Defense Notices


All students and faculty are welcome to attend the final defense of EECS graduate students completing their M.S. or Ph.D. degrees. Defense notices for M.S./Ph.D. presentations for this year and several previous years are listed below in reverse chronological order.

Students who are nearing the completion of their M.S./Ph.D. research should schedule their final defenses through the EECS graduate office at least THREE WEEKS PRIOR to their presentation date so that there is time to complete the degree requirements check, and post the presentation announcement online.

Upcoming Defense Notices

Md Mashfiq Rizvee

Hierarchical Probabilistic Architectures for Scalable Biometric and Electronic Authentication in Secure Surveillance Ecosystems

When & Where:


Eaton Hall, Room 2001B

Committee Members:

Sumaiya Shomaji, Chair
Tamzidul Hoque
David Johnson
Hongyang Sun
Alexandra Kondyli

Abstract

Secure and scalable authentication has become a primary requirement in modern digital ecosystems, where both human biometrics and electronic identities must be verified under noise, large population growth and resource constraints. Existing approaches often struggle to simultaneously provide storage efficiency, dynamic updates and strong authentication reliability. The proposed work advances a unified probabilistic framework based on Hierarchical Bloom Filter (HBF) architectures to address these limitations across biometric and hardware domains. The first contribution establishes the Dynamic Hierarchical Bloom Filter (DHBF) as a noise-tolerant and dynamically updatable authentication structure for large-scale biometrics. Unlike static Bloom-based systems that require reconstruction upon updates, DHBF supports enrollment, querying, insertion and deletion without structural rebuild. Experimental evaluation on 30,000 facial biometric templates demonstrates 100% enrollment and query accuracy, including robust acceptance of noisy biometric inputs while maintaining correct rejection of non-enrolled identities. These results validate that hierarchical probabilistic encoding can preserve both scalability and authentication reliability in practical deployments. Building on this foundation, Bio-BloomChain integrates DHBF into a blockchain-based smart contract framework to provide tamper-evident, privacy-preserving biometric lifecycle management. The system stores only hashed and non-invertible commitments on-chain while maintaining probabilistic verification logic within the contract layer. Large-scale evaluation again reports 100% enrollment, insertion, query and deletion accuracy across 30,000 templates, therefore, solving the existing problem of blockchains being able to authenticate noisy data. Moreover, the deployment analysis shows that execution on Polygon zkEVM reduces operational costs by several orders of magnitude compared to Ethereum, therefore, bringing enrollment and deletion costs below $0.001 per operation which demonstrate the feasibility of scalable blockchain biometric authentication in practice. Finally, the hierarchical probabilistic paradigm is extended to electronic hardware authentication through the Persistent Hierarchical Bloom Filter (PHBF). Applied to electronic fingerprints derived from physical unclonable functions (PUFs), PHBF demonstrates robust authentication under environmental variations such as temperature-induced noise. Experimental results show zero-error operation at the selected decision threshold and substantial system-level improvements as well as over 10^5 faster query processing and significantly reduced storage requirements compared to large scale tracking.


Fatima Al-Shaikhli

Optical Measurements Leveraging Coherent Fiber Optics Transceivers

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Rongqing Hui, Chair
Shannon Blunt
Shima Fardad
Alessandro Salandrino
Judy Wu

Abstract

Recent advancements in optical technology are invaluable in a variety of fields, extending far beyond high-speed communications. These innovations enable optical sensing, which plays a critical role across diverse applications, from medical diagnostics to infrastructure monitoring and automotive systems. This research focuses on leveraging commercially available coherent optical transceivers to develop novel measurement techniques to extract detailed information about optical fiber characteristics, as well as target information. Through this approach, we aim to enable accurate and fast assessments of fiber performance and integrity, while exploring the potential for utilizing existing optical communication networks to enhance fiber characterization capabilities. This goal is investigated through three distinct projects: (1) fiber type characterization based on intensity-modulated electrostriction response, (2) coherent Light Detection and Ranging (LiDAR) system for target range and velocity detection through different waveform design, including experimental validation of frequency modulation continuous wave (FMCW) implementations and theoretical analysis of orthogonal frequency division multiplexing (OFDM) based approaches and (3) birefringence measurements using a coherent Polarization-sensitive Optical Frequency Domain Reflectometer (P-OFDR) system.

Electrostriction in an optical fiber is introduced by interaction between the forward propagated optical signal and the acoustic standing waves in the radial direction resonating between the center of the core and the cladding circumference of the fiber. The response of electrostriction is dependent on fiber parameters, especially the mode field radius. We demonstrated a novel technique of identifying fiber types through the measurement of intensity modulation induced electrostriction response. As the spectral envelope of electrostriction induced propagation loss is anti-symmetrical, the signal to noise ratio can be significantly increased by subtracting the measured spectrum from its complex conjugate. We show that if the field distribution of the fiber propagation mode is Gaussian, the envelope of the electrostriction-induced loss spectrum closely follows a Maxwellian distribution whose shape can be specified by a single parameter determined by the mode field radius.        

We also present a self-homodyne FMCW LiDAR system based on a coherent receiver. By using the same linearly chirped waveform for both the LiDAR signal and the local oscillator, the self-homodyne coherent receiver performs frequency de-chirping directly in the photodiodes, significantly simplifying signal processing. As a result, the required receiver bandwidth is much lower than the chirping bandwidth of the signal. Simultaneous multi-target of range and velocity detection is demonstrated experimentally. Furthermore, we explore the use of commercially available coherent transceivers for joint communication and sensing using OFDM waveforms.

In addition, we demonstrate a P-OFDR system utilizing a digital coherent optical transceiver to generate a linear frequency chirp via carrier-suppressed single-sideband modulation. This method ensures linearity in chirping and phase continuity of the optical carrier. The coherent homodyne receiver, incorporating both polarization and phase diversity, recovers the state of polarization (SOP) of the backscattered optical signal along the fiber, mixing with an identically chirped local oscillator. With a spatial resolution of approximately 5 mm, a 26 GHz chirping bandwidth, and a 200 us measurement time, this system enables precise birefringence measurements. By employing three mutually orthogonal SOPs of the launched optical signal, we measure relative birefringence vectors along the fiber.


Past Defense Notices

Dates

Gordon Ariho

Multipass SAR Processing for Ice Sheet Vertical Velocity and Tomography Measurements and Application of Reduced Rank MMSE to Spectrally Efficient Radar Design

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Jim Stiles, Chair
John Paden (Co-Chair)
Shannon Blunt
Carl Leuschen
Emily Arnold

Abstract

First Topic: Ice sheets impact sea-level change and hence their response to climatic variations needs to be continually monitored and studied. We propose to apply multipass differential interferometric synthetic aperture radar (DInSAR) techniques to data from the Multichannel Coherent Radar Depth Sounder (MCoRDS) to measure the vertical displacement of englacial layers within an ice sheet. DInSAR’s accuracy is usually on the order of a small fraction of the wavelength (e.g. millimeter to centimeter precision is common) in monitoring ground displacement along the radar line of sight (LOS).  In the case of ice sheet internal layers, vertical displacement is estimated by compensating for the spatial baseline using precise trajectory information and estimates of the cross-track layer slope from direction of arrival analysis. Preliminary results from a high accumulation region near Camp Century in northwest Greenland and Summit Station in central Greenland are presented here. We propose to extend this work by implementing a maximum likelihood estimator that jointly estimates the vertical velocity, the cross-track internal layer slope, and the unknown baseline error due to GPS and INS errors. The multipass algorithm will be applied to additional flights from the decade long NASA Operation IceBridge airborne mission that flew MCoRDS on many repeated flight tracks. We also propose to improve the accuracy of tomographic swaths produced from multipass measurements and investigate the possibility to use focusing matrices to improve wideband tomographic processing.

Second Topic: With the increased demand for bandwidth-hungry applications in the telecommunications industry, radar applications can no longer enjoy the generous frequency allocations within the UHF band. Spectral efficiency, if achievable, leads to the freeing of portions of the radar bandwidth to facilitate spectrum sharing between radar and other wireless systems. A decrease in bandwidth leads to worse radar resolution. In certain scenarios, reduced resolution is acceptable, and bandwidth may be compromised for spectral efficiency. An iterative reduced rank MMSE algorithm based on marginal Fisher information is proposed and investigated to minimize the loss of resolution with the tradeoff of degraded side-lobe performance. The algorithm is applied to the radar measurement model with simulated range profiles and performance results discussed.


Kishanram Kaje

Complex Field Modulation in Direct Detection Systems

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Rongqing Hui, Chair
Christopher Allen
Victor Frost
Erik Perrins
Jie Han

Abstract

 Even though fiber optics communication is providing a high bandwidth channel to achieve high speed data transmission, there is still a need for higher spectral efficiency, faster data processing speeds while reduced resource requirements due to ever increasing data and media traffic. Various multilevel modulation and demodulation techniques are used to improve spectral efficiency. Although, spectral efficiency is improved, there are other challenges that arise while doing so such as requirement for high speed electronics, receiver sensitivity, chromatic dispersion, operational flexibility etc. Here, we investigate complex high speed field modulation techniques in direct detection systems to improve spectral efficiency while focusing to reduce resources required for implementation, compensating for linear and nonlinear impairments in fiber optics communication systems.

We first demonstrated a digital-analog hybrid subcarrier multiplexing (SCM) technique which can reduce the requirement of high speed electronics such as ADC and DAC, while providing wideband capability, high spectral efficiency, operational flexibility and controllable data-rate granularity.

With conventional Quadrature Phase Shift Keying (QPSK), to achieve maximum spectral efficiency, we need high spectral efficient Nyquist filters which takes high FPGA resources for digital signal processing (DSP). Hence, we investigated Quadrature Duobinary (QDB) modulation as a solution to reduce the FPGA resources required for DSP while achieving spectral efficiency of 2bits/s/Hz. Currently we are investigating all analog single sideband (SSB) complex field modulated direct detection system. Here, we are trying to achieve higher spectral efficiency by using QDB modulation scheme in comparison to QPSK while avoiding signal-signal beat interference (SSBI) by providing a guard-band based approach.

Another topic we investigated, both through simulation and experiments, is a way to compensate for nonlinearities generated by semiconductor optical amplifiers (SOA) when operated in gain saturation in a field modulated direct detection systems. We successfully, compensated for the SOA nonlinearities in the presence of fiber chromatic dispersion, which was post compensated using electronic dispersion compensation after restoring the phase information of the received signal using Kramers-Kronig receiver.


Theresa Moore

Array Manifold Calibration for Multichannel SAR Sounders

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

James Stiles, Chair
John Paden (Co-Chair)
Shannon Blunt
Carl Leuschen
Leigh Stearns

Abstract

Multichannel synthetic aperture radar (SAR) sounders with cross-track antenna arrays map ice sheet basal morphology in three dimensions with a single pass using tomography.  The tomographic ice-sheet imaging method leverages parametric direction-finding techniques like the Maximum Likelihood Estimator and the Multiple Signal Classification algorithm to resolve scattering interfaces in elevation.  These techniques have received considerable attention because of their potential to exceed the Rayleigh resolution limit of the receive array under certain conditions.  This performance is predicated on having perfect knowledge of the frequency-dependent response of the array to directional sources, referred to as the array manifold.  Even modest amounts of mismatch between the assumed and actual manifold model degrade the accuracy of parametric angle estimators and erode their sought-after superresolution potential.

 

Array manifold calibration refers to the step in the array processor of refining our representation of the directional array-response vectors by accounting for factors such as mutual coupling, geometric uncertainties, and channel-to-channel gain imbalances.  Pilot calibration requires measuring the in-situ array over its field of view and storing the manifold in a look-up-table.  Alternatively, the array transfer function may be modeled parametrically to levy an estimation framework for characterizing mismatch.  Parametric calibration theory for sensor position perturbations has been established for several decades.  However, there remains a marked disconnect between the signal processing and antennas communities regarding how to include mutual coupling within the parametric framework.  To date, literature lacks validated studies that address parameterization of the embedded element patterns for direction-finding arrays.

 

A manifold calibration methodology is proposed for an airborne, multichannel ice-penetrating SAR.  The methodology departs from conventional approaches by extracting calibration targets from SAR imagery of well-understood terrain to empirically characterize the directional responses of the integrated array's embedded element patterns.  This work presents a Maximum Likelihood Estimator for nonlinear parameters common across disjoint calibration sets that has the potential to improve the accuracy of our estimated geometric uncertainties by increasing the total Fisher information in our observations.  The investigation contributes to specific gaps in array signal processing and remote sensing literature by treating the unique challenge of calibrating in-situ arrays used in direction-finding applications.


Dung Viet Nguyen

Particle Swarm Deep Reinforcement Learning for Base Station Optimization in Urban Areas

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Taejoon Kim, Chair
Morteza Hashemi
Heechul Yun


Abstract

Densifying the network by deploying many small cells has attracted significant interests from wireless industries for exploring its potential to facilitating the proposed many data-intensive use cases in fifth-generation (5G) networks. While such efforts are essential, there are gaps in fundamental research and practical deployment of small cells. It is clear that increased interference from adjacent cells, called intercell interference, is the major limiting factor.  In order to address this issue, each base station's parameters should be properly controlled to mitigate the intercell interference. We call the task of designing the base station's parameters the base station optimization (BSO) problem in this work. Due to the large numbers of small cells and mobile users distributed over the network, solving BSO by precisely modeling the network conditions is almost infeasible. One of the popular approaches that has attracted many researchers recently is a data-based framework called machine learning (ML). While supervised ML is prevalent, it requires pre-labeled off-line data that are not available in many wireless scenarios. Unlike supervised ML, reinforcement learning (RL) can handle this situation because it is based on designing a good policy to find the best exploration-\&-exploitation tradeoff without the pre-labeled training dataset. Thus, in this work, we present a new approach to the problem of BSO, based on the application of deep reinforcement learning (DRL) to enhance the quality of service (QoS) experienced by mobile users. To speed up the exploration of DRL, we employ particle swarm optimization (PSO), which shows improved QoS and convergence compared to conventional DRL.


Dalton Hahn

Delving Into DevOps: Examining the Security Posture of State-of-Art Service Mesh Tools

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Alex Bardas, Chair
Drew Davidson
Fengjun Li


Abstract

Explosion in the use of containers and a shift in software engineering design from monolithic applications into a microservice model has driven a need for software solutions that can manage the deployment and networking of microservices at enterprise-level scale. Service meshes have emerged as a promising solution to the microservice eruption that enterprise software is currently experiencing. This work examines service meshes from the perspective of security solutions offered within the tools and how the available security mechanisms impact the original goals of service meshes. As part of this study, we propose a relevant threat model to the service mesh domain and consider two different levels of configuration of these tools. The first configuration we study is the “idealized” configuration; one in which a system administrator has deep knowledge and the ability to properly configure and enable all available security mechanisms within a service mesh. The second configuration scenario is that of the default configuration deployment of service meshes. Through this work, we consider a range of adversarial approaches and scenarios that comprehensively cover the available attack surface of service meshes. Our experimental results show a distinct lack in security support of service meshes when deployed under default configurations, and additionally, in many idealized scenarios studied, it is possible for attackers to achieve some of their adversarial goals, presenting tempting targets to attackers.


Calen Carabajal

Development of Compact UWB Transmit Receive Modules and Filters on Liquid Crystal Polymer for Radar

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Carl Leuschen, Chair
Fernando Rodriguez-Morales (Co-Chair)
Christopher Allen


Abstract

Microwave and mm-wave radars have been used extensively for remote sensing applications, and ultra-wideband (UWB) radars have provided particular utility in geophysical research due to their ability to resolve narrowly-spaced targets or media interface levels. With increased availability of unmanned aerial vehicles (UAS) and expanded application of microwave radars into other realms requiring portability, miniaturization of radar systems is a crucial goal. This thesis presents the design and development of various microwave components for a compact, airborne snow-probing radar with multi-gigahertz bandwidth and cm-scale vertical resolution.

 
First, a set of UWB, compact transmit and receive modules with custom power sequencing circuits is presented. These modules were rapid-prototyped as an initial step toward the miniaturization of the radar’s front-end, using a combination of custom and COTS circuits. The transmitter and receiver modules operate in the 2–18 GHz range. Laboratory and field tests are discussed, demonstrating performance that is comparable to previous, connectorized implementations of the system, while accomplishing a 5:1 size reduction.

 

Next, a set of miniaturized band-pass and low-pass filters is developed and demonstrated. This work addressed the lack of COTS circuits with adequate performance in a sufficiently small form factor that is compatible with the planar integration required in a multi-chip module.

 

The filters presented here were designed for manufacture on a multi-layer liquid crystal polymer (LCP) substrate. A detailed trade study to assess the effects of potential manufacturing tolerances is presented. A framework for the automated creation of panelized design variations was developed using CAD tools. Thirty-two design variations with two different types of launches (microstrip and grounded co-planar waveguide) were successfully simulated, fabricated and tested, showing good electrical performance both as individual filters and cascaded to offer outstanding out-of-band rejection. The size of the new filters is 1 cm x 1 cm x 150 µm, a vertical reduction of over 90% and a reduction of total cascaded length by over 80%.


Kunal Karnik

Augment drone GPS telemetry data onto its Optical Flow lines

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Andy Gill, Chair
Drew Davidson
Prasad Kulkarni


Abstract

Optical flow is the apparent displacement of objects, surfaces and edges in a visual scene caused because of the relative motion between an observer and the scene. This apparent displacement (parallax) is used to render optical flow lines for such objects which hold invaluable information about their motion. In this research, we apply this technique to study a video file. We will locate pixels of objects with strong optical flow displacements. Which will enable us to identify an aerial multirotor craft (drone) from possible object pixels. Further we will not only mark the drones path using optical flow lines, but we will also add value to the video file by augmenting the drone’s 3D Telemetry data onto its optical flow lines.


Guojun Xiong

Distributed Filter Design and Power Allocation for Small-Cell MIMO Network

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Taejoon Kim, Chair
Morteza Hashemi
Erik Perrins


Abstract

The deluge of wireless data traffic catalyzed by the growing number of data-intensive devices has motivated the deployment of small-cell in fifth-generation (5G) networks. A primary challenge for deploying dense small-cell networks comes from the lack of practical techniques that efficiently handle the increased network interference at a low cost. This has aroused considerable interest in the distributed precoder/combiner coordination techniques that leverage the channel reciprocity, while relying on the local channel state information (CSI) available at each communication end. In this project, a distributed approach is proposed to the problem of signal-to-interference-plus-noise-ratio (SINR)-guaranteed power minimization (SGPM) for multicell multiuser (MCMU) multiple-input multiple-output (MIMO) systems. Unlike prior SGPM approaches, the technique is based on solving necessary and sufficient optimality conditions, which are derived by decomposing the original problem into forward and backward (FB) subproblems, while ensuring the strong duality of each subproblems. The proposed distributed SGPM algorithm makes use of FB adaptation and Jacobi recursion for iterative filter design and power allocation, respectively, which guarantees target SINR performance as well as its convergence to a stationary point. Simulation results illustrate the enhanced power efficiency with the performance guarantees of the proposed method compared to the existing distributed techniques.


Jason Baxter

An FPGA Implementation of Carrier Phase and Symbol Timing Synchronization for 16-APSK

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Erik Perrins, Chair
Taejoon Kim
Carl Leuschen


Abstract

Proper synchronization between a transmitter and receiver, in terms of carrier phase and symbol timing, is critical for reliable communication. Carrier phase synchronization is related to the frequency translation hardware, where perfect synchronization means that the local oscillators of the transmitter’s upconverter and receiver’s downconverter are aligned in phase and frequency. Timing synchronization is related to the analog-to-digital converter in the receiver, where perfect synchronization means that samples of the received signal are taken at transmitted symbol times. Perfect synchronization is unlikely in practical systems for a number of reasons, including hardware limitations and the independence of the transmitter and receiver. This thesis explores an FPGA implementation of a PLL-based carrier phase and symbol timing synchronization subsystem as part of a 16-APSK aeronautical telemetry receiver. The theory behind this subsystem is presented, and the hardware implementation of each component is described. Results demonstrate successful demodulation of a test signal, and system performance is shown to be comparable to double-precision floating point simulations in terms of error vector magnitude, synchronization lock time, and BER.


Adam Petz

An Infrastructure for Faithful Execution of Remote Attestation Protocols

When & Where:


Zoom Meeting, please contact jgrisafe@ku.edu for link

Committee Members:

Perry Alexander, Chair
Drew Davidson
Andy Gill
Prasad Kulkarni
Emily Witt

Abstract

Security decisions often rely on trust.  An emerging technology for gaining trust in a remote computing system is remote attestation.  Remote attestation is the activity of making a claim about properties of a target by supplying evidence to an appraiser over a network.  Although many existing approaches to remote attestation wisely adopt a layered architecture–where the bottom layers measure layers above–the dependencies between components remain static and measurement orderings fixed.  Further, they are often restricted to a specialized embedded platform, or only perform shallow measurements on a component of interest without considering the trustworthiness of its context or the attestation mechanism itself.  For modern computing environments with diverse topologies, we can no longer fix a target architecture any more than we can fix a protocol to measure that architecture.

Copland is a domain-specific language and formal framework that provides a vocabulary for specifying the goals of layered attestation protocols.  It remains configurable by measurement capability, participants, and platform topology, yet provides a precise reference semantics that characterizes system measurement events and evidence handling; a foundation for comparing protocol alternatives.  The aim of this work is to refine the Copland semantics to a more fine-grained notion of attestation manager execution–a high-privilege thread of control responsible for invoking attestation services and bundling evidence results.  This refinement consists of two cooperating components called the Copland Compiler and the Attestation Virtual Machine (AVM).  The Copland Compiler translates a Copland specification into a sequence of primitive attestation instructions to be executed in the AVM.  These components are implemented as functional programs in the Coq proof assistant and proved correct with respect to the Copland reference semantics.  This formal connection is critical in order to trust that protocol specifications are faithfully carried out by the attestation manger implementation.  We also explore synthesis of appraisal routines that leverage the same formally verified infrastructure to interpret evidence generated by Copland protocols and make trust decisions.