Colloquia Announcements


Thursday, 14th December 2017, 2:00pm, UB230

Mrs. Hande Kucuk-McGinty
Department of Computer Science
University of Miami

will present

Knowledge Acquisition and Representation Methodology (KNARM) and Its Applications

Technological advancements in many fields have led to huge increases in data production, including data volume, diversity, and the speed at which new data is becoming available. In accordance with this, there is a lack of conformity in the ways data is interpreted. In-depth analyses - making use of various data types and data sources, and extracting knowledge - has become a more daunting task. This is especially the case in life-sciences where simplification and flattening of diverse data types often leads to incorrect predictions.Effective applications of big data approaches in the life sciences require better, knowledge-based, semantic models that are suitable as a framework for 'big data' integration, while avoiding overly extreme simplification, such as reducing various biological data types to the 'gene' level. A huge hurdle in developing such semantic knowledge models, or ontologies, is the knowledge acquisition bottleneck.Automated methods are still very limited and significant human expertise is required. In this research, we describe a methodology to systematize this knowledge acquisition and representation challenge, termed KNowledge Acquisition and Representation Methodology (KNARM). We also present how KNARM was applied on three ontologies - BioAssay Ontology (BAO), LINCS FramEwork Ontology (LIFE) and Drug Target Ontology (DTO) - built for three different projects - BioAssay Ontology, Library of Integrated Network-Based Cellular Signatures (LINCS) and Illuminating the Druggable Genome (IDG) -, and how they work together in complex queries.

This is a Department of Computer Science PhD Proposal.


Wednesday, 13th December 2017, 5:00pm, UB506

Dr. Paige Morgan

will present

Can We Make the Web Smarter? An Intro to Linked Open Data and the Semantic Web

In 2001, Sir Tim Berners-Lee coined the phrase "semantic web" to describe an idea that he thought would revolutionize the way that the web worked: "a common framework allow[ing] data to be shared and reused across application, enterprise, and community boundaries." Since the idea of the semantic web was introduced, many people (both developers and non-developers) have made great progress towards realizing the vision of the semantic web - but we have also had to confront challenges involving technical infrastructure, maintenance, and authority.  This talk will introduce the concepts of the semantic web, linked open data, and non-relational databases; and will examine specific current and potential applications, including Wikipedia, DBpedia, and a range of cultural heritage applications. Using these specific cases, the talk will also explore several questions and problems that the idea of the semantic web raises, and possible answers.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 6th December 2017, 5:00pm, UB506

Dr. Alessandro Warth

will present

Towards a Better Programming Experience - In the Classroom and Beyond

Over the past few years, researchers have shared compelling visions of better, more helpful programming environments - e.g., my colleagues Bret Victor's "Inventing on Principle" (2012) and Sean McDirmid's "A Live Programming Experience" (2015) - but these visions have yet to impact the way we program today. The fact is there are substantial design and engineering challenges that prevent us from turning these researchers' compelling demos into practical and robust programming environments.  My group at YC Research has been making progress on the Programming Experience (PX) problem. Our strategy is to first restrict the scope of the programming tools we create, then use what we've learned to branch out towards truly general programming environments. So far we have created a programming environment for implementing programming languages (the Ohm Editor), a new language that enables end-users to create mobile social apps (Chorus), and several other tools that aim to provide a better PX in the classroom, for teachers as well as students. This talk will focus on the latter: I will show some of the educational programming tools we have created, discuss their preliminary results, and outline our plans for next steps.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 29th November 2017, 5:00pm, UB506

Daniel Messinger
Professor of Psychology
University of Miami

will present

Sensing Typical and Atypical Development:
What can Objective Measurement and Modeling of Interaction Tell Us?

New sensing technologies and measurement algorithms are providing insight into the social and emotional development of typically developing children and those with communication disorders such as autism and deafness. Computer vision and pattern recognition tools have provided insights into emotional expression and the structure of early social interaction. Modeling of input from Kinect sensors is providing objective measurements of early attachment. Automated analysis of classroom movement and vocal interaction is suggesting how language development takes place among peers. The talk will consider the strengths, challenges, and future of objective measurement and modeling of child behavior.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 15th November 2017, 5:00pm, UB506

Amin Sarafraz
Center for Computational Science
University of Miami

will present

Photogrammetry: from Obscurity to Prominence

The past few years have seen the emergence of exciting new techniques that produce 3D models from digital images. The underlying science for creating such models is called Photogrammetry and has been used for decades by surveying and civil engineers for mapping and documentation purposes. One of the main factors in unleashing the potentials of Photogrammetry and bringing it into prominence is the increase in computing power. I will give a brief overview of Photogrammetry and some of its applications fueled by ever increasing computing power.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 15th November 2017, 2:00pm, UB330G

Mr. Joseph Masterjohn
Department of Computer Science
University of Miami

will present

Encasement: A Robust Method for Finding Intersections of Semi-algebraic Curves

One of the fundamental concepts in computational geometry is deducing the combinatorial structure, or interactions, of a group of static geometric objects. In two dimensions, the objects in question include, but are not limited to: points, lines, line segments, polygons, and non-linear curves. There are various properties of interest describing a collection of such objects; examples include: distances, adjacencies, and most notably, intersections of these objects. Well studied, robust, and highly efficient algorithms exist for linear geometry and parametric curves. Problems involving non-linear, implicit, and high-dimensional objects however are an active area of research. Algebraic curves and algebraic surfaces arise frequently in numerous applications: GIS software, CAD software, VLSI design, computational chemistry and biology, dynamics, and robotics. We present a novel algorithm for finding all intersections of two semi-algebraic curves in a convex polygonal region, and describe its prospective analog in 3 dimensions. We "encase" the curves in the convex region by repeatedly splitting the region until each cell contains at most two intersecting segments, thus detecting and isolating all of the intersections. The advantage of using encasement is that the running time is proportional to the size of the convex region when it is small and yet comparable to existing techniques when it is large.

This is a Department of Computer Science Masters Thesis defence.


Friday, 3rd November 2017, 11:00am, Ungar 230

Dr. Francis J. Pelletier
Department of Philosophy
University of Albertta

will present

How to Make Some Many-Valued Logics be Useful

In 1976 Nuel Belnap published a (relatively) well-known paper "A Useful Four-Valued Logic: How a Computer Should Think" in which he argued for a four-valued logic that could accommodate knowledge bases that were presented with conflicting data, or with incomplete data, about a query in some field of knowledge. More of the formal background was presented in Michael Dunn's "Intuitive Semantics for First Degree Entailment" that same year. The logic became known as FDE. A serious problem with FDE (and some related logics) is that you can't do any reasoning with them!! They do not contain a conditional connective that would allow for a normal modus ponens inference, nor from any other rule of inference that is equivalent to modus ponens, such as (unit) resolution and the like. The present talk proposes a conditional connective for FDE that will work, and furthermore has interesting (and surprising) extensions to certain 3-valued logics, such as Lukasiewicz-3, Kleene-3, RM3, and "the logic of paradox". This is joint work with Allen Hazen and (I hope) Geoff Sutcliffe.

This is another in the Department of Computer Science Seminar series.


Wednesday, 1st November 2017, 5:00pm, UB506

Dr. Adrian Reynolds
University of Miami

will present

Learning How to Learn: Study Strategies Every Student Should Know

Preparing our students to be innovators and leaders in their respective disciplines not only requires the development of subject matter expertise, but, equally important, the use of self-regulated learning strategies to solve complex problems of global significance.  Regrettably, however, our education system has been structured around the teaching of content knowledge at the expense of teaching self-regulated active learning strategies that help to facilitate content mastery. Advising students to "take control of their own learning", as well-intentioned as it might be, might cause more harm than good if they're not taught how to do so. If you're a college student who can identify with any aspect of the following case, this seminar is for you:

I consider myself a dedicated, hardworking student, but I somehow still struggle to perform to my full potential. When I study I mostly read the lecture slides and my notes multiple times so I can memorize key concepts. I sometimes study with a group and we quiz each other, but there's always that one person who's either behind or ahead of everyone else: This makes group work really difficult. I also create study guides which are more detailed, organized versions of my notes, but I rarely have time to go back and review all of them. I usually start reviewing a week before the test: If I begin reviewing any earlier, I'll forget the material. To stay organized, I usually keep a to-do list, but I hardly use a study schedule. I'm putting in the hours, but I feel like my grades don't reflect that.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 25th October 2017, 5:00pm, UB506

Dr. Dilip Sarkar
Department of Computer Science
University of Miami

will present

Threats and Vulnerabilities in Cyberspace

Individual users, small businesses, large enterprises, governments, national and international infrastructures depend on cyberspace for regular operations. However, cyberspace and their users have vulnerabilities, which malicious actors are exploiting. In particular, malicious actors use /mal/icous soft/wares /(malwares), including viruses, worms, Trojan horses, backdoors, rootkits, adware, key loggers, spywares, ransomewares, and botnets. After discussing common methods used to distribute malwares, we will discuss bots and botnets, because they are the biggest threat in the cyberspace. In the past they have inflicted most harm to cyberspace infrastructures as well as cyberspace users; in the future they are expected to do so again and again. Also, we will discuss phishing and social engineering techniques.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 18th October 2017, 5:00pm, UB506

Dr. Alberto Cairo
School of Communication
University of Miami

will present

Visualization Design: It's Not Just About the Data

When designing charts, graphs, or maps to inform the public, scientists often overlook critical features such as visual elegance, typography, color, hierarchy, and composition. They do it because they think that visual design is just about "beautifying" graphics. This talk will teach you to reconsider that thought.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 11th October 2017, 5:00pm, UB506

Dr. Timothy Norris
Research Data Scientist
University of Miami

will present

Participatory Research, Information Science and GIS Method

Maps and geospatial information play an increasingly prominent role in the everyday lives of citizens in most "western" nations. Scholars also recognize that "the power of maps" stretches back in history to the origins of modern cartographic practice in the 15th and 16th centuries. Recent research shows that the nascent "data revolution" disrupts traditional power relations found in the visualization of geospatial information which can present opportunities for alternative mappings. One such alternative includes participatory mapping in which residents of a certain region or area become the cartographers who draw maps of their own territory. Some claim that participatory mapping can empower communities and increase democratic governance while others insist that the power of the map always lies with those who have the right to use force to legitimize the specific visualization of data. In this seminar, several participatory mapping projects will be presented and given the critique from a framework that includes critical cartography and on-the-ground experience with participatory mapping. The conclusion suggests that lessons learned from the participatory mapping experience can also be applied to allied data-driven good governance initiatives.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 4th October 2017, 5:00pm, UB506

Dr. Gang Ren
Center for Computational Science
University of Miami

will present

Content-Based Multimedia Timeline Analysis Employing
Sequential Pattern Discovery and Alignment

Multimedia timeline analysis explores the temporal patterns from multiple signal dimensions of multimedia content and employs these temporal patterns as a computational representation for modeling high-level multimedia concepts and objects, such as narrative structures, genres, emotion, and audience response attributes. An example of multimedia timeline analysis is the temporal arrangement and synchronization of the video color patterns and the audio event density in the content production processes, where these multimedia elements and their interactions render the narrative tension to enhance the storyline and persuasive effectiveness. We present a computational framework for multimedia timeline analysis based on sequential pattern discovery and alignment algorithms. This framework extracts video and audio signal features from the multimedia content and employs sequential pattern discovery tools to explore and interpret the temporal patterns in the signal feature timelines at hierarchical time resolutions. Our proposed framework enables the ensemble analyses of large multimedia datasets or more refined characterization of complex narrative dynamics, which are impossible or inefficient for conventional manual analysis workflows. Empirical studies and subjective rating experiments based on a commercial advertisement dataset are also included to demonstrate the usage of our proposed tools and to validate the cognitive relevance of the analysis results.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 27th September 2017, 5:00pm, UB506

Dr. Le Liu
Department of Computer Science
University of Miami

will present

Effective Visualizations of the Uncertainty in Hurricanes

The National Hurricane Center track forecast cone is the most widely adopted visualization for enhancing viewers' understanding of hurricane forecasts. However, current research has experimentally shown that the cone easily leads to misconceptions of the uncertainty included, and difficulties of interpreting the crucial time-specific information. The research reported here focuses on mitigating these limitations by developing ensemble visualizations. The research began by developing a technique that generates and smoothly interpolates robust statistics from an ensemble of hurricane predictions, thus creating visualizations that inherently include the spatial uncertainty by displaying three levels of positional storm strike risk at a specific point in time. In addition, this research develops time-specific visualizations depicting spatial information based on a sampling technique that selects a small, representative subset from an ensemble of points. It also allows depictions of such important storm characteristics as size and intensity. Further, this research generalizes the representative sampling framework to process ensembles of forecast tracks, selecting a subset of tracks accurately preserving the original distributions of available storm characteristics and keeping appropriately defined spatial separations. This framework supports an additional hurricane visualization portraying prediction uncertainties implicitly by directly showing the members of the subset without the visual clutter. An ongoing cognitive studies suggests that these visualizations enhance viewers' ability to understand the predictions because they are potentially interpreted more as uncertainty distributions.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 6th September 2017, 5:00pm, UB506

Dr. Paige Morgan
Digital Humanities Librarian
University of Miami

will present

Can We Make the Web Smarter? An Intro to Linked Open Data and the Semantic Web

In 2001, Sir Tim Berners-Lee coined the phrase "semantic web" to describe an idea that he thought would revolutionize the way that the web worked: "a common framework allow[ing] data to be shared and reused across application, enterprise, and community boundaries." Since the idea of the semantic web was introduced, many people (both developers and non-developers) have made great progress towards realizing the vision of the semantic web -- but we have also had to confront challenges involving technical infrastructure, maintenance, and authority.  This talk will introduce the concepts of the semantic web, linked open data, and non-relational databases; and will examine specific current and potential applications, including Wikipedia, DBpedia, and a range of cultural heritage applications. Using these specific cases, the talk will also explore several questions and problems that the idea of the semantic web raises, and possible answers.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 30th August 2017, 5:00pm, UB506

Dr. Jonathan Poterjoy
NOAA Atlantic Oceanographic and Atmospheric Laboratory

will present

Nonparametric Data Assimilation for Numerical Weather Prediction and Research

Numerical weather prediction presents one of the largest applications of high-performance computing in science, owing to the enormous state dimension and the demand for timely forecasts. Weather forecasting also contains several intrinsic limitations related to the observability of atmospheric motions, nonlinearity in the underlying system dynamics, and the ability of numerical models to faithfully simulate the physical processes important for forecasting a given weather event. Therefore, a probabilistic framework is required.  Quantifying probabilities for weather prediction is an exercise in Bayesian filtering, where a probability distribution for the model state is updated sequentially to reflect measurements collected from ground stations, aircrafts, satellites, and other sources. In geoscience, this process is called data assimilation.  In this talk, I will introduce the basic strategies currently adopted for data assimilation in operational weather forecasting. These strategies rely on Gaussian assumptions for the underlying error distributions, which is often suboptimal when the model dynamics are nonlinear, when measurements relate nonlinearly to model state variables, and when observation errors are non-Gaussian. I will then introduce a new nonparametric data assimilation method that has potential for nonlinear/non-Gaussian problems encountered in weather models. Benefits of this method will be discussed using applications where convectively driven atmospheric motions determine the evolution of the dynamical system (i.e., severe thunderstorms and squall lines).

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Wednesday, 23rd August 2017, 5:00pm, UB506

Dr. Erik Noonburg
Department of Biological Sciences
Florida Atlantic University

will present

Modeling Animal Foraging Behavior as a Gtate-dependent Game

Behavioral ecology often applies game theoretic models to understand animal decision-making. However, when decisions depend on an animal's state, analytic solutions for the game theoretic equilibrium are generally impossible. I will present two case studies in which I use reinforcement learning techniques to find approximate solutions. The case studies consider animals' choices of foraging locations in the face of competition, with application to wildlife management.

This is another in the Department of Computer Science Pizza Seminar Series. Refreshments will be served at 4:30 p.m. in the reception area of the 3rd floor of Ungar.


Previous Colloquia Announcements