Senior Design Projects Topics

FALL 2023 Senior Design Topics 

 Instructor: Professor Zhigang Zhu (1DD)

 BEAT+: Adding Branding and Entrepreneurship for Real-World  Applications Using Emerging Technologies: AI, AR, AT, and Apps

Undergraduate Seniors in CS and CpE will work in teams to design emerging technical solutions in Artificial Intelligence (AI), Augmented and Virtual Reality (AR/VR), Assistive Technology (AT), data analytics and app development skills to solve real-world application problems for social good and national priorities. Teams will  learn basic branding principles (how to design user interfaces and communicate with end users and community partners about their technical solutions). Teams will be encouraged to participate in academic research projects, the CCNY Zahn Innovation competition and NYSID’s CREATE competition. We will invite collaborators from both academia and industry as the BEAT+ mentors and evaluators. Students are expected to learn new software/hardware tools and skills by doing their projects.     

Instructor: Professor Kaliappa Ravindran (EE)

Students will be provided with 7-8 projects to choose form, inter-mixed with lecture sessions covering the underlying theory and programming elements. The project descriptions are custom-made, which are designed to bring out a broader exposure of the students to real-world problems. The projects involve the core areas of computer science & engineering: such as telecom networks, distributed computing, GIS, and data-science. A broader coverage of the project topics is planned, as listed below:

     1. Simulation of multi-vehicle coordination in autonomous driving

     2. Algorithms for cyber-fencing of metro-areas by multiple drones

     3. Bandwidth-adaptive video downloads using scalable video encoders         

     4. Software-defined network (SDN) methods for improved end-to-end video quality     

     5. Replica voting algorithms to detect malicious data in transactional services

     6. Use of GIS tools for prediction of disease epidemics across multiple geographic regions

    7. Multiplayer game simulation methods for robot soccer-games

Instructor: Professor Jianting Zhang (CC)

High-Performance Deep Learning: Systems and Applications

This Capstone section will introduce students to a new field of High-Performance Deep Learning from system and application perspectives. Topics include #1) a brief introduction to BigData, Parallel Computing and Deep Learning (DL) #2) popular DL algorithms such as MLP, CNN, RNN and Transformer #3) DL systems with a focus on PyTorch. After presenting case studies of high-performance DL applications towards the end of the first semester, students are expected to propose, design and implement DL applications of their choices in the second semester (CSc59867). Projects are expected to be interesting, useful and with appropriate level of technical depth.

Instructor: Professor Thomas Sessa (4TU) (CC)

Led by a senior executive of a NYC based health tech company, students will learn the fundamentals of the US healthcare system and the role big data, artificial intelligence and machine learning is playing in reshaping the industry. Case studies and suggested projects will have a heavy emphasis on addressing many of the biggest healthcare related challenges of today, eg. epidemiology, public health, population health, patient access/equity. Using both private and publicly available data sets, teams will propose a project of their own and follow a user centered design approach to devise a solution that will benefit the patient ecosystem using software development and data science, which will be implemented in the second semester of this class (CSC 59867)​.

Last Updated: 03/28/2023 16:21