Manal Helal , Ph.D.
Dr. Manal Helal is researching the applications of technology to solve real life problems. Her interests is in the parallelisation of sequential algorithms to various high performance computing architectures, artificial intelligence, data fusion, high dimensional/tensor data representation and analysis, signal processing, and Geographic Information Sciences. The applications Dr. Manal is working on include: computational biology, traffic and network analysis, knowledge representation and discovery in various domains including medical and legal.
Dr. Manal received her B.Sc. and M.Sc. degrees from computer science and engineering department, school of sciences and engineering, the American University in Cairo (AUC), in 1995 and 2001 respectively. She received her Ph.D. degree from the computer science and engineering department, faculty of engineering, The University of New South Wales (UNSW), Sydney, Australia, in 2010. Manal joined University of Sydney as a research fellow in the centre of infectious diseases and microbiology, faculty of medicine in April 2008 to January 2011, in which she applied her Ph.D. and post-doc experimentation in high performance computing for computational biology problems, and clustering and classification of DNA sequences. Manal has an industrial experience of almost 12 years applying ERP, financial analysis, data warehousing and business intelligence using various technologies and tools.
Currently, she is an assistant professor in the college of engineering and technology, the Arab Academy for Science, Technology, and Maritime Transport. She is teaching parallel algorithms, graph theory, programming, computer graphics, computational theory, and computer algorithms, and pattern recognition courses.
List of Publications
Abdel Azeem, B., Helal, M.,,
"Performance Evaluation of Checkpoint/Restart Techniques for MPI Applications on Amazon Cloud,"
In Proceedings of the 9th INFOS 2014 International Conference on Informatics and Systems, Cairo, Egypt, 15-17, December 2014 , 2014.
Helal, M.E., Kong, F., Chen, S.C.A., Zhou, F., Dwyer, D.E., Potter, J., Sintchenko, V.,
"Linear normalised hash function for clustering gene sequences and identifying reference sequences from multiple sequence alignments"
Microbial Informatics and Experimentation, 2(2), , 2012.
Helal, M.E., Kong, F., Chen, S.C.A., Bain, M., Christen,R., Sintchenko, V.,
"Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data"
PLoS ONE, 6(6), , 2011.
Helal, M, Sintchenko, V.,
"Dynamic programming algorithms for discovery of antibiotic resistance in microbial genomes."
Electronic Journal of Health Informatics 2011 6(1):e10. ISSN: 1446-4381. , 2011.
"Indexing and Partitioning Schemes For Distributed Tensor Computing With Application To Multiple Sequence Alignment"
in fulfilment of the degree of Doctor of Philosophy, University of New South Wales, Computer Science and Engineering School, Faculty of Engineering, August 2009. , 2009.
Brett Bader Zhaojun Bai Gregory Beylkin Lieven DeLathauwer Inderjit Dhillon Chris Ding
Lars Eld ́en
Petros Drineas Christos Faloutsos Shmuel Friedland
Robert J. Harrison Manal Helal Anthony Kennedy Dongmin Kim Tamara Kolda Julien Langou Lek-Heng Lim Michael Mahoney Carla Martin Martin Mohlenkamp Jason Morton Lenore Mullin
Frank Olken Larsson Omberg Haesun Park Robert Plemmons Stefan Ragnarsson Sri Priya Ponnapalli J. Ram Ramanujam James Raynolds Phillip Regalia
P. Saday Sadayappan Berkant Savas Charles Van Loan,
"Future Directions in Tensor-Based Computation and Modeling"
Prepared by Charles Van Loan (Workshop Organizer) with editorial assistance from Sri Priya Pon- napalli and Stefan Ragnarsson (Workshop Scribes) and financial assistance from Lenore Mullin and Frank Olken (NSF Program Managers). Award number 0908059. The Workshop was held in Arling- ton, Virginia at the National Science Foundation, February 20-21, 2009. , 2009.
Helal, M., Mullin, L., Potter, J., Sintchenko, V.,
"Search Space Reduction Technique for Distributed Multiple Sequence Alignment."
In Proceedings of the 6th IFIP International Conference on Network and Parallel Computing (NPC 2009). Gold Coast, Queensland, Australia, , 2009.
Helal, M., Sintchenko, V.,
"Dynamic programming algorithms for discovery of antibiotic resistance in microbial genomes"
In Proceedings of the Health Informatics Conference (HIC-09). Canberra, Australia , 2009.
Helal M., El-Gindy, H., Gaeta, G., Sintchenko, V.,
"High Performance Multiple Sequence Alignment Algorithms for Comparison of Microbial Genomes."
In Proceedings of the 19th International Conference on Genome Informatics – GIW 2008. – Gold Coast, 2008. , 2008.
Helal, M., El-Gindy, H., Mullin, L., Gaeta, B.,
"Parallelizing Optimal Multiple Sequence Alignment by Dynamic Programming."
In Proceedings of the International Symposium on Advances in Parallel and Distributed Computing Techniques (APDCT-08) held in conjunction with 2008 IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA-08). Sydney, Australia, pp. 669-674. ISBN: 978-0-7695-3471- 8. , 2008.
Helal, M., Mullin, L.M., Gaeta, B., El-Gindy, H.,
"Multiple sequence alignment using massively parallel mathematics of arrays."
In Proceedings of the International Conference on High Performance Computing, Networking and Communication Systems (HPCNCS- 07), Orlando, FL. USA, 2007. pp. 120-7. , 2007.
Helal, M., Mullin, L., El-Gindy, H., Gaeta, B.,
"Optimal Parallel Solution for Multiple Sequence Alignment Using Mathematics of Arrays."
Poster presentation presented at Bioinformatics Australia 2006 “Connecting Australian Bioinformatics” 21-22 November 2006, Sydney Convention and Exhibition Centre, Darling Harbour, Sydney, NSW , 2006.
Helal, M., Mullin, L., Gaeta, B., El-Gindy, H.,
"Multiple Sequence Alignment Using Massively Parallel Mathematics of Arrays."
Poster presentation presented at BioInfoSummer 2005 – ICE-EM Summer Symposium in Bioinformatics, The Australian National University, Canberra, Australia , 2005.
Sameh, M. A., Helal, M.E.,,
"Dimension and Shape Invariant Array Programming: The Implementation and the Application"
Recent Advances in Simulation, Computational Methods, and Soft Computing, Electrical and Computer Engineering Series, Editor: Nokos Mastorakis, WSEAS Press , 2002.
"Dimension and Shape Invariant Programming – The Implementation and the Application"
In partial fulfilment of the degree of Masters of Science, American University in Cairo, Computer Science Department, School of Science and Engineering, January 2001. , 2001.
- CS243: Object Oriented Programming
CS244: Advanced Programming Applications
SE491: Software Component Design (Design Patterns)
IS477: Geographic Information Systems
CS452/CC416: Computer Graphics
CS311: Computational Theory
CS312: Computer Algorithms
CC111: Introduction to Computers
CC213: Programming Applications
CC410: System Programming
CC114: Introduction To Programming
CS710: Parallel Programming
CS712: Graph Theory
CC716: Pattern Recognition
Graduation Projects Supervision
1. Big data processing using Apache Mahout and Hadoop.
2. Automated class attendance using face recognition with opencv over MS Kinect device.
3. GIS crime mapping tool.
4. Web Crawling Internet contents to answer queries, using keyword mapping to particular topics, image processing, NLP,
5. Green Energy GIS decision support System, for demand/supply analysis, siting optimisation, environmental impact analysis, future prediction, and simulation tools (time permits all will be attempted, and can be completed and extended in future projects).
6. Building an interoperable cloud storage that spans the free services from the various providers: box, Google drive, Amazon drive, MS sky drive, Ubuntu one, … etc. Future ideas can extend to provide more apps for the various devices (IOS, Android, windows, mac, linux) to access the virtual drive as one. Future ideas can provide automatic backup and restore, replication for fault tolerance,
The following ideas are general descriptions for classes of applications that can be addressed using different technologies, and with varying scope.
A) Cloud Computing for Web-services & Parallel Processing
Consider any web services project of choice and running it on any available cloud such as the AWS EC2, and compare performance and cost with other stand alone networked clusters of servers. This can be a web application hosted on normal web servers, and/or any parallel program comparing the performance on multi-core hardware, clusters of networked computers, and the EC2.
Measuring Webhosting, file-sharing, database availability, performance and cost on the different architectures.
Parallel processing performance and cost comparison on the different architectures.
Writing comparison report about positives and negatives of the different architectures, and suitability for the different applications.
B) GPU vs CPU performance evaluation
Develop an image video processing application like feature extraction, pattern recognition, any graphics text book problem and implement it using CUDA toolkit on a GPU, and report the normal CPU performance compared to the GPU.
Learn CUDA GPU development toolkit.
Compare GPU vs CPU performance
Compare GPU vs other parallel architectures, like multi-core, clusters of computers, any accessible High Performance Computers.
C) High Dimensional Data Analysis
Experimenting with any high dimensional dataset such as those from UCI (University of California, Irvine) datasets from the machine learning repository by the Centre for Machine Learning and Intelligent Systems, and apply various Multivariate Statistical methods from R matlab, compare and report results.
D) Understanding Crowed Serviced Web Contents
Use web crawlers to download data available in the internet public domain, and apply natural language processing and learning techniques to extract information of interest to specific general queries.
E) Automatic Traffic & Crowed Management
Build a traffic and crowds management system, using information collected from cell phone access points, street cameras, radar cameras, satellite images, online location tagged posts on twitter, facebook, blogs, any accessible information source, to estimate the number of people in a given location at a given time, and the exits and entries routes to that location. Features like safe entries and exits need to be estimated, emergency situation detection and intervention methods, controlling crowds and leading them out of hazards scenarios.
F) Building Ontologies, specifically Legal ontologies
G) Estimating Colleges Admission GPA requirements (Tansik) based on the marks in each subject in high school for each specialisation and the society needs, using Numerical Methods.
H) Connecting Sensors to cell phones for continuous geo-tagged s to public databases. For example weather s using temperature and humidity sensors.
I) Building GIS Systems for various objectives, including but not limited to: house hunting, administrative data visualization, utilities management, market research, environmental monitoring
Previous & Ongoing Experiments:
1. My Distributed MSA: https://github.com/mhelal/mmDST
2. Clusters boundaries cut-offs using distance matrix gaps.
3. Programming Assignments Marking System: https://github.com/mhelal/marks
4. Curriculum Mapping System
5. Class Scheduling System
6. Web crawling Python script usage with the various social networking APIs
Address : AASTMT, Engineering & Technology College, Heliopolis, 308A
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