- Information Technology
Areas of Expertise
- Computer Science
- Data Mining and Analytics
- Machine learning (deep learning), image recognition and neural networks
- Big data analytics, predictive analysis and clustering
The Top Three Things I Would Like to Learn or Experience During my Mentorship
- Contribute to development and testing of new approaches for autonomous navigation and self-localization of mobile robots.
- Collaborate closely with roboticists, software engineers and external consultants from the industry.
- Manage data collection and develop efficient and accurate data annotation schemes for machine learning projects.
Ideal Company Type
My ideal host company conforms to my learning objectives and is an artificial intelligence-based company that has experience in building autonomous cars or robots. The company focuses on machine learning and big data analytics to build systems that achieve accurate and autonomous navigation with real-time warning system to avoid collision.
What impact will your mentorship have on your career and professional path?
Working in a leading company in machine learning field is a great opportunity to challenge myself and push boundaries to come up with original scientific contributions. I will utilize this hands-on experience to develop a solution for educating students with special needs and to build models that predict learning disabilities of students in an e-Learning environment, which will in turn help identify appropriate intervention methods.
What will be your most valuable contribution to your TechWomen host company?
I aspire to participate in solving open research problems in building autonomous-navigating systems. My passion for machine learning has led me to build a solid knowledge base of existing approaches that have achieved maximum possible accuracy in self-localization. I have also gained insights on existing challenges in this field and in my graduate studies I proposed a synergic anomaly detection method that achieved better accuracy compared with methods in the literature. I have experience analyzing data in different contexts, for example I worked on weather data to predict drought and I currently work on analyzing student data.
After participating in the TechWomen program, how will you leverage your mentorship experience to make an impact in your home country?
TechWomen will give me the opportunity to build new professional relationships which will be useful in structuring future research collaborations. I will use machine learning algorithms in e-learning platforms to track students' progress and consequently provide a measurable way to enhance the efficiency of the learning process. Machine learning will be used to provide a personalized educational experience. Analyzing students’ behaviors while they interact with e-learning platforms will help detect students’ specific areas of talents and direct them to the right profession. Finally, I aspire to increase awareness among students on the potential of computer science to improve our lives.
Years of Full-time Work Experience6
Primary Professional Focus
- QA and testing
Current/Most Recent Job
- Title and Company: Software Engineer, Ministry of Education
- Direct Reports: 10+
- Type: Full-time
- Location: Ramallah, Palestinian Territories
- Dates: August 4, 2010 –
Write, modify, integrate and test computer code for software applications and data processing applications; develop and implement policies and procedures throughout the software development life cycle to maximize efficiency; collect and document users' requirements to develop logical and physical software specifications; plan, design and coordinate the development, installation, integration and operation of computer-based systems including mobile applications; design, develop, implement and maintain databases, mainly SQL Server.
- Title and Company: Scientific researcher, The Scientific and Technological Research Council of Turkey
- Type: Part-time
- Location: Kayseri, Turkey
- Dates: December 1, 2013 – June 30, 2014
Carried out research and development of unsupervised learning algorithms to identify potentially useful patterns in diabetics data.
Highest Level of Education CompletedMaster's
- Institution: Erciyes University
- Degree Awarded: Master's
- Major: Computer Engineering
- Minor: Data Mining
- Location: Kayseri, Turkey
- Completion Date: February 1, 2015
- Institution: An-Najah University
- Degree Awarded: Bachelor's
- Major: Computer Science
- Location: Nablus, Palestinian Territories
- Completion Date: May 1, 2009