EXPLORING ELECTRICAL ANDCOMPUTER ENGINEERINGRESEARCH OPPORTUNITIES

The Electrical & Computer Engineering department provides a host ofpaid research opportunities in communications digital system design,energy and power systems, integrated circuits, nanoscale devices andmaterials, plasma and vacuum electronics, and signal processing. Thevast majority of research is funded by federal government, foundation, orcorporate sponsors. The department is proud to have one IEEE fellowand three NSF CAREER recipients among our faculty. Our teams engageactively with national and international research communities andfrequently pursue interdisciplinary research with industry partners.

NANOSCALE MATERIALS & DEVICES

Amorphous ElectronicsWe design new electronic components that could replace some of the existing higher-power consumption components in portable electronicdevices. In addition, we create new types of electronic devices that may eventually lead to di1erent computing architectures. We exploresignificant changes to the way computers process information, including the ability of a computer to make independent decisions based oninternal and external inputs. We have developed a back-end-of-line fabrication process that allows our novel device materials to be integrated intoa CMOS-based test chip or platform. We perform complete electrical characterization in our laboratory with variable temperature, frequency,optical, and magnetic field capabilities.

Faculty: Kris Campbell (ECE)

CMOS PhotonicsThe rise of “big data” and a profusion of network-intensive applications such as cloud computing, HD multimedia streaming,and data mining, have motivated technologies that manage skyrocketing data rates between chips, motherboards,computers, and networks. Conventional electrical signaling over copper channels is severely limited by attenuation,dispersion, and crosstalk. To alleviate this bottleneck, we are researching CMOS photonics integrated circuits which employlight in a guided medium to enable >1 Tbps on-chip interconnects for multi-core processors, datalinks for “green” datacenters, and photonics-enabled RF and biochemical sensing. We focus on modeling photonic components on a system-leveldesign, high-speed mixed-signal and microwave circuit design, and CMOS photonics system packaging and testing.

Faculty: Vishal Saxena (ECE) and Wan Kuang (ECE)

Electrical Energy StorageA rapid rise in energy consumption fueled by economic growth and population expansion has intensified electrical energystorage technology research. Such e1orts will promote a sustainable future by reducing imported fossil fuel dependenceand greenhouse gas emissions. Electrical energy storage technologies can power a wide range of devices such asportable electronics, power tools, and electric vehicles, and can also enable application development for “load leveling” ofrenewable wind and solar energy sources. Our research focuses on developing new nanoarchitectures for rechargeablebatteries (e.g., Li and Na). Students studying energy nanomaterials will gain hands-on experience in materials synthesisand characterization, electrochemical processing, coin-cell battery construction, and electrochemical characterization.

Faculty: Claire Xiong (MSE)

Multifunctional NanocompositesWe study the electrical and thermal transport properties of electronic nanomaterials such as carbon nanotubes and graphene. Using thisfundamental understanding, we aim to design energy e4cient transistors for post-10 nm silicon CMOS computing, as well as multifunctionalnanocomposites for applications in the energy, healthcare, and aerospace industries. This research focuses on: (1) high-volume manufacturing ofatomically thin metallic, semiconducting, and insulating nanomaterials; (2) novel methods of material characterization; (3) material design withtailored electrical, thermal, thermoelectric, and electrochemical properties; (4) understanding electronic transport in nanoscale transistors madefrom emerging nanomaterials; and (5) predicting the e1ects of nanomaterials on water quality, our food supply, and human health.

Faculty: David Estrada (MSE), Elton Graugnard (MSE), Kurtis Cantley (ECE), and Yanliang Zhang (MBE)

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Current research projects

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Nanoionic ElectronicsNanoionic research deals with devices based on ion-related processes such as conductive bridge memristors and radiationsensors. These emerging technologies will replace today’s non-volatile flash devices to address the increasing scalingproblems. Our research answers questions related to new memory solutions, formation of nanoionic memristor arrays forlogic functions, and improvement of memristor radiation hardness, speed, and stability. The research focuses on: (1) thedesign of memristors/arrays and sensors; (2) new material and device structure solutions; (3) radiation studies andsensing; and (4) new architectures for cognitive systems. Students working in this area gain experience in electrical andmaterials engineering, device testing, materials characterization, and cognitive systems implementation.

Faculty: Maria Mitkova (ECE), Nader Rafla (ECE), and Darryl Butt (MSE)

NanophotonicsNanophotonics research scales optical devices and components to their ultimate size limits. We envision technologies of thenext decade as devices continue to add functionality, and become smaller and less expensive. We ask, “How small can adevice be?” Our team designs and makes devices that exploit near-field optical interactions on a scale well below thedi1raction limit. The research focuses on: (1) using DNA origami (DNA folding) as an assembly template for devicefabrication; (2) applying ultrafast laser-based coherent microscopy and spectroscopy for device characterization; and (3)integrating with current semiconductor fabrication methods. Students studying nanophotonics gain multi-disciplinary skillsin electrical engineering, optical engineering, physics, quantum electronics, materials engineering, chemistry, and biophysics.

Faculty: Wan Kuang (ECE), Elton Graugnard (MSE), Bernard Yurke (MSE), and William Knowlton (MSE)

Thermal-Electric DevicesOur research aims to develop novel materials and energy systems with significantly enhanced energy e4ciency. For example,we examine how to improve fuel economy in cars and also reduce their emissions. To achieve our goals, we develop methodsto study thermal and energy transport and conversion in nanostructured materials. These methods enable us to designpredictable novel material of unprecedented performance. We also develop devices and systems for energy harvesting,thermal management, and biomedical applications. A representative ongoing project is automotive waste heat recovery usinga nanomaterials-based thermoelectric generator. Students participating in this research will be exposed to cutting-edgenanoscale science and advanced technology for practical applications.

Faculty: Yanliang Zhang (MBE)

SIGNALS AND SYSTEMSAnimal Biometrics

Wildlife biologists conduct demography studies to identify individual animals and endangered species in wildpopulations. To do so, they capture animals on multiple occasions and compare specimen changes over time.Photographs of animals —such as frogs— were taken over days, weeks, months, or years with the intent to distinguishan image of a recaptured frog to images of “new” specimens. Our research simplifies this task by providing tools thatautomatically compare animals based on photographic images. These tools are based on both traditional methods

(PCA— principal components analysis) and modern methods (deep learning via convolutional neural networks).

Faculty: John Chiasson (ECE)

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Bio-molecular Data ProcessingGenome sequencing projects such as the Human Genome Project have generated a huge amount of data that continues to expand exponentially.Comparing this amount of human data against that of other organisms may lead to cures for many human diseases, such as cancers. However,such an e1ort requires considerable computing resources. Our research addresses this issue by using dedicated hardware and softwareapproaches to handle large and complex molecular biological databases. Methods to improve the speed and e4cacy of database search includefast application-specific hardware approaches employing ASICs, FPGAs or GPUs. Software methods include statistical model based successivedatabase filtering and integration of laboratory data on non-coding RNA molecules.

Faculty: Jennifer Smith (ECE)

Compressive SensingWe are researching a revolutionary approach for sampling large visual and audio data. Consider how most people can rapidly pick out a tree froma sky, visually sampling details to infer the whole. Compressive sensing is an approach where the processor need not capture the whole data.Instead, as data enters the device, the processor intelligently determine the next samplings. As a result, this method captures data at a lowersampling rate while maintaining the same quality. Our research examines the impact of compressive sensing on inference problems such as facialrecognition and on developing e4cient compressive sensing algorithms to identify the lowest sampling rate possible.

Faculty: Hao Chen (ECE) and Elisa Barney Smith (ECE).

Image ProcessingOur image processing research focuses on document and biomedical applications. We convert images ofdocuments into text you can edit (MS Word) or search (Google), and develop ways to improve low quality imageconversion. We also address image binarization and recognition, develop open-source document analysis software,and convert historical document collections to make them more accessible to scholars. In addition, we build toolsfor medical practitioners to better enable diagnosis and improve therapy selection. An example is registering(aligning) 2D fluoroscopy image sequences and 3D computed tomography or magnetic resonance images toproduce 3D motion clips. Many projects involve collaboration with researchers in biology, radiological science,community & environmental health, and kinesiology.

Faculty: Elisa Barney Smith (ECE)

Real-world Signal ProcessingOur research focuses on leveraging rapidly increasing device capabilities while minimizing energy usage. Today we carry unprecedented computerpower in our pockets. As device functionality increases, so do device energy needs. To address this area, we primarily study how to improve thealgorithm design behind basic device functions, minimizing algorithm complexity, and reducing computational load. We use multi-core real-timetargets and graphical processing units to develop innovative solutions to a wide variety of real-world signal processing problems. Software-defined radio applications are of particular interest.

Faculty: Thad Welch (ECE)

Signal Processing and CommunicationsDistributed systems enable individuals and organizations to operate at di1erent locations, where they can sense, monitor, communicate, control,and process information. Such systems include wireless sensor networks, relay networks, and distributed data centers. In our research, we design

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and develop both signal processing and communication algorithms to provide accurate status monitoring, improved communication throughput, andfaster, more precise control. Our research focuses on (1) optimal distributed inference algorithm development under resource constraints such ascommunication bandwidth; (2) joint spectrum sensing and allocation for cognitive radio networks to maximize the spectrum utility; and (3)addressing security issues in distributed systems.

Faculty: Hao Chen (ECE)

NEUROMORPHIC COMPUTINGSince their invention in the 1940s, computers have become an integral part of our daily lives enabling everything from a routine text message to weatherprediction that demands immense supercomputing resources. However, the processing power of today’s computers pales in comparison to that mostadvanced processor — the human brain. Technological progress now enables us to take up the challenge of developing a new kind of computingarchitecture that functions more like the brain. System architectures emulating biological learning mechanisms may lead to significant increases in speedat low power consumption suitable for use in many application areas. Three research groups bring their unique approaches to this area.

Neuromorphic ArchitecturesWe are investigating the integration of memristor arrays with CMOS transistor structures to implement a bio-inspired orneuromorphic design, where the memristors simulate synapses (weights), and CMOS structures form the neural somaor summing nodes. This new architecture forms the basis for an adaptive bio-inspired processor, which has applicationin a variety of fields.

Faculty: Maria Mitkova (ECE) and Nader Rafla (ECE)

Neuromorphic CircuitsThe goal of neuromorphic circuit research is to realize monolithically integrated bio-mimetic andbioinspired neuromorphic systems-on-a-chip (SoCs). The research approach is multidisciplinary,including research on developing chalcogenide-based memristive devices, neural network learning and mixed-signal circuitdesign, chip tape-out, and testing. We have developed neuromorphic circuit prototypes and are working to developneuromorphic systems and demonstrate algorithms. The systems use memristive devices fabricated at Boise State as weightsbetween neurons. The networks are capable of learning, computing, pattern recognition, and classification.

Faculty: Elisa Barney Smith (ECE), Kris Campbell (ECE), and Vishal Saxena (ECE)

Neuromorphic InterfacesThis research area aims to combine the unique properties and capabilities of neuromorphic architectures withnanoscale systems that interface directly with the environment. Creating mechanically flexible circuits that canconform to many di1erent surface topologies including that of biological tissue is a particular focus. Examplesinclude arrays of pressure and thermally sensitive devices for an artificial robotic skin, chemical sensor arrays(artificial olfaction), and electrode arrays for neural interfaces.

Faculty: Kurtis Cantley (ECE)

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PLASMA AND VACUUM ELECTRON DEVICESMicrowave Vacuum ElectronicsMicrowave vacuum electron devices are used in a variety of applications ranging from radar to satellite communications, particularly when usersneed high power density, high e4ciency, high reliability, and a long lifetime in harsh space environments. Such devices will be needed for manydecades to come. Our research focuses on new-generation devices which use gated vacuum field emission arrays as the electron source. Thesespatially addressable arrays can improve performance in crossed field amplifiers and magnetrons by controlling electron current injection. We arealso interested in electron hop funnels for use in microwave devices and for the study of secondary electron emission from dielectric surfaces.

Faculty: Jim Browning (ECE)

Plasma DevicesPlasma is an ionized gas, and as a fourth state of matter, o1ers unusual properties in many devices and applications. Wenumerically and experimentally study miniature ion thrusters, which can be used for satellite station keeping. Ion thrustersproduce small levels of thrust by accelerating ions using electric fields. They are ideal for long missions such as adjusting orbitsor deep space exploration. We also examine how to use microplasma discharges for medicine. Plasmas are gainingconsiderable interest for their ability to break down gases into free radicals and chemical species that can be used to treat skindiseases and wounds, and decontaminate surfaces.

Faculty: Jim Browning (ECE), Don Plumlee (MBE), and Ken Cornell (Chemistry)

ADDITIONAL RESEARCH AREASEnergy and Power SystemsWe do research in power and energy systems with a particular interest in environmentally sustainable electrical energy generation, transmission,distribution, and utilization. Our research in electrical energy generation includes developing new electric machine theories; parameter identificationof large synchronous generators using nonlinear identification methods; modeling and simulation of wind farms in power distribution systems; andpower electronic converter design for photovoltaic systems. We are also interested in integrating signal processing and communication technologiesfor the next-generation smart grid. Finally, our research in electrical energy utilization is currently focused on the FPGA implementation of highperformance electric drives.

Faculty: Said Ahmed-Zaid (ECE), Hao Chen (ECE), John Chiasson (ECE), Nader Rafla (ECE), Thad Welch (ECE), and John Gardner (MBE).

Mixed-Signal CircuitsRapid evolution of wireless broadband communication systems demands power-e4cient mixed-signal circuits with increasing signal bandwidth inmultiple frequency bands. In nano-CMOS technologies, where high-speed transistors have poor gain and increased device variability, developingenergy-e4cient analog-to-digital conversion is a primary challenge. We investigate novel architectures for future wireless networks (IEEE 802.11ac+)and software-defined radios, including continuous-time Delta-Sigma modulators with multi-step quantizers, direct RF-to-digital conversion, multi-band and cascaded modulators. We expect to achieve wideband conversion (>25 MHz) with a dynamic range >75 dB and a figure of merit<100fJ/bit. Also of interest are phase locked loops with a wide frequency range (900 MHz–5 GHz) and radio frequency front ends for Delta-Sigmaconverters.

Faculty: Vishal Saxena (ECE)

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Sensor SystemsOur research aims at designing improved sensors and sensor systems for applications such as monitoring airlinecabins, remote-monitoring of spent nuclear fuel canisters, wildlife tracking, and tracking of personal health data. Theamount of spent nuclear fuel kept in long-term storage is expected to double within the next decade, so our work isparticularly urgent and timely. Sensor systems consist of microprocessors, sensors, power management, and datastorage, supported by wired or wireless communications. We focus on improving circuit and firmware design inpower- and processing-limited environments, optimizing performance under environmental constraints such asintense heat and gamma radiation, and “harvesting” power from energy rich environments.

Faculty: Sin Ming Loo (ECE)

Wireless Sensor NetworksResearch in wireless sensor networks take a more precise look at one aspect of sensor system design, enablingscientists to acquire important data in environments and with a dimensionality that is di4cult if not impossible toacquire with traditional instrumentation. A primary focus for our team is on developing a novel data sharing system forwireless sensor networks to facilitate in-network collaborative processing of sensor data. This is important since shiftingdata processing to the sensor network itself can greatly reduce power requirements and latency issues intrinsic totraditional wireless sensor network data processing methods.

Faculty: Sin Ming Loo (ECE)

Remote Sensing of the EnvironmentOur research focuses on using LiDAR (light detection and ranging), hyperspectral, and multispectral remote sensing to characterize semiaridecosystems. We are particularly interested in developing methods for quantifying terrain (soil and vegetation) at multiple scales with ground,airborne, and satellite based LiDAR. Our studies also use hyperspectral imagery for improving ecological structure and function, and modeling.Research in our lab also focuses on the development of point cloud analysis tools, visualization of point cloud and hyperspectral data fusion, andunmanned aerial systems (UAS). https://bcal.boisestate.edu.

Faculty: Nancy Glenn (Geosciences)

Reconfigurable HardwareThis research focuses on the integration of processors, reconfigurable logic, and interfaces into a system to provide flexible high-speed solutions toapplications requiring complex computations, high-speed processing, and large resource utilization. We investigate the use of reconfigurationcapabilities of Systems on a Programmable Chip to create intelligent architectures for use in real-world application areas. Current research projectsinclude: 1) collective adaptive systems; 2) health diagnosis and monitoring systems; 3) study of cognitive processing; and 4) evolvable anddevelopmental hardware.

Faculty: Nader Rafla (ECE)

FOR MORE INFORMATIONContact Us. We provide a faculty contact name for each research area in this brochure. Please feel free to contact faculty directly. You can find theircontact information on our department website.

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