Jansen Orfan
Lecturer
Department of Computer Science
Golisano College of Computing and Information Sciences
585-475-2834
Office Location
Jansen Orfan
Lecturer
Department of Computer Science
Golisano College of Computing and Information Sciences
Education
BS in Computer Science, Monmouth University; MS in Computer Science, University of Rochester
585-475-2834
Areas of Expertise
Natural language understanding
Symbolic knowledge representation and reasoning
Currently Teaching
CSCI-140
Computer Science for AP Students
4 Credits
This accelerated course covers material from the first-year sequence of courses and provides the foundation for all subsequent Computer Science courses. The course stresses problem solving while covering modern software development techniques and introducing essential software tools. Topics include tree and graph structures, nested data structures, objects, classes, inheritance, interfaces, object-oriented collection class libraries for abstract data types (e.g. stacks, queues, maps, and trees), and static vs. dynamic data types. Concepts of object-oriented design are a large part of the course. Software qualities related to object orientation, namely cohesion, minimal coupling, modifiability, and extensibility, are all introduced in this course, as well as a few elementary object-oriented design patterns. Input and output streams, graphical user interfaces, and exception handling are covered. Note: Requires department permission for registration.
CSCI-331
Introduction to Artificial Intelligence
3 Credits
An introduction to the theories and algorithms used to create artificial intelligence (AI) systems. Topics include search algorithms, logic, planning, machine learning, and applications from areas such as computer vision, robotics, and natural language processing. Programming assignments are an integral part of the course.
CSCI-630
Foundations of Artificial Intelligence
3 Credits
An introduction to the theories and algorithms used to create artificial intelligence (AI) systems. Topics include search algorithms, logic, planning, machine learning, and applications from areas such as computer vision, robotics, and natural language processing. Programming assignments and oral/written summaries of research papers are required.