Gita Sukthankar

Gita Sukthankar
University of Central Florida | UCF · Department of Electrical Engineering & Computer Science

Ph.D. Robotics Carnegie Mellon University

About

188
Publications
43,720
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1,774
Citations

Publications

Publications (188)
Article
In this study, we explore the future of work by examining differences in productivity when teams are composed of only humans or both humans and machine agents. Our objective was to characterize the similarities and differences between human and human–machine teams as they work to coordinate across their specialized roles. This form of research is i...
Article
Good communication is indubitably the foundation of effective teamwork. Over time teams develop their own communication styles and often exhibit entrainment, a conversational phenomena in which humans synchronize their linguistic choices. Conversely, teams may experience conflict due to either personal incompatibility or differing viewpoints. We ta...
Chapter
This paper explains the design of a social network analysis framework, developed under DARPA’s SocialSim program, with novel architecture that models human emotional, cognitive, and social factors. Our framework is both theory and data-driven, and utilizes domain expertise. Our simulation effort helps understanding how information flows and evolves...
Article
Many of the most popular intelligent training systems, including driving and flight simulators, generate user time series data. This paper presents a comparison of representation options for two different student modeling problems: 1) early failure prediction and 2) classifying student activities. Data for this analysis was gathered from pilots exe...
Preprint
The ever-increasing complexity of modern software engineering projects makes the usage of automated assistants imperative. Bots can be used to complete repetitive tasks during development and testing, as well as promoting communication between team members through issue reporting and documentation. Although the ultimate aim of these automated assis...
Preprint
Full-text available
Good communication is indubitably the foundation of effective teamwork. Over time teams develop their own communication styles and often exhibit entrainment, a conversational phenomena in which humans synchronize their linguistic choices. This paper examines the problem of predicting team performance from embeddings learned from multiparty dialogue...
Article
As the complexity of aircraft cockpit operations increases, training effectiveness must be improved, and learning accelerated. Virtual reality (VR) training is increasingly offered as a method for improving training efficacy given its ability to provide a rich sensory experience during learning. This paper describes a study examining how training e...
Preprint
Full-text available
Social coding platforms, such as GitHub, serve as laboratories for studying collaborative problem solving in open source software development; a key feature is their ability to support issue reporting which is used by teams to discuss tasks and ideas. Analyzing the dialogue between team members, as expressed in issue comments, can yield important i...
Preprint
Full-text available
Popularity and engagement are the currencies of social media platforms, serving as powerful reinforcement mechanisms to keep users online. Social coding platforms such as GitHub serve a dual purpose: they are practical tools that facilitate asynchronous, distributed collaborations between software developers while also supporting passive social med...
Preprint
While there are many machine learning methods to classify and cluster sequences, they fail to explain what are the differences in groups of sequences that make them distinguishable. Although in some cases having a black box model is sufficient, there is a need for increased explainability in research areas focused on human behaviors. For example, p...
Preprint
Full-text available
Our goal is to understand the characteristics of high-performing teams on GitHub. Towards this end, we collect data from software repositories and evaluate teams by examining differences in productivity. Our study focuses on the team formation phase, the first six months after repository creation. To better understand team activity, we clustered re...
Chapter
This paper investigates the problem of predicting student flight performance in a training simulation from multimodal features, including flight controls, visual attention, and knowledge acquisition tests. This is a key component of developing next generation training simulations that can optimize the usage of student training time. Two types of su...
Chapter
Open source software development platforms are natural laboratories for studying the diffusion of innovation across human populations, enabling us to better understand what motivates people to adopt new ideas. For example, GitHub, a software repository and collaborative development tool built on the Git distributed version control system, provides...
Article
Full-text available
This paper explores the value of weak-ties in classifying academic literature with the use of graph convolutional neural networks. Our experiments look at the results of treating weak-ties as if they were strong-ties to determine if that assumption improves performance. This is done by applying the methodological framework of the Simplified Graph C...
Preprint
Full-text available
This paper explains the design of a social network analysis framework, developed under DARPA's SocialSim program, with novel architecture that models human emotional, cognitive and social factors. Our framework is both theory and data-driven, and utilizes domain expertise. Our simulation effort helps in understanding how information flows and evolv...
Article
The aim of our research is to forecast the propagation of information related to cybersecurity threats and software vulnerabilities on social coding platforms such as GitHub. Users on social coding platforms exhibit repetitive behavior patterns that can be leveraged to predict trends in network evolution. These patterns exhibit greater consistency...
Article
Full-text available
Burst analysis and prediction is a fundamental problem in social network analysis, since user activities have been shown to have an intrinsically bursty nature. Bursts may also be a signal of topics that are of growing real-world interest. Since bursts can be caused by exogenous phenomena and are indicative of burgeoning popularity, leveraging cros...
Preprint
Full-text available
A physical selfie stick extends the user's reach, enabling the creation of personal photos that include more of the background scene. Conversely a quadcopter can capture photos at distances unattainable for the human, but teloperating a quadcopter to a good viewpoint is a non-trivial task. This paper presents a natural interface for quadcopter phot...
Conference Paper
Full-text available
One of the advantages of teaching robots by demonstration is that it can be more intuitive for users to demonstrate rather than describe the desired robot behavior. However, when the human demonstrates the task through an interface, the training data may inadvertently acquire artifacts unique to the interface, not the desired execution of the task....
Chapter
Social norms have been demonstrated to strongly affect people's health choices, yet they are often not included in health models due to the complex interdependencies of reasoning about norm adoption over a large population. This article introduces two agent‐based modeling frameworks designed explicitly for reasoning about the influence of social no...
Preprint
Full-text available
Object detection models based on convolutional neural networks (CNNs) demonstrate impressive performance when trained on large-scale labeled datasets. While a generic object detector trained on such a dataset performs adequately in applications where the input data is similar to user photographs, the detector performs poorly on small objects, parti...
Preprint
In this paper we introduce the concept of network semantic segmentation for social network analysis. We consider the GitHub social coding network which has been a center of attention for both researchers and software developers. Network semantic segmentation describes the process of associating each user with a class label such as a topic of intere...
Preprint
Full-text available
Social coding platforms, such as GitHub, can serve as natural laboratories for studying the diffusion of innovation through tracking the pattern of code adoption by programmers. This paper focuses on the problem of predicting the popularity of software repositories over time; our aim is to forecast the time series of popularity-related events (code...
Preprint
Full-text available
One of the most challenging coordination problems in artificial intelligence is to achieve successful collaboration across large-scale heterogeneous systems that include Robots, Agents, and People (RAP). In the best case, these RAP systems are potentially capable of leveraging the strengths of the individual entities to achieve complex distributed...
Preprint
Full-text available
Drones are a versatile platform for both amateur and professional photographers, enabling them to capture photos that are impossible to shoot with ground-based cameras. However, when guided by inexperienced pilots, they have a high incidence of collisions, crashes, and poorly framed photographs. This paper presents an intelligent user interface for...
Chapter
Full-text available
Agent-based models are a powerful tool for predicting population level behaviors; however their performance can be sensitive to the initial simulation conditions. This paper introduces a procedure for leveraging large datasets to initialize agent-based simulations in which the population is abstracted into a set of archetypes. We show that these ar...
Article
Cambridge Core - Computing and Society - Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju
Chapter
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Chapter
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Article
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Chapter
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Chapter
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Chapter
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Chapter
Social Interactions in Virtual Worlds - edited by Kiran Lakkaraju July 2018
Article
Full-text available
Many interesting real-world systems are represented as complex networks with multiple types of interactions and complicated dependency structures between layers. These interactions can be encoded as having a valence with positive links marking interactions such as trust and friendship and negative links denoting distrust or hostility. Extracting in...
Conference Paper
Full-text available
One of the advantages of teaching robots by demonstration is that it can be more intuitive for users to demonstrate rather than describe the desired robot behavior. However, when the human demonstrates the task through an interface, the training data may inadvertently acquire artifacts unique to the interface, not the desired execution of the task....
Article
Full-text available
This paper presents a practical approach towards implementing pathfinding algorithms on real-world and low-cost non- commercial hardware platforms. While using robotics simulation platforms as a test-bed for our algorithms we easily overlook real- world exogenous problems that are developed by external factors. Such problems involve robot wheel sli...
Poster
Full-text available
Although sources of social media data abound, companies are often reluctant to share data, even anonymized or aggregated, for fear of violating user privacy. This paper introduces an approach for learning the probability of link formation from data using generative adversarial neural networks. In our generative adversarial network (GAN) paradigm, o...
Conference Paper
Many interesting real-world systems are represented as complex networks with multiple types of interactions and complicated dependency structures between layers. These interactions can be encoded as having a valence with positive links marking interactions such as trust and friendship and negative links denoting distrust or hostility. Extracting in...
Book
This book compiles the most visionary papers from 10 workshops held at the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017. The 15 full papers presented in this volume were carefully reviewed and selected for inclusion in this volume. They deal with novel ideas proposing a ch...
Book
This book features a selection of best papers from 13 workshops held at the International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2017, held in Sao Paulo, Brazil, in May 2017. The 17 full papers presented in this volume were carefully reviewed and selected for inclusion in this volume. They cover specific topics, both theoret...
Article
Full-text available
This report summarizes the 39 workshops held as part of the 2016 International Joint Conference on Artificial Intelligence, held in New York from July 9-11.
Conference Paper
Networks extracted from social media platforms frequently include multiple types of links that dynamically change over time; these links can be used to represent dyadic interactions such as economic transactions, communications, and shared activities. Organizing this data into a dynamic multiplex network, where each layer is composed of a single ed...
Conference Paper
Full-text available
Article
Full-text available
Networks extracted from social media platforms frequently include multiple types of links that dynamically change over time; these links can be used to represent dyadic interactions such as economic transactions, communications, and shared activities. Organizing this data into a dynamic multiplex network, where each layer is composed of a single ed...
Article
Full-text available
Most real-world social networks are inherently dynamic, composed of communities that are constantly changing in membership. To track these evolving communities, we need dynamic community detection techniques. This article evaluates the performance of a set of game theoretic approaches for identifying communities in dynamic networks. Our method, D-G...
Conference Paper
Full-text available
Reinforcement learning (RL) is a popular choice for solving robotic control problems. However, applying RL techniques to controlling humanoid robots with high degrees of freedom remains problematic due to the difficulty of acquiring sufficient training data. The problem is compounded by the fact that most real-world problems involve continuous stat...
Conference Paper
Full-text available
The aim of link prediction is to forecast connections that are most likely to occur in the future, based on examples of previously observed links. A key insight is that it is useful to explicitly model network dynamics, how frequently links are created or destroyed when doing link prediction. In this paper, we introduce a new supervised link predic...
Article
This editorial to the summer 2015 AI Magazine introduces the special-issue articles on architectures for activity recognition and context-aware computing.
Conference Paper
Full-text available
Massively-multiplayer online games (MMOGs) can serve as a unique laboratory for studying large-scale human behaviors. However, one question that often arises is whether the observed behavior is specific to the game world and its winning conditions. This paper studies the nature of conflict and communication across two game worlds that have differen...
Article
Full-text available
Mobile phone crowdsourcing is a powerful tool for many types of distributed sensing problems. However, a central issue with this type of system is that it relies on user contributed data, which may be sparse or erroneous. This paper describes our experiences developing a mobile phone crowdsourcing app, Kpark, for monitoring parking availability on...
Conference Paper
Full-text available
In many cases, creating long-term solutions to sustainability issues requires not only innovative technology but also large-scale public adoption of the proposed solutions. Social simulations are a valuable but underutilized tool that can help public policy researchers understand when sustainable practices are likely to make the delicate transition...
Article
Full-text available
This paper tackles the problem of designing an effective user interface for a multi-robot delivery system, composed of robots with wheeled bases and two 3 DOF arms. There are several proven paradigms for increasing the efficacy of human-robot interaction: 1) multimodal interfaces in which the user controls the robots using voice and gesture; 2) con...