesight and Understanding from Scientific Exposition (FUSE)
Principal Investigator: Deborah L. McGuinness
Co Investigator: Jim Hendler
Description: Technical emergence refers to the process whereby innovative ideas, capabilities, applications, and even entirely new fields of study arise, are tested, mature, and, if conditions are favorable, demonstrate feasibility and impact. IARPA’s Foresight and Understanding from Scientific Exposition (FUSE) Program is sponsoring advanced research and development (R&D) to develop automated systems that aid in the systematic, continuous, and comprehensive assessment of technical emergence using information derived from the published scientific, technical, and patent literature.
Health Data Challenge (HealthData)
Principal Investigator: Jim Hendler and Deborah L. McGuinness
Co Investigator: Jamie McCusker
Description: An infrastructure for large-scale collaboration around aggregation, generation, and publication of health-related Linked Data.
Repurposing Drugs with Semantics (ReDrugS)
Principal Investigator: Deborah L. McGuinness and Jonathan Dordick
Description: We aim to find new effective treatments for disease using existing drugs. Our approach is to gather and integrate existing data using semantic technologies to help discover promising drug repurposing.
SDC LogoStreaming Data Characterization (SDC)
Co Investigator: Deborah L. McGuinness
Description: This project aims to leverage the novel notion of semantic importance to characterize the importance among the boundless streaming data, so as to provide better query results in terms of accuracy or recall, as well as improve the system response time.
TW LogoStreaming Hypothesis Reasoning (Shyre)
Principal Investigator: William Smith and Deborah L. McGuinness
Description: AIM will advance streaming reasoning techniques to overcome a limitation in contemporary inference that performs analysis only over data in a fixed cache or a moving window. This research will lead to methods that continuously shed light on proposed hypotheses as new knowledge arrives from streams of propositions, with a particular emphasis on the effect that removing the expectation of completeness has on the soundness and performance of symbolic deduction platforms.
TWC schema.org Project LogoTWC Schema.org Vocabulary Development (TWC_Schemas)
Principal Investigator: Jim Hendler
Description: schema.org provides a collection of schemas — html tags — that webmasters can use to markup their pages in ways recognized by major search providers. Search engines including Bing, Google, Yahoo! and Yandex rely on this markup to improve the display of search results, making it easier for people to find the right web pages. Since early 2012 researchers at TWC RPI have been working with government and research data providers to define vocabularies for expressing the structured data that powers their web sites, using on-page markup based on schema.org vocabularies. In particular, we developed the schema.org/Dataset extension, a concise vocabulary that extends schema.org for describing datasets and data catalogs. Current work includes applying Dataset to scientific datasets and developing new extensions for use by Web Observatories