Faculty Research and Teacher Research Topics

The proposed RET Site has eleven faculty mentors. In the original proposal, for each faculty mentor, we briefly described 2-3 activities a teacher can be involved in. While most of the activities are research-oriented projects, some involve the development of educational kits/tools. We understand that, instead of pure development of education materials and tools, each teacher should be engaged in research projects among other professional development activities. We acknowledge that mixing the descriptions of research projects with activities on educational materials, as presented in the original proposal, was confusing. In the implementation of the proposed RET Site, we will ensure that each teacher gain substantial authentic research experiences in addition to their curriculum development activities.  In the following, we describe specifically the research projects planned for the teachers under each faculty mentor.

TOPIC 1: Biosensors and Biomedical Devices

Wen Li

Dr. Wen Li (Electrical & Computer Eng.; Biomedical Eng.)

  • Faculty research area: Implantable Brain-Machine Interface. Dr. Li’s research focuses on the development of implantable neural interfaces for sensing brain signals, using advanced organic/inorganic biomedical micro-electro-mechanical systems (bioMEMS) technologies. Current projects include the development of (1) hybrid opto-electro arrays for optical stimulation and electrical recording of neural activity; (2) polycrystalline diamond based electrochemical sensors; and (3) packaging methods to prolong the functional lifetime of chronically implanted microsensors. 
  • Research projects for teachers:  include the development of (1) computational models to simulate and optimize mechanical properties and stability of implantable neural probes; (2) signal processing algorisms to better understand large-scale neural connectivity from brain recordings; and (3) bioMEMS processing and packaging  echniques for building neural implant devices. 

Dr. Evangelyn Alocilja (Biosystems & Agricultural Eng.)

  • Dr. Evangelyn AlociljaFaculty research area: Nano-Enabled Biosensors for Rapid Detection of Infectious Disease. Dr. Alocilja’s research is on designing and developing nano-enabled biosensors for rapid detection of infectious agents applicable in resource-limited settings. Part of the development is the synthesis of magnetic nanoparticles functionalized with pathogen-associated molecular receptors to quickly extract, purify, and concentrate microbial pathogens (e.g. bacteria) from complex matrices. The extracted bacteria are then detected directly by electrochemical methods.
  • Research projects for teachers: include computational modeling of various nanosensors for electrochemical detection. Other projects include extraction and detection of infectious agents which are transmitted through (1) food, (2) water, (3) surfaces, and (4) body fluids. 

Dr. Zhen Qiu (Biomedical Eng.)

  • Faculty research area: In-vivo MEMS-based Bio-optical Sensing and Imaging. Dr. Zhen Qiu's research interests include biomedical optics, MEMS/MOEMS, multi-modal targeted imaging, wearable and implantable medical devices, ultrafast laser applications. His current work is focused on miniaturized optical Dr. Zhen Qiuimaging  system development for early cancer detection and imaging-guided surgical navigation, such as wide-field imaging-guided confocal microendoscope, multi-photon/SHG handheld microscope, surface-enhanced Raman spectroscopy. 
  • Research projects for teachers: include the development of (1) real-time system control, signal acquisition, imaging reconstruction and biomedical signal post-processing for early cancer detection and in-vivo imaging-guided surgery; (2) User-friendly GUI development (Matlab/Python/C++/C#) for clinics translational imaging system. 

TOPIC 2: Robotics and Human-Machine Interaction

Dr. Vaibhav Srivastava

Dr. Vaibhav Srivastava (Electrical & Computer Eng.)

  • Faculty research area: Human-Robot Interaction and Robotic Networks. Dr. Srivastava’s research focuses on the development of human-robot interaction, robotic networks including bio-inspired swarms, and aerial robotics. Current projects include the development of algorithms for multiagent robotic search, human-team supervised robotic teams, dynamic analysis of EEG signals, bio-inspired decision-making in robotic swarms, and fault-tolerant control of aerial robots. 
  • Research projects for teachers: include the development of (1) robotic swarms testbed to implement bio-inspired behavior; (2) EEG measurement-based human-swarm interaction; and (3) computational models to analyze EEG data for human-robot interaction. 

Dr. Xiaobo Tan (Electrical and Computer Engineering) Xiaobo Tan

  • Faculty research area: ARobotic Sensing Platforms and Soft Robotics. Dr. Tan’s research focuses on underwater robotics and soft robotics. In particular, his group specializes in developing bio-inspired fish-like robots for underwater sensing applications, such as sampling harmful algal blooms and tracking invasive fish species. In the area of soft robotics, he is interested in electroactive polymer sensors and actuators, as well as 3D-printed soft sensors. 
  • Research projects for teachers: include the development of (1) underwater sensing platforms (for example, robotic boats and remotely operated underwater vehicles); (2) artificial lateral line systems that emulate fish’s flow-sensing organ, for underwater robots to perceive the ambient hydrodynamic conditions; (3) soft sensors for measuring the strain and force of soft robotic arms. 

TOPIC 3: Connected Sensing Systems and Sensor networks

Dr. Mi Zhang (Electrical & Computer Eng.; Computer Science & Eng.)

Dr. Mi Zhang

  • Faculty research area: Smart and Connected Sensing Systems.  Dr. Zhang’s research focuses on the development of smart and connected sensing systems that are mobile, distributed across edge and cloud, or embedded in the physical world. Current projects include the development of (1) efficient, dynamic, and scalable computational framework to enable deep learning on resource-constrained sensing devices such as smartphones and Internet of Things (IoT), (2) smart sensing systems for human activity and vital sign monitoring; and (3) mobile health systems and big sensor data analytics. 
  • Research projects for teachers: include the development of (1) a smart hearing aid enabled by energy-efficient deep learning algorithms; (2) WiFi-based device-free sensing system to support aging in place; and (3) smartphone-based behavior monitoring and analytics system for mental healthcare management. 

 Dr. Li Xiao (Computer Science & Eng.)Dr. Li Xiao

  • Faculty research area: Smartphone Networking and Communications. Dr. Xiao’s research interests include distributed and networking systems, wireless and mobile computing, overlay systems and applications, system resource management, and design and implementations of experimental algorithms. Current projects focus on (1) the development of smart algorithms to enable the automatic switching between WiFi Direct and Bluetooth to emphasize minimizing energy consumption while still maintaining an efficient network and (2) study of different strategies such as load balancing to help increase the lifetime of the network. 
  • Research projects for teachers: include (1) modulation scheme diversity in multicarrier smartphone networks and (2) resource management and interference precancellation in heterogeneous cellular networks. 

TOPIC 4: High Performance Computing, Pattern Recognition, and Machine Learning

Dr. H. Metin Aktulga (Computer Science & Eng.)Dr. H. Metin Aktulga

  • Faculty research area: High-Performance Computing, Big Data Analytics. Dr. Aktulga’s research focuses on the design and development of parallel algorithms, numerical methods and software systems that can harness the full potential of state-of-the-art computing platforms to address challenging problems in large-scale scientific computations and big-data analytics problems. A distinguishing aspect of his research is the close collaborations that he has built with domain experts in a wide range of fields such as molecular modeling, materials science, nuclear physics, and sensor systems.
  • Research projects for teachers: include the development of (1) scalable distributed algorithms for sensing systems and (2) efficient algorithms for embedded processors to improve the performance and/or energy usage of smart sensors. 

Dr. Arun Ross (Computer Science & Eng.) Dr. Arun Ross

  • Faculty research area: TBiometrics and Pattern Recognition. Dr. Ross’s research interests include pattern recognition, biometrics, machine learning, and computer vision. His current projects include cross-spectral face recognition, periocular biometric recognition, anti-spoofing methods for fingerprints, integrating demographics with biometrics, privacy-preserving schemes for biometric data, fusing fingerprint with DNA, mobile biometrics, big data and biometrics in the cloud. 
  • Research projects for teachers: include the development of (1) graphical models for predicting missing/incomplete biographic data in biometric records and (2) sensor forensics for near-infrared iris imagery. 

Center Research Efforts:

Dr. Elisa Toulson

 Energy and Automotive Research Laboratory (EARL)- Dr. Elisa Toulson (Mechanical Eng.; EARL) 

  • Faculty research area: Alternative Fuels and Combustion. Dr. Toulson is the faculty contact at EARL. Her research interests include combustion, ignition and chemical kinetics with an emphasis on alternative and next-generation renewable fuels. Current projects include research into the autoignition and laminar flame speed characteristics of alternative fuels and examining enhanced ignition technologies, which can improve fuel consumption, reduce emissions, and improve combustion stability in internal combustion engines.
  • Research projects for teachers: include (1) experimental testing of ignition systems with optical diagnostics in a rapid compression machine; (2) measurement of combustion characteristics of alternative fuels; and (3) computation fluid dynamics modeling of combustion.

Dr. Witold Nazarewicz

Facility for Rare Isotope Beams (FRIB) - Dr. Witold Nazarewicz (Physics and Astronomy, FRIB)

  • Faculty research area: Global Properties of Atomic Nuclei. Dr. Nazarewicz is the chief scientist and faculty contact at FRIB. His research expertise is the theoretical description of those exotic, short-lived nuclei that inhabit remote regions of nuclear landscape. This research invites a strong interaction between nuclear physics, many-body-problem, and high-performance computing. His research has made important contributions to nuclear structure and reaction physics, especially in the areas or rare isotopes and nuclear dynamics.
  • Research projects for teachers: Potential teacher projects include the development of (1) computational tools to visualize results of large-scale calculations of nuclear properties and (2) graphical interfaces between experimental and theoreticaldatabases that will allow direct comparison of computer simulation results with the data. 

Fraunhofer Center for Coatings and Diamond Technologies (Fraunhofer CCD): Dr. Thomas Schuelke (Director of Fraunhofer CCD and Faculty of Electrical & Computer Eng.) and Dr. Cory Rusinek

  • Faculty research area: Diamond-based Chemical Microsensors, Drs. Schuelke and Rusinek’s research focuses on the development of novel thin film chemical microsensors for the detection of environmentally and biologically-Dr. Witold Nazarewiczrelevant compounds. Current projects include the development of (1) thin film deposition techniques for various carbon materials; (2) wearable boron-doped diamond sensors for toxic heavy metal measurements in human perspiration; and (3) new electrode materials for electroanalytical applications.Dr. Cory Rusinek
  • Research projects for teachers: include the investigation of (1) different electrode materials for wearable sensors for sensitive detection of toxic metals and other analytes of interest, (2) complex water systems where measurements of heavy metals are needed, and (3) the performance of all-diamond microfiber electrodes compared to traditional electrodes.