Curriculum - BS/MS Dual Degree
BS/MS Dual Degree Option
As part of a rapidly changing field, computer engineers are constantly in demand in a variety of industries to design and research advanced computing systems. A Master's degree in engineering is becoming increasingly important for students to join the workforce prepared for the challenges and demands they will face.
The Computer Engineering BSMS program is an expedited dual-degree program for RIT students to pursue and finish both BS and MS degrees in approximately 5-year period. The BSMS students are expected to obtain fundamental training in Computer Engineering through the undergraduate curriculum as well as focus on a concentration area at the graduate level through course work and thesis research.
At the end of their second year in BS degree program, computer engineering students are given the option of joining the combined, expedited BS/MS program. This option is available to students who have a minimum cumulative 3.4 GPA. If accepted, the BS/MS students will continue their study following the BS/MS curriculum starting from the third year to complete both a BS degree and an MS degree in computer engineering.
The BS/MS students are scheduled to go on co-op beginning in the summer of the second year, and they are only required to complete two summer and one semester co-op blocks – one semester fewer than the students in the BS degree program. The BS/MS students take additional courses to satisfy the MS degree requirement with three courses double counted towards both the BS and the MS degrees. The students are required to maintain at least a 3.0/4.0 grade point average to stay in the BS/MS program. A graduate thesis is required to complete the requirements for the MS degree. Students typically begin their thesis research exploration in their fourth year at RIT.
The combined BSMS dual degree program in Computer Engineering will have the students take the required undergraduate courses for the BS degree as well as the required courses for the MS degree, with three courses double counted for both degrees. The three courses are:
- CMPE-630 Digital IC Design: counted towards CMPE-530 for the BS degree and a Restricted Graduate Core for the MS degree.
- CMPE-670 Data and Communication Networks: counted towards CMPE-570 for the BS degree and a Graduate Elective for the MS degree.
- MS Graduate Elective to be counted as a BS Free Elective
Other than the required courses, the Computer Engineering BS degree has 2 Free Electives and 2 Professional Electives, and the Computer Engineering MS degree has 5 Graduate Electives. With the above course counting, each BSMS dual degree student will have a total of 1 Free Elective, 2 Professional Electives, 1 Restricted Graduate Core, and 4 Graduate Electives.
Restricted Graduate Core:
- CMPE-655 Multiple Processor Systems
- CMPE-660 Reconfigurable Computing
- CMPE-685 Computer Vision
Computer Engineering Concentration Areas
Students in the BS/MS dual degree program in Computer Engineering are strongly encouraged to choose a concentration area among the following:
- Computer Architecture - Computer architecture area deals with hardware resource management, instruction set architectures and their close connection with the underlying hardware, and the interconnection and communication of those hardware components. Some of the current computer architecture challenges that are being tackled in the Computer Engineering Department include energy efficient architectures, high performance architectures, graphic processing units (GPUs), reconfigurable hardware, chip multiprocessors, and Networks-on-Chips.
- Integrated Circuits and Systems - Modern processors demand high computational density, small form factors, and low energy dissipation with extremely high performance demands. This is enabled by the nanoscale and heterogeneous integration of transistors and other emerging devices at the massive-scale. Such nanocomputers will open unimaginable opportunities as well as challenges to Computer Engineers. This research focuses designing computers with emerging novel technologies in the presence of severe physical constraints; investigating dynamic reconfigurability to exploit the power of nano-scale electronics for building reliable computing systems; and studying the applicability of emerging technologies to address challenges in computing hardware of the future.
- Networks and Security - The prevalence of interconnected computing, sensing and actuating devices have transformed our way of life. Ubiquitous access to data using/from these devices with reliable performance as well as security assurance presents exciting challenges for engineers and scientists. Resilient to environmental uncertainty, system failures and cyber attacks requires advances in hardware, software and networking techniques. The research track on Networks and Security in Computer Engineering focuses on intelligent wireless and sensor networks, cryptographic engineering, and predictive cyber situation awareness.
- Computer Vision and Machine Intelligence - Visual information is ubiquitous and ever more important for applications such as robotics, healthcare, human-computer interaction, biometrics, surveillance, games, entertainment, transportation and commerce. Computer Vision focuses on extracting information from image and video data for modeling, interpretation, detection, tracking and recognition. Machine Intelligence methods deal with human-machine interaction, artificial intelligence, agent reasoning, and robotics. Algorithm development for these areas spans image processing, pattern recognition and machine learning, and is intimately related to system design and hardware implementations.
- Signal Processing, Control and Embedded Systems - This research area is concerned with algorithms and devices used at the core of system that interacts with our physical world. As such, this area considers the sensing, analysis and modeling of dynamic systems with the intent of measuring information about a system, communicating this information and processing it to adapt its behavior. Application areas are robust feedback-based control where uncertainty in the dynamics and environment must be considered during the design process and signal processing algorithms and devices for system sensing and adaptation.
These concentration areas are designed to provide students the opportunity to gain additional knowledge in an area of particular interest and to prepare for thesis research within the computer engineering discipline.
Computer Engineering Semester Curriculum:
Computer Engineering Transitional Quarter/Semester Flowcharts based on Freshmen entry date: