Senior Design Projects Topics

FALL 2024 Senior Design/Senior Project Topics

Professor: Zhigang Zhu (Section 2MN)

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) and basics of entrepreneurship (customer discovery, business models, etc). 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.

Professor: Jianting Zhang (Section M)

GPU-Accelerated Data Science

With fast increasing availability of Graphics Processing Units (GPUs) in data centers and personal computing systems, there are significant interests to adopt the massively data parallel computing power on GPUs for Data Science, including data management, data analytics, machine learning and AI applications.

In the two-semester project-oriented capstone courses, the first semester (Capstone I) will introduce the basics of GPU hardware, the leading data parallel programming model, i.e., Nvidia CUDA, its integration with Python and various applications in Data Science. Small project templates will be provided to students to gain hand-on experiences in GPU programming using C++ and Python Interfaces. Students are expected to develop a group-based project proposal that can focus either on computing efficiency or domain-specific applications. The proposal will be implemented in the second semester (Capstone II).

Students are expected to have reasonable skills in C++ programming (from CSc 212) and basic knowledge of Python-based Data Science software (from CSc 113 or self-learning); but more importantly, enthusiasm in parallel computing and its realizable efficiency in practical applications.

Professor: Huy Vo (Section B)

This course provides students with technical preparations for defining projects and crafting a strategy to identify user requirements, possibilities for new designs and engineering solutions to support their project objectives. Topics in data science will be recommended, however, students are welcome to propose their own projects. Students are encouraged to strengthen their skills in full-stack, web and/or mobile development throughout the course. At the end of Senior Design I, students are expected to form teams, complete a project proposal, and a mock-up/prototype of the product with a clear timeline of deliverables. A prototype must be completed by the end of Senior Design II.

Professor: Kaliappa Ravindran (Section 5FG)

Students select one project from the below list, based on their strengths and interests. Projects cover foundational concepts and theory underpinning. The theory and concepts broadly cover many aspects, such as: algorithms, probability & statistics, computer networks, operating systems, and distributed computing. Students can also propose their own project (will be approved if it meets the overall expectation of the course). Students are strongly encouraged to work as 2-member teams to maximize the learning of technical knowledge.
Below is a compilation of the capstone plan, with a list of 7 projects to choose from, inter-mixed with lecture sessions covering the underlying theory and programming elements.
  1. Simulation of multi-vehicle coordination in autonomous driving
  2. Bandwidth-adaptive video downloads using scalable video encoders
  3. Software-defined network (SDN) methods for improved end-to-end video quality
  4. Replica voting algorithms to detect malicious data in transactional services
  5. Use of GIS tools for prediction of disease epidemics across multiple geographic regions
  6. Multiplayer game simulation methods for robot soccer games
  7. Algorithms for target tracking by multiple unmanned ground vehicles

Last Updated: 04/16/2024 12:26