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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. Franceli L. Cibrian's research is focused on the design, development, and evaluation of ubiquitous interactive technology to support child development and vulnerable population.  

Students working on projects in her group might: 

  • Conduct user studies to design emerging technology and applications that support healthcare and education. 
  • Develop novel technology (e.g., voice assistants, wearables and deformable displays) to support child development and individuals with disabilities. 
  • Evaluate the impact of novel devices using qualitative and quantitative methodologies and automatic data analysis. 

 

Dr. Nasim Mohammadi Estakhri's  research is focused on the design of novel optical meta-structures that involve enhanced and function-based light-matter interaction phenomena. 

Students working on projects in her group might:   

  • Design planar structured materials (i.e. metasurfaces) for on-demand wave-shaping functionalities.
  • Use machine learning to design advanced optical components and optical computational platforms.
  • Design next-generation antennas for low-noise, efficient communication.
  • Work on multi-layer and three-dimensional metamaterials for dispersion and polarization control. 

 

Dr. Mark Harrison's research is focused on the development of new photonic and plasmonic devices for use in optical computing and sensing applications. 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.
  • Characterize fabricated circuit behavior with benchtop equipment, including lasers and fiber optics.
  • Conduct experiments to explore device behavior for either sensing or computing applications. 

 

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:

  • 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

 Currently, Dr Kurz is particularly interested in supervising projects that bring together programming languages and natural language processing.

 

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 works on the design and development of novel haptic interfaces, with an emphasis on assistive technology. Specific projects under investigation include hand training system, wearable tactile music, and refreshable braille-graphic display.

Students working with her might:

  • Design hardware solutions for novel electro-mechanical systems using microcontrollers, sensors, and actuators.
  • Develop firmware algorithms and mobile applications for these closed-loop control systems.
  • Characterize commercial haptic devices (e.g. Ultraleap STRATOS, Phantom Omni, etc.).

 

Dr. Chelsea Parlett-Pelleriti's research involves applying statical methods (particularly Bayesian methods) and machine learning methods to behavioral data. She has worked specifically on improving inferences for a specific meta memory task, as well as in research about the autism spectrum, and other behavioral applications.

Students working with her might:

  • Apply methods such as Bayesian parameter estimation, Item Response Theory, or Unsupervised Machine Learning to problems in psychology, law, ecology, or other behavioral fields. 
  • Take complex methods and communicate clearly about them in order to bridge the gap between applied statisticians and practitioners in other fields.

 

Dr. Trudi Qi’s research is at the intersection of computer graphics, human-computer interaction, virtual reality (VR), and artificial intelligence (AI). She is particularly interested in studying multidisciplinary problems with practical impact by connecting visual computing technologies with real-world human-centered endeavors. Potential application areas of her research include healthcare education and training, assistive technology, collaborative VR, and computational creativity.

Students with an interest in computer graphics, game development, VR/AR, or AI are welcome to undertake or participate in her research projects:

  • Build human-interactive 3D modeling and animation tools for content creation in VR/AR
  • Develop VR/AR simulation techniques for medical education and training
  • Build ML models for 3D computer graphics problems such as shape classification
  • Develop interactive VR motion data visualization and statistical analysis tools
  • Utilize AI/ML technologies to assist with human learning and training in VR/AR

 

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.

 

Dr. Yuxin Wen's research is focused on data science and Big data analytics in complex systems with the applications in manufacturing, aerospace, healthcare and traffic, etc.

Students working on projects in her group might:

  • Develop advanced machine learning tools for real-time equipment health monitoring, diagnostics and prognostics that enable decision-making.

  • Conduct change-point, anomaly detection for quality and reliability improvement in manufacturing process.

  • Build robust models on severity assessment and progression prediction for diseases.

 

Dr. Peiyi Zhao's research is focused on the development of integrated circuits to achieve low power, low energy consumption in order to reduce the energy consumption of data centers in big data era.

These projects will allow students to learn about clocking integrated circuits to be used in digital processors.  

Students working on projects in his lab might:

  • Design digital integrated circuits using CADS tools
  • Design logic circuits/architecture using CAD tools
  • Measure power and speed of integrated circuits 
  • Investigate/examine different low power/energy techniques

 

Changing Care Through Data

Grand Challenges Initiative

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.