Ph.D. Presentations

Modern scientific studies increasingly rely on complex datasets exhibiting spatial and temporal dependence, particularly in social, environmental, and climate applications. This dissertation develops statistical models and computational methods for analyzing such data, with an emphasis on capturing dependence structures, nonlinear dynamics, and uncertainty quantification. A spatial deep learning framework is developed to extend classical geostatistical […]

Most optimization problems face the challenge of computing an optimum solution requiring superpolynomial time. In particular, they are classified as NP-hard problems that have no polynomial-time algorithm to date. Instead, computer scientists turn to find an approximate solution and create numerous elegant algorithms. However, in the modern era, computational environments have changed drastically, and we […]

Research on fault-tolerance protocols for approximate Byzantine agreement (ABA) has largely focused on ensuring that distributed processes remain consistent despite fewer than 1/3 faulty processes. Yet in many real systems, consistency is only useful when it enables processes to make accurate decisions from replicated, noisy, and potentially adversarially corrupted data relative to an ideal fault-free […]

Pattern counting is a fundamental problem in computer science with applications in many domains. For a fixed small pattern H, we are given a large graph G and we are asked to count the number of subgraphs or homomorphisms (edge-preserving maps) of H in G. For practical applications where the input graph can be very […]

Sequencing technologies have revolutionized our understanding of biology, yet many existing methods require fragmentation of DNA or RNA, fundamentally limiting our ability to study these molecules in their native, intact forms. Long-read sequencing overcomes this constraint by enabling the sequencing of long, single-molecule native DNA and RNA, providing simultaneous access to both sequence and base […]

Centromeric DNA is critical for accurate chromosome segregation and genome stability, but due to its repetitive nature, it was only recently fully included in a human reference. Rapid evolution and sequence diversity in these regions limit the utility of one reference sequence, however. Integrating centromeric and pericentromeric satellite DNA – which together constitute over 5% […]

Every year, tens of thousands of tons of plaster-based materials are used in restoration and conservation applications, many of which are derived from non-renewable sources and discarded at the end of their service life. Here, we introduce a biodegradable, bio-derived composite based on chitosan and calcium carbonate that is composed of simple, widely available constituents […]

This work addresses improvements in branch prediction mechanism to support high perfor- mance processors. The state of the art aims to balance the prediction latency and prediction accuracy using multi level correcting predictors . Prior published work focusses on scalar designs and prediction accuracy improvement for hard to predict branches employing tailor made, non generic […]

Modern datacenter CPUs lose 25–66% of execution cycles to instruction-delivery stalls. This bottleneck persists, despite the recent trend towards accelerators and GPUs, as there is continuing demand by applications that only execute on CPUs. Two workload classes dominate today’s datacenter execution cycles: hyperscale server software (databases, build systems, and content stores), whose large instruction footprints […]

This dissertation investigates how neuromorphic and brain-inspired principles can guide the design of efficient neural language architectures. It addresses two central limitations of modern Transformer-based language models: memory growth with […]