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Fowler School of Engineering

» Research Opportunities

At Fowler School of Engineering, we want our students to engage in the deeply impactful experiences that accompany research projects and programming. That’s why we foster a research community that serves both undergraduate and graduate-level students, providing early access to student and faculty-led endeavors.

Here to Uncover, Understand and Solve

Fowler Engineering faculty conduct research on a wide range of topics, including cybersecurity, behavioral health, assistive technologies, artificial intelligence/machine learning, optical computing, internet of things, green computing, and the mathematical foundations of computer science.

We encourage our students to connect directly with faculty and discuss what their role could be in faculty-led research.

 

Dr. LouAnne Boyd's research is focused on the design, development, and evaluation of innovative assistive and accessible technologies. Students working on projects in her group apply theories and techniques from human-computer interaction to support diversity and inclusion. 

Students may: 

  • Conduct user studies using an iterative design process to discover inclusive user requirements
  • Develop new interaction designs for novel platforms to improve accessibility
  • Evaluate the impact of prototypes for diverse user groups

 

 

Dr. Mark Harrison's research is focused on the development of new architectures for integrated photonic logic circuits used in optical computing. These projects will allow students to learn about optics and photonics while applying computer architecture and digital logic principles to novel systems.

Students working on projects in his lab might:

  • Develop new integrated optical device designs via high-powered simulations
  • Investigate fabrication approaches to combine discrete devices into larger-scale logic circuits
  • Characterize fabricated circuit behavior with benchtop equipment, including lasers and fiber optics

 

 

Dr. Alexander Kurz works on the mathematical foundations of computer science in general and programming languages and software engineering in particular.

Mathematics and computer science students with an interest in the mathematical and logical foundations of their subject, are welcome to undertake a research project in this area on:

  • Logic and category theory
  • Artificial intelligence
  • Multi-agent systems 
  • Formal methods
  • Software verification 
  • Distributed systems 
  • Probabilistic programming languages
  • Model checking
  • SAT and SMT solving
  • Theorem proving 
  • Bitcoin and blockchain

 

 

Dr. Erik Linstead is the principal investigator of the MLAT Lab at Chapman University. His research interests span all areas of artificial intelligence and machine learning, with applications to software engineering, remote sensing, and developmental disorders. Most recently, his work has focused on autism spectrum disorder and deep learning. 

Students working on projects in his group:

  • Build machine learning models with multiple programming languages
  • Use GPU-enabled computing to develop computer vision algorithms, and architect software solutions to quickly find and retrieve patterns in big data 
  • They will co-author papers that make novel contributions to the scientific literature

 

 

Dr. Andrew Lyon's research is focused on the development of new materials for regenerative medicine applications. These efforts then couple with collaborative research on how those new materials can be applied to wound healing and tissue regeneration.

Students working on projects in his group might:

  • Perform new polymer synthesis
  • Develop approaches for high-resolution microscopy of nanomaterials
  • Develop image processing algorithms to extract quantitative data from those microscopies

 

 

Dr. Dhanya Nair researches how to characterize human touch and develop tactile assisting technologies, such as is used in Braille displays.

Students will:

  • Utilize microcontrollers, sensors and actuators for designing
  • Develop or characterize novel electro-mechanical systems 
  • Apply ranging from braille-displays, mid-air haptics, educational training, and music therapy

 

Dr. Elizabeth Stevens’ research sits at the intersection of machine learning and behavior analysis. In particular, she has explored unsupervised techniques for modeling subtypes of autism spectrum disorder (ASD) and how they respond to treatment intensity and duration. 

Students working with her might:

  • Explore how learning objectives map to certain identified subgroups or look at clustering within challenging behaviors 
  • The overall goal of this research is to effectively impact treatment and tailor therapy plans to best fit the individual in hopes of obtaining the highest rates of success.

 

 

Changing Care Through Data

Grand Challenges Initiative

Dean Lyon working with Students

The Grand Challenges Initiative is an interdisciplinary, student-driven part of every science and engineering student’s curriculum where they guide research and study issues that fascinate and perplex us, building critical skills over a two-year timeline.

 


Get Connected to Real Research

Find a project that inspires you to talk with a faculty member.