Jinane Harmouche

◦ Developing R&D Proposals: Two proposals for developing new technologies using AI got awarded by the Department of Energy.
◦ Leading R&D Machine Learning Projects: Developed end-to-end data analytic pipelines with prediction models involving data merging, conditioning and processing of raw drilling vibrations, measurements while drilling data and seismic data.
◦ Leading a Data Compression Project: Taking a principal investigator role on this project and implementing data compression algorithms for seismic and fiber optic data.
◦ Preparing Presentations & Reports: for clients and working closely with consultants.
◦ Serving as a Subject Matter Expert: on machine learning, data extraction and project management for the geophysicists and the engineers on my team.

<p>Developing R&D proposals for new technologies using AI.<br>
Two proposals were awarded by the Department of Energy.<br>
Leading R&D machine learning projects.<br>
Developed end-to-end data analytic pipelines with prediction models involving data merging, conditioning, and processing of raw drilling vibrations, measurements while drilling data, and seismic data.<br>
Leading a data compression project.<br>
Took a principal investigator role on the project and implemented data compression algorithms for seismic and fiber optic data.<br>
Preparing presentations and reports for clients.<br>
Worked closely with consultants.<br>
Serving as a subject matter expert on machine learning, data extraction, and project management for geophysicists and engineers on the team.</p>

<p>Done behavioral data acquisition and analysis to assess learning and memory in Alzheimer’s mice models.<br>
Conducted literature review on electrical brain stimulation for Alzheimer’s disease and the NIH stroke scale for its predictive and prognostic value.<br>
Mentored data science and neuro-engineering graduate students at Rice University.</p>

<p>Developed NLP pipelines for content matching and text similarity between legal contracts.<br>
Developed NLP pipelines for contracts clause classification.<br>
Developed NLP models for detecting legal decisions that have been overruled using datasets of overruled and overruling legal cases.<br>
Trained and fine-tuned deep learning models on large datasets using AWS machine learning and storage services.<br>
Worked closely with subject matter experts to define requirements, solicit feedback, and establish product enhancement cycles.<br>
Acquired a 3 months training and a certificate in reinforcement learning.</p>

<p>Developed association rules mining models for condition monitoring of water distribution pipelines using built-in sensors in smart fire hydrants.<br>
Developed unsupervised signal processing and statistical features extraction methods for monitoring large gearbox systems using vibration data.<br>
Applied the methods to the Terminal Link Train of Toronto Pearson Airport.<br>
Mentored civil engineering graduate students at the University of Waterloo.</p>

<p>Conducted exploratory data analysis and regression using disparate historical environmental time-series data.<br>
Evaluated data usefulness in the early prediction of sewer overflows using publicly available data for US states and counties.</p>

<p>Proposed improvements to the quality and reliability of information provided by hotel booking websites, particularly Tripadvisor.com, to facilitate users decision making.<br>
Developed a proof-of-concept workflow and pipeline.<br>
Added user selection fields for reviews’ time frame.<br>
Webscraped website data of Tripadvisor.com.<br>
Built NLP machine learning models.<br>
Visualized results of hotels’ ranking by sentiments and reviews’ changes overtime.</p>

<p>Developed a novel semi-supervised time-frequency analysis and signal decomposition technique for non-stationary time-series.<br>
Contributed to the development of a Matlab toolbox for time-series decomposition, the ASTRES Toolbox.</p>