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Dr. Ghada Badr

Associate Professor

Faculty

علوم الحاسب والمعلومات
Office 99, Third Floor, Building 6
السيرة الذاتية

Dr Ghada Hany Mahmoud Badr

مختصر السيرة الذاتية
I completed my Ph.D. in 2006 in Computer Science at Carleton University, School of Computer Science, Ottawa, Canada. I was the winner of the university Senate Medal for outstanding research achievements and I was able to obtain one patent. From 2006 to 2007, I worked as a research associate at the National Research Council (NRC) of Canada for the language technology group in Gatineau, Canada, in the field of Machine Translation, where due to my contributions, my name was included in their patent application. In 2007, I won the prestigious NSERC Postdoctoral Fellowship in Canada. Since 2007 till 2011, I worked as a Postdoctoral fellow at the University of Ottawa, Ottawa, Canada, where my research focused in the field of Genome rearrangement and Data mining in Genome-scale Data for Bioinformatics with Dr. David Sankoff. I worked, and I am still working, on another research project with Dr. Marcel Turcotte (Joint Bioinformatics Program Associate Director (2010-12), and Vice-Dean for Undergraduate Studies since 2013), School of Electrical Engineering and Computer Science (EECS), University of Ottawa), in other bioinformatics aspects, where it involves discovering and localizing interacting RNA secondary structures for a Genome scale data. At KSU, I was able to establish the Bio-informatics Research group (BioInG), where I am coordinator for the group since Fall 2012 (http://bioinformaticksurg.blogspot.com). Through the group I was able to attract a lot of researchers from different departments and to develop a lot of research activities and workshops. My current projects focus on Data-mining for big data (Medical data and others). Taking into consideration that it was not easy for a woman in KSA society, I was able to develop a project and attract a fund to the university (more than one million Saudi Riyals) for 2 years. Using this fund, I supported a Phd student, 5 master students, and 5 undergraduates. I also organized the 1st Bioinformatics meeting workshop at KSU on May 4th, 2014, which was such a successful event that attracted invited speakers from different universities and research institutes in KSA and outside KSA. It also included a poster competition. In addition, I established a Bioinformatics lab that is equipped with HPC. These machines are currently serving students and researchers working in HPC projects. I started with only few who are familiar with the field and currently the group includes more than 40 members from diverse background and research interests. We also have research collaborations with research centers in KSA such as King Faisal Hospital and King Abdullah for Science and Technology. Through that collaboration, a lot of training opportunities are made available for both junior and senior researchers, who would like to start conducting their research in a Big Data project for Next Generation Sequencing Data. This is an avenue of research that I would like to continue with, where a lot of my computing background can be applied. I am also interested in applying data mining approaches in a lot of other applications.
نص السيرة الذاتية

Bioinformatics: Motifs (Localization and discovery, sequential and structural), Genome Scale (big data) sequence and structural analysis, RNA pairwise structure alignment, Genome Rearrangement, Sorting by Reversals, RNA-RNA secondary structure interaction, microarray gene expression, Next Generation Sequencing, Structural Variation, brain signal processing, Fourier Transformed Infra Red FTIR signal analysis for medical data, inference techniques for gene regulatory networks.

Machine learning and Machine Translation: Phrase-based statistical machine translation, decoding techniques, filtering techniques for models, learning techniques for optimizing weights in log-linear models. Quantitive rule-based classification models, feature selection (filter, wrapped and hybrid), regression models for learning entities weights for semantic data analysis.

Artificial Intelligence: Search techniques, Blind Search, Heuristic Search, Branch and Bound techniques, clustered beam search, Bio inspired algorithms, genetic-based algorithms.

Data Mining: classification, feature selection, frequent pattern mining, Hidden Markov Models, Bio inspired classification models, high dimensional data analysis, sequence alignment, structure alignment, text mining, Opinion Mining and Sentiment analysis, educational data mining, and social media analysis.

Pattern Recognition: Syntactic Pattern Recognition (PR), Approximate String Matching (ASM), Efficient Sequence Alignment techniques for dictionary-based models, Exact String Matching.

Advanced Data Structures: The design and analysis of many advanced data structures, Designing and implementing algorithms that use these advanced data-structures. Most data structures used or updated are used for storing strings and sequences. Design an efficient data structure for storing and retrieving Genome data. Self-adjusting data structures.

Information Retrieval: The design and analysis of information retrieval algorithms, Self-adjusting search techniques. Update these algorithms to be used efficiently for strings.

Database: Relational and Object Oriented Databases.