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

David Felton

Optimization and Evaluation of Physical Complementary Radar Waveforms

When & Where:


Nichols Hall, Room 129 (Apollo Auditorium)

Committee Members:

Shannon Blunt, Chair
Rachel Jarvis
Patrick McCormick
James Stiles
Zsolt Talata

Abstract

The RF spectrum is a precious, finite resource with ever-increasing demand. Consequently, the mandate to be a "good spectral neighbor" is in direct conflict with the requirements for high-performance sensing where correlation error is fundamentally limited. As such, matched-filter radar performance is often sidelobe-limited with estimation error being constrained by the time-bandwidth (TB) of the collective emission. The methods developed here seek to bridge this gap between idealized radar performance and practical utility via waveform design.    

Estimation error becomes more complex when employing pulse-agility. In doing so, range-sidelobe modulation (RSM) spreads energy across Doppler, rendering traditional methods ineffective. To address this, the gradient-based complementary-FM framework was developed to produce complementary sidelobe cancellation (CSC) after coherently combining subsets within a pulse-agile emission. In contrast to the majority of complementary signals, explored via phase-coding, these Comp-FM waveform subsets achieve CSC while preserving hardware-compatibility since they are FM (though design distortion is never completely avoided). Although Comp-FM addressed practicality via hardware amenability, CSC was localized to zero-Doppler. This work expands the Comp-FM notion to a Doppler-generalized (DG) framework, extending the cancellation condition to an arbitrary span. The same framework can likewise be employed to jointly optimize an entire coherent processing interval (CPI) to minimize RSM within the radar point-spread-function (PSF), thereby generalizing the notion of complementarity and introducing the potential for cognitive operation if sufficient scattering knowledge is available a-priori.          

Sensing with a single emitter is limited by self-inflicted error alone (e.g., clutter, sidelobes), while MIMO systems must additionally contend with the cross-responses from emitters operating concurrently (e.g., simultaneously, spatially proximate, in a shared spectrum), further degrading radar sensitivity. Now, total correlation error is dictated by the overlapping TB (i.e., how coincident are the signals) and number of operating emitters, compounding difficulty to estimate if left unaddressed. As such, the determination of "orthogonal waveforms" comprises a large portion of MIMO literature, though remains a phenomenological misnomer for pulsed emissions. Here, the notion of complementary-FM is applied to a multi-emitter context in which transmitter-amenable quasi-orthogonal subsets, occupying the same spectral band, are produced via a similar gradient-based approach. To further practicalize these MIMO-Comp-FM waveform subsets, the same "DG" approach described above, addressing the otherwise-default Doppler-induced degradation of complementary signals, is applied. In doing so, Doppler-independent separability and complementarity greatly improves estimation sensitivity for multi-emitter systems. 

This MIMO-Comp-FM framework is developed for standard matched filter processing. Coupling this framework with a "DG" form of the previously explored MIMO-MiCRFt is also investigated, illustrating the added benefit of pairing optimized subsets with similarly calibrated processing. 

Each of these methods is developed to address unique and increasingly complex sources of estimation error. All approaches are initially developed and evaluated via simulated analysis where ground-truth is known. Then, despite hardware-induced distortion being unavoidable, the MIMO-Comp-FM framework is confirmed via loopback measurements to preserve the majority of CSC that was observed in simulation. Finally, open-air demonstration of each approach validates practical utility on a radar system.


Hao Xuan

Toward an Integrated Computational Framework for Metagenomics: From Sequence Alignment to Automated Knowledge Discovery

When & Where:


Nichols Hall, Room 246 (Executive Conference Room)

Committee Members:

Cuncong Zhong, Chair
Fengjun Li
Suzanne Shontz
Hongyang Sun
Liang Xu

Abstract

Metagenomic sequencing has become a central paradigm for studying complex microbial communities and their interactions with the host, with emerging applications in clinical prediction and disease modeling. In this work, we first investigate two representative application scenarios: predicting immune checkpoint inhibitor response in non-small cell lung cancer using gut microbial signatures, and characterizing host–microbiome interactions in neonatal systems. The proposed reference-free neural network captures both compositional and functional signals without reliance on reference genomes, while the neonatal study demonstrates how environmental and genetic factors reshape microbial communities and how probiotic intervention can mitigate pathogen-induced immune activation.

These studies highlight both the promise and the inherent difficulty of metagenomic analysis: transforming raw sequencing data into clinically actionable insights remains an algorithmically fragmented and computationally intensive process. This challenge arises from two key limitations: the lack of a unified algorithmic foundation for sequence alignment and the absence of systematic approaches for selecting and organizing analytical tools. Motivated by these challenges, we present a unified computational framework for metagenomic analysis that integrates complementary algorithmic and systems-level solutions.

First, to resolve fragmentation at the alignment level, we develop the Versatile Alignment Toolkit (VAT), a unified algorithmic system for biological sequence alignment across diverse applications. VAT introduces an asymmetric multi-view k-mer indexing scheme that integrates multiple seeding strategies within a single architecture and enables dynamic seed-length adjustment via longest common prefix (LCP)–based inference without re-indexing. A flexible seed-chaining mechanism further supports diverse alignment scenarios, including collinear, rearranged, and split alignments. Combined with a hardware-efficient in-register bitonic sorting algorithm and dynamic index-loading strategy, VAT achieves high efficiency and broad applicability across read mapping, homology search, and whole-genome alignment. Second, to address the challenge of tool selection and pipeline construction, we develop SNAIL, a natural language processing system for automated recognition of bioinformatics tools from large-scale and rapidly growing scientific literature. By integrating XGBoost and Transformer-based models such as SciBERT, SNAIL enables structured extraction of analytical tools and supports automated, reproducible pipeline construction.

Together, this work establishes a unified framework that is grounded in real-world applications and addresses key bottlenecks in metagenomic analysis, enabling more efficient, scalable, and clinically actionable workflows.


Pramil Paudel

Learning Without Seeing: Privacy-Preserving and Adversarial Perspectives in Lensless Imaging

When & Where:


Eaton Hall, Room 2001B

Committee Members:

Fengjun Li, Chair
Alex Bardas
Bo Luo
Cuncong Zhong
Haiyang Chao

Abstract

Conventional computer vision relies on spatially resolved, human-interpretable images, which inherently expose sensitive information and raise privacy concerns. In this study, we explore an alternative paradigm based on lensless imaging, where scenes are captured as diffraction patterns governed by the point spread function (PSF). Although unintelligible to humans, these measurements encode structured, distributed information that remains useful for computational inference. 

We propose a unified framework for privacy-preserving vision that operates directly on lensless sensor measurements by leveraging their frequency-domain and phase-encoded properties. The framework is developed along two complementary directions. First, we enable reconstruction-free inference by exploiting the intrinsic obfuscation of lensless data. We show that semantic tasks such as classification can be performed directly on diffraction patterns using models tailored to non-local, phase-scrambled representations. We further design lensless-aware architectures and integrate them into practical pipelines, including a Swin Transformer-based steganographic framework (DiffHide) for secure and imperceptible information embedding. To assess robustness, we formalize adversarial threat models and develop defenses against learning-based reconstruction attacks, particularly GAN-driven inversion. Second, we investigate the limits of privacy by studying the reconstructability of lensless measurements without explicit knowledge of the forward model. We develop learning-based reconstruction methods that approximate the inverse mapping and analyze conditions under which sensitive information can be recovered. Our results demonstrate that lensless measurements enable effective vision tasks without reconstruction, while providing a principled framework to evaluate and mitigate privacy risks. 


Past Defense Notices

Dates

ALHANOOF ALTHNIAN

Evolutionary Learning of Goal-Driven Multi-Agent Communication

When & Where:


2001B Eaton Hall

Committee Members:

Arvin Agah, Chair
Prasad Kulkarni
Fengjun Li
Bo Luo
Elaina Sutley

Abstract

Multi-agent systems are a common paradigm for building distributed systems in different domains such as networking, health care, swarm sensing, robotics, and transportation. Systems are usually designed or adjusted in order to reflect the performance trade-offs made according to the characteristics of the mission requirement. 
Research has acknowledged the crucial role that communication plays in solving many performance problems. Conversely, research efforts that address communication decisions are usually designed and evaluated with respect to a single predetermined performance goal. This work introduces Goal-Driven Communication, where communication in a multi-agent system is determined according to flexible performance goals. 
This work proposes an evolutionary approach that, given a performance goal, produces a communication strategy that can improve a multi-agent system’s performance with respect to the desired goal. The evolved strategy determines what, when, and to whom the agents communicate. The proposed approach further enables tuning the trade-off between the performance goal and communication cost, to produce a strategy that achieves a good balance between the two objectives, according the system designer’s needs. 


JYOTI GANGARAJU

A Laboratory Manual for an Introduction to Communication Systems Course

When & Where:


2001B Eaton Hall

Committee Members:

Victor Frost, Chair
Dave Petr
Glenn Prescott


Abstract

Communication systems laboratory is a hands-on way to effectively visualize the real life applications of communication systems in its simplest form. Recently, hardware equipment such as spectrum analyzer, oscilloscope, and function generator were replaced by Pico Scope 6, a software based data analyzer. The Pico Scope 6 is a user friendly software which enables its users to capture and analyze analog and digital signals with a comparatively higher accuracy. Additionally, it is an economically viable solution, from both the procurement and maintenance stand point. The current effort focuses on developing a laboratory user manual, based on Pico Scope 6, for undergraduates of the Department of Electrical Engineering and Computer Science (EECS). The series of laboratory exercises developed follows the course outline of Introduction to Communication Systems – EECS 562. The expected outcomes of this laboratory manual is an improved understanding of analog modulations, digital modulations, and noise analysis of communication systems.


ARNESH BOSE

Two-Stage Operational Amplifier using MOSFET CMOS Technology

When & Where:


2001B Eaton Hall

Committee Members:

Yang Yi, Chair
Ron Hui
Jim Stiles


Abstract

The operational amplifier is perhaps the most useful integrated device in existence today. It is widely used in analogue computers simulation systems and in a variety of electronic applications such as amplification filtering, buffering and comparison of signed levels. In this design project, we use the operational amplifier for amplification. Two-stage opamp is one of the most commonly used opamp architectures. A two stage differential amplifier is designed with an objective of a minimum gain of 65 dB. The gain achieved is 74.6 dB and 71.4 MHz 3dB gain bandwidth, which is useful for medium frequency operations. The schematic circuit is constructed using Metal Oxide Semiconductor Field Effect Transistor and the technology used for the final layout is Complementary metal–oxide–semiconductor (CMOS) using Cadence.


ISHA KHADKA

Multi-Controller SDN for Fault-Tolerant Resilient Network

When & Where:


246 Nichols Hall

Committee Members:

James Sterbenz, Chair
Fengjun Li
Gary Minden


Abstract

Software Defined Networking (SDN) decouples the control or logical plane of a network from its physical/data plane thus enabling features such as centralized control, network programmability, virtualization, network application development, automation and more. However, SDN is still vulnerable to attacks and failures just like any other non-SDN network. The failure in SDN can be either a link or device failure. Controller is the central device, acting like the brain of a network, and its failure can propagate rapidly rendering the underlying data plane dysfunctional. The concept of Multi-Controller SDN uses redundancy as an effective method to ensure resilience and fault-tolerance in a Software-Defined Network. Multiple Controllers are connected in a cluster to form a physically distributed but logically centralized network. The backup controllers ensure resilience against failure, attack, disaster and other network disruptions. In this project, we implement multi-controller SDN and measure performance metrics such as high availability, reliability, latency, datastore persistency and failure recovery time in a clustered environment.


MD AMIMUL EHSAN

Enabling Technologies for Three-dimensional (3D) Integrated Circuits (ICs): Through Silicon Via (TSV) Modeling and Analysis

When & Where:


246 Nichols Hall

Committee Members:

Yang Yi, Chair
Chris Allen
Ron Hui
Lingjia Liu
Judy Wu

Abstract

Three-dimensional (3D) integrated circuits (ICs) offer a promising near-term solution for pushing beyond Moore’s Law because of their compatibility with current technology. Through silicon vias (TSVs) provide electrical connections that pass vertically through wafers or dies to generate high-performance interconnects, which allows for higher design densities through shortened connection lengths. In recent years, we have seen tremendous technological and economic progress in adoption of 3D ICs with TSVs for mainstream commercial use. 
Along with the need for low-cost and high-yield process technology, the successful application of TSV technology requires further optimization of the TSV electrical modeling and design. In the millimeter wave (mmW) frequency range, the root mean square (rms) height of the through silicon via (TSV) sidewall roughness is comparable to the skin depth and hence becomes a critical factor for TSV modeling and analysis. The impact of TSV sidewall roughness on electrical performance, such as the loss and impedance alteration in the mmW frequency range, is examined and analyzed. The second order small analytical perturbation method is applied to obtain a simple closed-form expression for the power absorption enhancement factor of the TSV. In this study, we propose an accurate and efficient electrical model for TSVs which considers the TSV sidewall roughness effect, the skin effect, and the metal oxide semiconductor (MOS) effect. The accuracy of the model is validated through a comparison of circuit model behavior for full wave electromagnetic field simulations up to 100 GHz. 
Another advanced neurophysiological computing system that can incorporate 3D integration could provide massive parallelism with fast and energy efficient links. While the 3D neuro-inspired system offers a fantastic level of integration, it becomes inordinately arduous for the designer to model, merely because of the innumerable interconnected elements. When a TSV array is utilized in a 3D neuromorphic system, crosstalk has a malefic effect upon the system’s signal to noise ratio; the result is an overall deterioration of system performance. To countervail the crosstalk, we propose a novel optimized TSV array pattern by applying the force directed optimization algorithm. 


ADAM PETZ

A Semantics for Attestation Protocols using Session Types in Coq

When & Where:


246 Nichols Hall

Committee Members:

Perry Alexander, Chair
Andy Gill
Prasad Kulkarni


Abstract

As our world becomes more connected, the average person must place more trust in cloud systems for everyday transactions. We rely on banks and credit card services to protect our money, hospitals to conceal and selectively disclose sensitive health information, and government agencies to protect our identity and uphold national security interests. However, establishing trust in remote systems is not a trivial task, especially in the diverse, distributed ecosystem of todays networked computers. Remote Attestation is a mechanism for establishing trust in a remotely running system where an appraiser requests information from a target that can be used to evaluate its operational state. The target responds with evidence providing configuration information, run-time measurements, and authenticity meta-evidence used by the appraiser to determine if it trusts the target system. For Remote Attestation to be applied broadly, we must have attestation protocols that perform operations on a collection of applications, each of which must be measured differently. Verifying that these protocols behave as expected and accomplish their diverse attestation goals is a unique challenge. An important first step is to understand the structural properties and execution patterns they share. In this thesis I present a semantic framework for attestation protocol execution within the Coq verification environment including a protocol representation based on Session Types, a dependently typed model of perfect cryptography, and an operational execution semantics. The expressive power of dependent types constrains the structure of protocols and supports precise claims about their behavior. If we view attestation protocols as programming language expressions, we can borrow from standard language semantics techniques to model their execution. The proof framework ensures desirable properties of protocol execution, such as progress and termination, that hold for all protocols. It also ensures properties of authenticity and secrecy for individual protocols.


RACHAD ATAT

Communicating over Internet Things: Security, Energy-Efficiency, Reliability and Low-Latency

When & Where:


250 Nichols Hall

Committee Members:

Lingjia Liu, Chair
Yang Yi
Shannon Blunt
Jim Rowland
David Nualart

Abstract

The Internet of Things (IoT) is expected to revolutionize the world through its myriad applications in health-care, public safety, environmental management, vehicular networks, industrial automation, etc. Some of the concepts related to IoT include Machine Type Communications (MTC), Low power Wireless Personal Area Networks (LoWPAN), wireless sensor networks (WSN) and Radio-Frequency Identification (RFID). Characterized by large amount of traffic with smart decision making with little or no human interaction, these different networks pose a set of challenges, among which security, energy, reliability and latency are the most important ones. First, the open wireless medium and the distributed nature of the system introduce eavesdropping, data fabrication and privacy violation threats. Second, the large number of IoT devices are expected to operate in a self-sustainable and self-sufficient manner without degrading system performance. That means energy efficiency is critical to prolong devices' lifetime. Third, many IoT applications require the information to be successfully transmitted in a reliable and timely manner, such as emergency response and health-care scenarios. To address these challenges, we propose low-complexity approaches by exploiting the physical layer and using stochastic geometry as a powerful tool to accurately model the spatial locations of ''things''. This helps provide a tractable analytical framework to provide solutions for the mentioned challenges of IoT.


OMAR BARI

Ensembles of Text and Time-Series Models for Automatic Generation of Financial Trading Signals

When & Where:


2001B Eaton Hall

Committee Members:

Arvin Agah, Chair
Joseph Evans
Andy Gill
Jerzy Grzymala-Busse
Sara Wilson

Abstract

Event Studies in finance have focused on traditional news headlines to assess the impact an event has on a traded company. The increased proliferation of news and information produced by social media content has disrupted this trend. Although researchers have begun to identify trading opportunities from social media platforms, such as Twitter, almost all techniques use a general sentiment from large collections of tweets. Though useful, general sentiment does not provide an opportunity to indicate specific events worthy of affecting stock prices.


AQSA PATEL

Interpretation of Radar Altimeter Waveforms using Ku-band Ultra-Wideband Altimeter Data

When & Where:


317 Nichols Hall

Committee Members:

Carl Leuschen, Chair
Prasad Kulkarni
Ron Hui
John Paden
David Braaten

Abstract

The surface-elevation of ice sheets and sea ice is currently measured using both satellite and airborne radar altimeters. These measurements are used for generating mass balance estimates of ice sheets and thickness estimates of sea ice. However, due to the penetration of the altimeter signal into the snow there is ambiguity between the surface tracking point and the actual surface location which produces errors in the surface elevation measurement. In order to address how the penetration of the signal affects the shape of the return waveform, it is important to study the effect sub-surface scattering and seasonal variations in properties of snow have on the return waveform to correctly interpret the satellite radar altimeter data. To address this problem, an ultra-wide bandwidth Ku-band radar altimeter was developed at the Center for Remote Sensing of Ice Sheets (CReSIS). The Ku-band altimeter operates over the frequency range of 12 to 18 GHz providing very fine resolution to measure ice surface and resolve the sub-surface features of the snow. It is designed to encompass the frequency band of satellite radar altimeters. The data from Ku-band altimeter can be used to simulate satellite radar altimeter data, and these simulated waveforms can help us understand the effect of signal penetration and sub-surface scattering on low bandwidth satellite altimeter returns. The extensive dataset collected as a part of the Operation Ice Bridge (OIB) campaign can be used to interpret satellite radar altimeter data over surfaces with varying snow conditions. The goal of this research is to use waveform modeling and data inter-comparisons of full and reduced bandwidth data products from Ku-band radar altimeter to investigate the effect of signal penetration and snow conditions on surface tracking using threshold and waveform fitting retracking algorithms to improve the retrieval of surface elevation from satellite radar altimeters.


VAISHNAVI YADALAM

Real Time Video Streaming over a Multihop Ad Hoc Network

When & Where:


1 Eaton Hall

Committee Members:

Aveek Dutta, Chair
Victor Frost
Richard Wang


Abstract

High rate data transmission is very common in cellular and wireless local area networks. It is achievable because of its wired backbone where only the first or the last hop is wireless, commonly known as wireless “last-mile” link. With this type of infrastructure network, it is not surprising to achieve the desired performance of wirelessly-transmitted video. However, the current challenge is to transmit an enunciated and a high quality real time video over multiple wireless hops in an ad hoc network. The performance of multiple wireless hops to transmit a high quality video is limited by data rate, bandwidth of wireless channel and interference from adjacent channels. These factors constrain the applications for a wireless multihop network but are fundamental to military tactical network solutions. The project addresses and studies the effect of packet sensitivity, latency, bitrate and bandwidth on the quality of video for line of sight and non-line of sight test scenarios. It aims to achieve the best visual user experience at the receiver end on transmission over multiple wireless hops. Further, the project provides an algorithm for placement of drones in sub-terrain environment to stream real time videos for border surveillance to monitor and detect unauthorized activity.