faculty
Amir Akhavan Masoumi, PhD
Assistant Teaching Professor
Computer & Information Science
Contact
508-910-6895
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Education
2015 | Computer Sciences, University of Science Malaysia | PhD |
2009 | Computer Sciences, University of Science Malaysia | MSc |
2004 | Civil Engineering, Urmia Azad University | BSc |
Teaching
- CIS 568/DSC 530: Data Visualization
- EGR 111: Intro Engineering & Computing
Teaching
Programs
Programs
Teaching
Courses
Software architectural patterns and techniques for building web applications. This course is intended to expose students to theories and principles of web-based user interface design, and a wide variety of client- and server-side technologies for developing web applications.
This course explores real-world scenarios introducing software debugging, quality testing, unit testing, Whitebox and Blackbox testing, code analysis techniques, and employing automation for various stages like integration, testing, deployment, and monitoring to optimize the workflow, reduce errors, and expedite delivery. Furthermore, it explores the Agile environment-based automated software testing (DevOps), containerization, and version controlling.
Prerequisites: Completion of three core courses. Development of a detailed, significant project in computer science under the close supervision of a faculty member, perhaps as one member of a student team. This project may be a software implementation, a design effort, or a theoretical or practical written analysis. Project report with optional oral presentation must be evaluated by three faculty members including the project supervisor.
Offered as needed to present advanced material to graduate students.
Offered as needed to present advanced material to graduate students.
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
A team-based learning experience that gives students the opportunity to synthesize prerequisite course material and to conduct real-world analytics projects using large data sets of diverse types and sources. Students work in independent teams to design, implement, and evaluate an appropriate data integration, analysis, and display system. Oral and written reports and ethical aspects are highlighted.
Research
Research activities
- Modeling the Dynamics of Infectious Diseases
- Climate Change and Extreme Events Patterns
- Cryptanalysis of Chaos-Baded Cryptography Systems
- Adverse Events Analytics using Clinical Data
Research
Research interests
- Complex Systems
- Cognitive Science
- Cryptography
- Chaos Theory
- Data Science
Select publications
See curriculum vitae for more publications
- Joseph Norman, Amir Akhavan, Chen Shen, David Aron, Luci Leykum, Yaneer Bar-Yam (2020).
Toward Prevention of Adverse Events Using Anticipatory Analytics
Progress in Preventive Medicine, 5, e0029. - Azam Majooni, Mona Masood, Amir Akhavan (2018).
An eye-tracking study on the effect of infographic structures on viewer’s comprehension and cognitive load
Information Visualization, 17, 257-266. - Amir Akhavan, Azman Samsudin, Afshin Akhshani (2017).
Cryptanalysis of an image encryption algorithm based on DNA encoding
Optics & Laser Technology, 95, 94-99.