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EXPLORE
0.9
0.9
100%
$10 USD / Hour
・
Egypt (6:43 AM)
・
Joined on September 4, 2008
$10 USD / Hour
・
My interests include data science, machine learning, bioinformatics and drug discovery. In recent years, I have gained a lot of experience in machine learning due to my PhD thesis. I am into data science nowadays and am comfortable working with Python, R, MATLAB, Java and SQL. I am also a good scientific writer. ~~~~~~~~~~~~~~~~ Skills: ▪ Programming: Python, R, MATLAB, Java, SQL, C/C++, Tableau, Keras, Hadoop ▪ Tools: Git, LaTeX, Linux, Awk, MS Office ▪ Competencies: machine learning, data mining, statistics, academic writing, software engineering, objected-oriented programming, web development, relational databases, shell scripting, data visualization, bioinformatics, drug discovery
Great work, nicely documented, completed on time, and included additional suggestions for improvement.
Harry I.
@softwarecodersvw
•
Brookline, United States
•
Share
Experience
Software Engineer
Oct, 2008 - May, 2011
•
2 years, 7 months
United OFOQ
Oct, 2008 - May, 2011
•
2 years, 7 months
Worked as a Java EE developer and was responsible for adding functionality to company products as well as fixing bugs reported internally or by the customer. In addition, other duties included customer support and on-site deployment of software. Projects: - Baggage Reconciliation System (BRS) - OFOQ Talent Management System (OTMS) Tools/Technologies used: - Java EE, JSP, JSF, JavaScript, EJB 3.0, JPA - IBM Websphere, Oracle Application Server, ActiveVOS, Glassfish, Liferay - IBM DB2, Oracle DB
Oct, 2008 - May, 2011
•
2 years, 7 months
Education
Nanyang Technological University
2013 - 2018
•
5 years
PhD in Computer Science
Singapore
2013 - 2018
•
5 years
Nanyang Technological University
2011 - 2012
•
1 year
MSc in Bioinformatics
Singapore
2011 - 2012
•
1 year
Ain Shams University
2002 - 2006
•
4 years
B.Sc. in Computer Science
Egypt
2002 - 2006
•
4 years
Qualifications
Machine Learning Foundations: A Case Study Approach
2015
Coursera
2015
Introduction to Big Data
2015
Coursera
Intro to using Hadoop and MapReduce.
2015
Publications
Computational Prediction of Drug-Target Interactions via Ensemble Learning
Springer Protocols (Methods in Molecular Biology)
Book chapter on prediction of drug-target interactions via ensemble learning. Link: https://link.springer.com/protocol/10.1007/978-1-4939-8955-3_14
Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization
IEEE/ACM Transactions on Computational Biology and Bioinformatics
Came up with a new method that improves prediction performance over preceding algorithms for drug-target interaction prediction. In this work, matrix factorization and manifold learning (graph regularization) were used. Link: https://doi.org/10.1109/TCBB.2016.2530062
Drug-target interaction prediction using ensemble learning and dimensionality reduction
EL-SEVIER (METHODS)
An improvised machine learning method was devised to deal with issues in the data being used to train the prediction model, namely the huge size of the data, the high dimensionality of the data and the severe class imbalance in the data. Link: https://doi.org/10.1016/j.ymeth.2017.05.016
Certifications
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Foundation vWorker Member
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100%
On budget
100%
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