8 Search Results

q=AI/Machine%20Learning/NLP

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Xiaoyu Chai , MS

Email: xchai@fredhutch.org

Phone: (206) 667-3004

Xiaoyu Chai's interests lie in the design of experiments such as A/B testing, factorial design, sampling, blocking, randomization, stratification, power and sample size calculation; statistical modeling such as generalized linear/non-linear/additive/penalized models, survival analysis, simulation, time series forecasting, clustering/segmentation, dimension reduction, hypothesis testing, feature selection; and machine learning such as bootstrap, cross-validation, Monte Carlo simulation, classification trees, bagging, random forests, boosting, support vector machines, neural networks, ensemble learning, parallel computing.

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Paul Edlefsen , PhD

Email: pedlefse@scharp.org

Phone: (206) 667-4086

Dr. Edlefsen's research interests include statistical and computational methods for bioinformatics applications. He is also interested in statistical modeling techniques for genome science analysis.

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Taran Gujral , PhD, Msc

Email: tgujral@fredhutch.org

Phone: (206) 667-4149

Cells respond to external stimuli by activating nonlinear and highly interconnected networks of signaling proteins. Dr. Gujral's work focuses on understanding how these networks are wired in different cell types and how they influence response to growth factors or cytotoxic agents using both hypothesis driven and systems-based data-driven approaches. His lab combines approaches from molecular genetics with cell and systems biology to study a recently discovered Wnt5-Fzd2 signaling pathway in metastasis as well as cell-to-cell contact in regulating cell fate decisions.

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Thomas Payne , MD

Email: tpayne@uw.edu

Dr. Payne’s major professional interest is the use and evaluation of clinical computing systems, especially electronic health records (EHRs) in patient care, clinical research, and quality improvement. Most of his work since completing his fellowship has involved development, selection, installation and operation of EHRs. His research interests include electronic documentation, natural language processing, and operating clinical computing programs.

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Thomas Richardson , MD, FACC

Email: thomasr@uw.edu

Phone: (206) 685-8488

Dr. Richardson's main area of research, graphical models, has developed at the interface between statistics and computer science, but has origins and applications in econometrics, epidemiology, genomics, psychology, and sociology. In other words, graphs (composed of vertices and edges) provide a language for formulating complex hypotheses.

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Emily Silgard , MS

Email: esilgard@fredhutch.org

Phone: (206) 667-4853

Emily Silgard's interests are in language processing for data extraction. She currently uses natural language processing to build a robust database for HIDRA based off of an extensive collection of clinical subjects. She is working closely with the different disease groups to interpret clinic and pathology reports to gather context, which informs and defines the pattern matching rules as well as knowledge based and statistical machine learning methods in her approach. Her future interests are to create a pipeline for computation and natural language processing.

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Dan Suciu , PhD

Email: suciu@cs.washington.edu

Phone: (206) 685-1934

Dr. Suciu is a full professor in Computer Science and Engineering at the University of Washington. He applies formal theory to novel and difficult data management tasks. Suciu's past work has addressed various aspects of managing semi-structured data, including query languages, compression, query processing and type inference. His more recent work includes data security and querying unreliable and inconsistent data sources.

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Fei Xia , PhD, MS

Email: fxia@u.washington.edu

Phone: (206) 543-9764

Dr. Xia's research area is computational linguistics. Her research covers a wide range of NLP tasks including morphological analysis, part-of-speech tagging, grammar extraction and grammar generation, treebank development, machine translation, named-entity recognition, and information extraction.

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