The standard methods to authenticate a computer or a network user, which typically occur once at the initial log-in, suffer from a variety of vulnerabilities such as masquerading and potential system compromise. An effective solution to this one-time authentication problem is the continuous authentication using behavioral biometrics. 

In the last decade, bioinformatics data has been accumulated at an unprecedented rate, thanks to the advancement in sequencing technologies. Such rapid development poses both challenges and promising research topics. In this dissertation, the authors propose a series of associative pattern recognition algorithms in biological regulation studies.

Speaker age and gender classification is one of the most challenging problems in speech processing. Recently with developing technologies, identifying a speaker age and gender has become a necessity for speaker verification and identification systems such as identifying suspects in criminal cases, improving human-machine interaction, and adapting music for awaiting people queue.

Cardiac magnetic resonance imaging (CMRI) has been proven to be a valuable source of diagnostic information concerning heart health. One application, myocardial blood flow (MBF) quantification using first-pass contrast-enhanced myocardial perfusion, has aided the detection of coronary artery disease and provides an accurate evaluation of myocardial ischemia, an identifier of coronary artery stenosis. 

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.

Sensor networks deployed in high-latency environments such as underwater acoustic and satellite channels find critical applications in disaster prevention and tactical surveillance. The sensors in these networks have limited energy reserves.

Author: Song-Wen Huang  (University at Buffalo, the State University of New York) Advisor: Dimitris A. Pados
Radio frequency and underwater acoustic communications have grown rapidly in environmental monitoring, telecommunications, offshore oil exploration, and surveillance applications. Nonetheless, signals may still suffer from harsh challenges in wireless fading channels for high attenuation, multipath effect, and Doppler spread. 

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem.

Advisor: Caylor, Kelly K.

Smallholder farms dominate in many parts of the world, including Sub-Saharan Africa. These systems are characterized by small, heterogeneous, and often indistinct field patterns, requiring a specialized methodology to map agricultural landcover. In this thesis, they developed a benchmark labeled data set of high-resolution satellite imagery of agricultural fields in South Africa. 

Non-invasive side-channel attacks (SCA) are powerful attacks which can be used to obtain the secret key in a cryptographic circuit in feasible time without the need for expensive measurement equipment. Power analysis attacks (PAA) are a type of SCA that exploit the correlation between the leaked power consumption information and processed/stored data. Differential power analysis (DPA) and leakage power analysis (LPA) attacks are two types of PAA that exploit different characteristics of the side-channel leakage profile.