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
Introduction of Design and Organization of Computing Systems. This course introduces fundamental concepts of computing systems, such as circuit design, boolean equations, binary arithmetic and data representation, the operation of memory, as well as design of a processor. This course also covers the use of VHDL in designing circuits. The course has design, implementation, and analytical components.
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.
Project-based course on advanced data visualization techniques. Topics may include: scalable visualization methods, multidimensional data analysis, network visualization, geospatial visualization, and interactive visualization. Ethical issues in data science.
Project-based course on advanced data visualization techniques. Topics may include: scalable visualization methods, multidimensional data analysis, network visualization, geospatial visualization, and interactive visualization. Ethical issues in data science.
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.
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.
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.
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.
Teaching
Online and Continuing Education Courses
Introduction of Design and Organization of Computing Systems. This course introduces fundamental concepts of computing systems, such as circuit design, boolean equations, binary arithmetic and data representation, the operation of memory, as well as design of a processor. This course also covers the use of VHDL in designing circuits. The course has design, implementation, and analytical components.
Project-based course on advanced data visualization techniques. Topics may include: scalable visualization methods, multidimensional data analysis, network visualization, geospatial visualization, and interactive visualization. Ethical issues in data science.
Register for this course.
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.