Computer Engineering and Analytics
With their senior design project, Computer Engineering and Analytics students will combine a core engineering foundation and cutting-edge data science across topics such as software and systems, control systems and robotics and data analysis to address open-ended design problems supplied by industry and faculty. Over the course of one semester, this will manifest as a cohesive, detailed and high-confidence list of product and engineering specifications, proof of concept and potentially a prototype or working model of some aspect of the design project.
Projects start in fall only and last 2 semesters. Project proposals are due in mid-March. Submit your proposal here:
Student Skills:
- Proficiency in Research Methodologies: Developing and conducting appropriate experimentation, analyzing and interpreting data and using engineering judgment to draw conclusions.
- Design Tools: Appropriately implementing tools and equipment from a wide range of technologies, including Artificial Intelligence (AI), sensors and control systems, robotics and virtual reality and more.
- Technical Communication: Effectively communicating design ideas and conclusions to a range of audiences.
- Problem Solving: Being able to identify, formulate and solve complex engineering problems by applying principles of engineering, science and mathematics.
- Applied Solutions and Standards: Applying engineering design principles to produce solutions that meet specified needs with consideration of public health, safety and welfare, as well as global, cultural, social, environmental and economic factors.
- Informed Decision Making: Recognizing ethical and professional responsibilities in engineering situations and making informed judgments, which must consider the impact of engineering solutions in global, economic, environmental and societal contexts.
- Engaged Teamwork: Functioning effectively on a team whose members together provide leadership, create a collaborative environment, establish goals, plan tasks and meet objectives.
Previous Projects:
VR Hand Tracking Integration with Robotic Arm and Haptic Feedback
This project focused on the development and integration of a robotic arm with virtual reality (VR) systems and haptic feedback, aimed at enabling remote operations such as surgeries. The system utilizes a WLkata robotic arm, a bHaptics TactGlove DK2 and a Meta Quest 3 VR headset to create an immersive and precise environment for remote manipulation tasks. This innovative integration of VR, haptic feedback and robotics represents a significant advancement in remote operation technology, with applications beyond remote surgeries such as hazardous material handling, precision manufacturing and other fields requiring remote dexterity. By bridging the gap between human sensation and robotic precision, the project demonstrates the potential for improving accuracy, safety and efficiency in environments where direct human involvement is limited or unsafe.
Team members: Youssef Mohamed, Emanuel Lara, Robert Vega
HR.AI: An AI-Driven Framework for Intelligent Recruitment and Skill Assessment
HR.AI is an intelligent recruitment framework that integrates advanced natural language processing and automation to streamline resume screening and candidate evaluation. Built with a robust Flask backend and OpenAI’s large language models, the platform supports dynamic prompt configuration, skill assessments and detailed evaluation workflows tailored for multiple job roles from software engineering to educational hiring. The system empowers recruiters by shifting traditional hardcoded AI logic into flexible, editable prompts, effectively handing control to the user while preserving the reliability and consistency of grading logic. HR.AI reimagines applicant tracking systems through the lens of applied AI and offers recruiters a scalable solution adaptable to their unique hiring needs.
Team members: Abdullah Abdel-Khalek and Anish Siddiqui
Control System Environmental Regulator for Application to a Greenhouse
The increasing challenges of climate change, resource scarcity and population growth have intensified the need for innovative agricultural solutions. Many plants require highly specific environmental conditions for optimal growth, often limiting their cultivation to particular geographic regions or seasons. This project addresses these limitations by designing and implementing a self-regulating greenhouse capable of creating controlled environments tailored to specific plant requirements. Using advanced control systems and feedback loops, the greenhouse will monitor and adjust critical growth factors such as temperature, humidity/soil moisture and CO2 levels. To test the system’s reliability and robustness, the greenhouse was subjected to cc controlled external stressors, such as temperature fluctuations and variable humidity levels, and the effectiveness of the feedback loop was assessed based on its ability to maintain environmental parameters within specified thresholds.
Team members: Nathan Tran, Alton Pike and Julia George
