Elinor Brondwine, Developer in Los Gatos, CA, United States
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Elinor Brondwine

Verified Expert  in Engineering

Lecturing Developer

Location
Los Gatos, CA, United States
Toptal Member Since
November 12, 2018

Elinor is a developer and researcher with a strong background in mathematics. Passionate about design and UX, she also utilizes her proficiency in Python, R, C++, and SQL to deliver world-class applications.

Python 3PandasSQLUnixC++NumPyPostgreSQLMicrosoft Visual StudioSciPyAWKRGitAnacondaPythonGensim

Availability

Part-time

Preferred Environment

Unix, Anaconda, Git

The most amazing...

...project I've coded included exploitation of user feedback via statistical models to improve search results. Check out the results in the research publication!

Work Experience

Research assistant

2014 - 2017
Technion - Israel Institute of Technology
  • Proposed, developed, implemented, and evaluated new models for utilizing user feedback to improve search results (proposed new models exploiting positive and negative feedback for the task of ad-hoc retrieval).
  • Implemented the models using Python (Pandas, Numpy) and C++ (expanded the Indri toolkit) in a Linux environment.
  • Evaluated and performed statistical analysis and visualization of the results (Trec Eval, Python, Numpy, and Matplotlib).
  • Generated visualization of the main results using Matplotlib.
  • Published and presented a short paper in ACM SIGIR 2016, leading conference in IR (in the top 4% of computer science conferences).
  • Collected data from users via online tools and created an additional dataset for evaluation.
Technologies: Matplotlib, Pandas, Python

Utilizing Focused Relevance Feedback

Presenting a novel study of ad hoc retrieval methods utilizing document-level relevance feedback and/or focused relevance feedback; namely, passages marked as (non-)relevant. The first method uses a novel mixture model that integrates relevant and non-relevant information at the language model level. The second method fuses retrieval scores produced by using relevant and non-relevant information separately. Empirical exploration attests to the merits of our methods and sheds light on the effectiveness of using and integrating relevance feedback for textual units of varying granularities.

Other

Information Retrieval, Lecturing

Languages

SQL, Python 3, Python, AWK, C++, R, HTML

Libraries/APIs

Matplotlib, Pandas, NumPy, SpaCy, SciPy

Tools

LaTeX, Sketch, Photoshop CS6, Adobe Illustrator, Git, Gensim, Microsoft Visual Studio

Platforms

Anaconda, Unix

Storage

PostgreSQL

2014 - 2017

Master's Degree in Information Management Engineering

Technion- Israel Institute of Technology, Israel - Israel

2010 - 2014

Bachelor of Science Degree in Industrial Engineering and Management

Technion- Israel Institute of Technology, Israel - Israel

2010 - 2014

Bachelor of Arts Degree in Economics and Management

Technion- Israel Institute of Technology, Israel - Israel

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