Event Archive

Join us for a poster fair to celebrate the results of over 100 talented Duke students who participated on projects in computer science, data science, and software development this summer through summer projects in Computer Science, Data+, and Code+.

Reasoning about 3D objects is one of the most critical perception problems robots face; outside of navigation, most interactions between a robot and its environment are object-centric. Object-centric robot perception has long relied on maintaining an explicit database of 3D object models with the assumption that encountered objects will be exact copies of entries in the database; however, as robots move into unstructured environments such as human homes, the variation of encountered objects increases and maintaining an explicit object database becomes infeasible.

We present a system for summarization and interactive exploration of high-valued aggregate query answers to make a large set of possible answers more informative to the user. Our system outputs a set of clusters on the high-valued query answers showing their common properties such that the clusters are diverse as much as possible to avoid repeating information, and cover a certain number of top original answers as indicated by the user.

Data collection has become a staple of both our digital and “off-line” activities. Government agencies, medical institutions, Internet companies, and academic institutions are among the main actors that collect and store users’ data. Analysis and sharing of this data is paramount in our increasingly data-driven world.
 

Abstract DNA based nanostructures and devices are becoming ubiquitous in nanotechnology with rapid advancements in theory and experiments in DNA self- assembly which have led to a myriad of DNA nanodevices. However, the modeling methods used by researchers in the field for design and analysis of DNA nanos- tructures and nanodevices have not progressed at the same rate. Specifically, there does not exist a formal system that can capture the spectrum of the most frequently intended chemical reactions on DNA nanostructures and nanodevices which have branched and pseudo-knotted structures.

We present work on the initial stages of a type-safe deep learning library, written in the \Idris{} programming language. In particular, we provide several modules---each meant to exist as distinct domain-specific languages---that correspond to the different levels of abstraction involved in specifying neural network architectures. In particular, we present three such modules. The first is an implementation of any higher-order composition function, which we call a flow.

The Computer Science ceremony will be held at the Durham Convention Center following the main University Commencement Ceremony at Wallace Wade Stadium.
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We consider a participatory budgeting problem in which each voter submits a proposal for how to divide a single divisible resource (such as money or time) among several possible alternatives (such as public projects or activities) and these proposals must be aggregated into a single consensus division.

The era of information explosion has opened up an unprecedented opportunity to study the social, political, financial and medical events described in natural language text. While the past decades have seen significant progress in deep learning and natural language processing (NLP), it is still extremely difficult to analyze textual data at the event-level, e.g., to understand what is going on, what is the cause and impact, and how things will unfold over time.

Data-driven decision making plays a dominant role across all domains, from health, business, government, to sports. These data-driven decisions are often ad-hoc and resource-intensive: a bank has to compare and analyze all users, sporting events might use previous events to estimate an acceptable ticket sales rate. In this dissertation, I describe efficient methods for optimizing complex analytic queries.

Computational protein design is a transformative field with exciting prospects for advancing both basic science and translational medical research. New algorithms blend discrete and continuous mathematics to address the challenges of creating designer proteins. I will discuss recent progress in this area and some interesting open problems.

When do you allow for the evolution of existing software versus throwing it all away and starting over? This is a question that all software developers will face many times during their career, in both small and in large ways. Too often there is a strong urge to start over with a clean slate, getting rid of all the cruft that has built up over the years.  Unfortunately the decision to succumb to this urge is taken with limited guidance, or clear reasoning.

Once upon a time, Computer Systems was a broad field encompassing everything from hardware to software. The incredible growth and success that our field has experienced over the past half a century has had the side effect of transforming systems into a constellation of siloed fields. I'm going to make the case that we should return to a broad interpretation of systems, undertake bolder, higher risk projects, and be intentional about how we interact with other fields. I'll support the case with examples of several research projects that embody this approach.

The Project Showcase is held annually by the Computer Science Department to highlight independent or team-based research and project work done during the academic year. The best projects in each category will be decided by faculty judges and announced towards the end of the event. Come explore the impressive efforts of our students and their advisors!

The “what ifs?” or ability to explore counterfactuals is central to the study of causal inference. Randomized control and A/B testing provides an approach to address this when counterfactuals can be experimented simultaneously. However, in a large number of scenarios such as policy evaluation, this is not feasible: we can’t have two Massachusetts, one having Gun Control and the other not at the same time, so that we can evaluate the impact of Gun Control on crime rate!

Though the sequence of the genome is essentially fixed, within each cell it exists in a complex and changing state, determined in part by the dynamic binding of proteins. These proteins—including nucleosomes, transcription factors (TFs), polymerases, and other complexes—define the living chromatin state of the genome. Understanding genome-wide how the dynamics of chromatin interact with the dynamics of transcriptional regulation remains a fundamental research problem.

The rapid development of Cloud computing and enterprise IT demand modern data centers to be less expensive and more efficient. With the improvement in software design such as concurrency control, caching and lease, we also need to exploit emerging network connection technologies to reduce some overhead. Remote Direct Memory Access (RDMA), a networking technology originally used in High-Performance Computing (HPC), is a trending technology for inter-node connection.

This project attempted to uncover hidden patterns in nanocomposite data. Natural Language Processing technique was used to analyze material science papers in order to discover the relationships between different material science terminologies. Also, this project tried to find the relationship between the glass-transition temperature (Tg) and other available features and the relationship between the shape parameter and other variables such as matrix type. Different models were used in this project such as LASSO regression, Support Vector Machine with Gaussian kernel and Decision Tree.

Recently convolutional neural networks (CNNs) have become popular for image recognition tasks due to their excellent performance compared to other earlier approaches. One limitation of CNNs however is that they require substantial quantities of hand-labeled training imagery compared to other models before they achieve their performance advantage. In this circumstance, multi-task learning (MTL) has been proposed, in which a single CNN is trained to perform several recognition tasks simultaneously.