Talal Rahwan

Talal Rahwan
New York University Abu Dhabi · Computer Science

PhD in Computer Science

About

99
Publications
15,985
Reads
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2,531
Citations
Citations since 2016
46 Research Items
1680 Citations
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20162017201820192020202120220100200300400
20162017201820192020202120220100200300400
Introduction
Talal Rahwan is an Associate Professor of Computer Science at New York University Abu Dhabi, UAE. He received his Ph.D. in Computer Science in 2007 from The University of Southampton, UK. His Ph.D. thesis earned him the British Computer Society's Distinguished Dissertation award, which annually recognizes the most outstanding Ph.D. thesis in the UK in Computer Science. He was selected by the IEEE Computer Society as one of AI’s 10 to Watch, which recognizes the 10 most promising, young Artificial Intelligence (AI) researchers in the world. His work appeared in major academic journals, including Nature Communications, Nature Human Behaviour, and Artificial Intelligence Journal (AIJ). His research interests include: Computational Social Science, Artificial Intelligence, and Graph Theory.
Additional affiliations
December 2018 - present
New York University Abu Dhabi
Position
  • Professor (Associate)
November 2013 - present
Masdar Institute
Position
  • Professor (Assistant)
December 2006 - November 2013
University of Southampton
Position
  • Research Associate

Publications

Publications (99)
Article
Full-text available
Recent breakthroughs in machine learning and big data analysis are allowing our online activities to be scrutinized at an unprecedented scale, and our private information to be inferred without our consent or knowledge. Here, we focus on algorithms designed to infer the opinions of Twitter users towards a growing number of topics, and consider the...
Article
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Influencing others through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, opinions, or viruses, identifying the diffusion source (i.e., the person that initiated it) is a problem that has attracted much research interest. Nevertheless, existing literature has ignored the possibility that...
Preprint
Full-text available
Academic publishing is the principal medium of documenting and disseminating scientific discoveries. At the heart of its daily operations are the editorial boards. Despite their activities and recruitment often being opaque to outside observers, they play a crucial role in promoting fair evaluations and gender parity. Literature on gender inequalit...
Article
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Social network analysis tools can infer various attributes just by scrutinizing one's connections. Several researchers have studied the problem faced by an evader whose goal is to strategically rewire their social connections in order to mislead such tools, thereby concealing their private attributes. However, to date this literature has only consi...
Article
Centrality measures are the most commonly advocated social network analysis tools for identifying leaders of covert organizations. While the literature has predominantly focused on studying the effectiveness of existing centrality measures or developing new ones, we study the problem from the opposite perspective, by focusing on how a group of lead...
Article
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Machine learning techniques are increasingly gaining attention due to their widespread use in various disciplines across academia and industry. Despite their tremendous success, many such techniques suffer from the “black-box” problem, which refers to situations where the data analyst is unable to explain why such techniques arrive at certain decis...
Preprint
Social network analysis tools can infer various attributes just by scrutinizing one's connections. Several researchers have studied the problem faced by an evader whose goal is to strategically rewire their social connections in order to mislead such tools, thereby concealing their private attributes. However, to date, this literature has only cons...
Article
Full-text available
Disinformation continues to raise concerns due to its increasing threat to society. Nevertheless, a threat of a disinformation-based attack on critical infrastructure is often overlooked. Here, we consider urban traffic networks and focus on fake information that manipulates drivers’ decisions to create congestion at a city scale. Specifically, we...
Preprint
Influencing (and being influenced by) others indirectly through social networks is fundamental to all human societies. Whether this happens through the diffusion of rumors, viruses, opinions, or know-how, finding the source is of persistent interest to people and an algorithmic challenge of much current research interest. However, no study has cons...
Preprint
Among the most fundamental tools for social network analysis are centrality measures, which quantify the importance of every node in the network. This centrality analysis typically disregards the possibility that the network may have been deliberately manipulated to mislead the analysis. To solve this problem, a recent study attempted to understand...
Article
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The Authors are retracting this Article in response to criticisms about the assumptions underpinning the Article in terms of the identification of mentorship relationships and the measure of mentorship quality, challenging the interpretation of the conclusions. These criticisms were raised by readers and confirmed by three experts post-publication...
Article
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We study mentorship in scientific collaborations, where a junior scientist is supported by potentially multiple senior collaborators, without them necessarily having formal supervisory roles. We identify 3 million mentor–protégé pairs and survey a random sample, verifying that their relationship involved some form of mentorship. We find that mentor...
Article
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Social media has made it possible to manipulate the masses via disinformation and fake news at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be one of the weakest links when protecting critical infrastructure in general, and the power grid in particular. Here, we consider an attack in wh...
Article
Multilayer networks allow for modeling complex relationships, where individuals are embedded in multiple social networks at the same time. Given the ubiquity of such relationships, these networks have been increasingly gaining attention in the literature. This paper presents the first analysis of the robustness of centrality measures against strate...
Preprint
Full-text available
Disinformation continues to attract attention due to its increasing threat to society. Nevertheless, a disinformation-based attack on critical infrastructure has never been studied to date. Here, we consider traffic networks and focus on fake information that manipulates drivers' decisions to create congestion. We study the optimization problem fac...
Article
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We consider a demand response program in which a block of apartments receive a discount from their electricity supplier if they ensure that their aggregate load from air conditioning does not exceed a predetermined threshold. The goal of the participants is to obtain the discount, while ensuring that their individual temperature preferences are als...
Preprint
Multilayer networks allow for modeling complex relationships, where individuals are embedded in multiple social networks at the same time. Given the ubiquity of such relationships, these networks have been increasingly gaining attention in the literature. This paper presents the first analysis of the robustness of centrality measures against strate...
Article
Full-text available
Recent advances in artificial intelligence and deep learning have made it possible for bots to pass as humans, as is the case with the recent Google Duplex—an automated voice assistant capable of generating realistic speech that can fool humans into thinking they are talking to another human. Such technologies have drawn sharp criticism due to thei...
Article
Full-text available
Our private connections can be exposed by link prediction algorithms. To date, this threat has only been addressed from the perspective of a central authority, completely neglecting the possibility that members of the social network can themselves mitigate such threats. We fill this gap by studying how an individual can rewire her own network neigh...
Preprint
Full-text available
Inspired by the numerous benefits of mentorship in academia, we study "informal mentorship" in scientific collaborations, whereby a junior scientist is supported by multiple senior collaborators, without them necessarily having any formal supervisory roles. To this end, we analyze 2.5 million unique pairs of mentor-prot\'eg\'es spanning 9 disciplin...
Preprint
Full-text available
Social technologies have made it possible to propagate disinformation and manipulate the masses at an unprecedented scale. This is particularly alarming from a security perspective, as humans have proven to be the weakest link when protecting critical infrastructure in general, and the power grid in particular. Here, we consider an attack in which...
Article
The intuitive notion of added value in groups represents a fundamental property of biological, physical, and economic systems: how the interaction or cooperation of multiple entities, substances, or other agents can produce synergistic effects. However, despite the ubiquity of group formation, a well-founded measure of added value has remained elus...
Article
We propose a new centrality measure, called the Random Walk Decay centrality. While most centralities in the literature are based on the notion of shortest paths, this new centrality measure stems from the random walk on the network. We provide an axiomatic characterization and show that the new centrality is closely related to PageRank. More in de...
Article
Full-text available
The reliable operation of the power distribution system is a matter of national security. Increasingly, urban distribution systems rely on communications between customers and the utility to implement consumer-centric programs such as demand response that enhance the grid resilience. This paper reports an unconventional and previously-unexamined mo...
Article
Centrality indices aim to quantify the importance of nodes or edges in a network. Much interest has been recently raised by the body of work in which a node's connectivity is understood less as its contribution to the quality or speed of communication in the network and more as its role in enabling communication altogether. Consequently, a node is...
Article
At the heart of multi-agent systems is the ability to cooperate to improve the performance of individual agents and/or the system as a whole. While a widespread assumption in the literature is that such cooperation is essentially unrestricted, in many realistic settings this assumption does not hold. A highly influential approach for modelling such...
Preprint
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Algorithmic-matching sites offer users access to an unprecedented number of potential mates. However, they also pose a principal-agent problem with a potential moral hazard. The agent's interest is to maximize usage of the Web site, while the principal's interest is to find the best possible romantic partners. This creates a conflict of interest: o...
Preprint
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Link prediction is one of the fundamental problems in computational social science. A particularly common means to predict existence of unobserved links is via structural similarity metrics, such as the number of common neighbors; node pairs with higher similarity are thus deemed more likely to be linked. However, a number of applications of link p...
Article
Full-text available
Inspired by the social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists to study the relationship between research impact and five classes of diversity: ethnicity, discipline, gender, affiliation, and academic age. Using randomized baseline models, we establish the presence of homophily in ethnicity, gen...
Preprint
Link prediction is one of the fundamental research problems in network analysis. Intuitively, it involves identifying the edges that are most likely to be added to a given network, or the edges that appear to be missing from the network when in fact they are present. Various algorithms have been proposed to solve this problem over the past decades....
Conference Paper
Full-text available
Assessing the progress made in AI and contributions to the state of the art is of major concern to the community. Recently, Frechette et al. [2016] advocated performing such analysis via the Shapley value, a concept from coalitional game theory. In this paper, we argue that while this general idea is sound, it unfairly penalizes older algorithms th...
Article
One of the fundamental research challenges in network science is centrality analysis, i.e., identifying the nodes that play the most important roles in the network. In this article, we focus on the game-theoretic approach to centrality analysis. While various centrality indices have been recently proposed based on this approach, it is still unknown...
Article
Research has shown that a person's financial success is more dependent on the ability to deal with people than on professional knowledge. Sage advice, such as "if you can't say something nice, don't say anything at all" and principles articulated in Carnegie's classic "How to Win Friends and Influence People," offer trusted rules-of-thumb for how p...
Article
Full-text available
Inspired by the numerous social and economic benefits of diversity, we analyze over 9 million papers and 6 million scientists spanning 24 fields of study, to understand the relationship between research impact and five types of diversity, reflecting (i) ethnicity, (ii) discipline, (iii) gender, (iv) affiliation and (v) academic age. For each type,...
Article
Full-text available
The Internet and social media have fueled enormous interest in social network analysis. New tools continue to be developed and used to analyse our personal connections, with particular emphasis on detecting communities or identifying key individuals in a social network. This raises privacy concerns that are likely to exacerbate in the future. With...
Article
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Game-theoretic centrality is a flexible and sophisticated approach to identify the most important nodes in a network. It builds upon the methods from cooperative game theory and network theory. The key idea is to treat nodes as players in a cooperative game, where the value of each coalition is determined by certain graph-theoretic properties. Usin...
Article
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Intelligent building automation systems can reduce the energy consumption of heating, ventilation and air-conditioning (HVAC) units by sensing the comfort requirements automatically and scheduling the HVAC operations dynamically. Traditional building automation systems rely on fairly inaccurate occupancy sensors and basic predictive control using o...
Article
How can individuals and communities protect their privacy against social network analysis tools? How do criminals or terrorists organizations evade detection by such tools? Under which conditions can these tools be made strategy proof? These fundamental questions have attracted little attention in the literature to date, as most social network anal...
Article
One of the fundamental research challenges in network science is the centrality analysis, i.e., identifying the nodes that play the most important roles in the network. In this paper, we focus on the game-theoretic approach to centrality analysis. While various centrality indices have been proposed based on this approach, it is still unknown what d...
Article
Prediction markets are well-established tools for aggregating information from diverse sources into accurate forecasts. Their success has been demonstrated in a wide range applications, including presidential campaigns, sporting events, and economic outcomes. Recently, they've been introduced to the machine learning community in the form of artific...
Article
Algorithms for NP-complete problems often have different strengths andweaknesses, and thus algorithm portfolios often outperform individualalgorithms. It is surprisingly difficult to quantify a component algorithm's contributionto such a portfolio. Reporting a component's standalone performance wronglyrewards near-clones while penalizing algorithms...
Article
Full-text available
The coalition structure generation problem is a natural abstraction of one of the most important challenges in multi-agent systems: How can a number of agents divide themselves into groups in order to improve their performance? More precisely, the coalition structure generation problem focuses on partitioning the set of agents into mutually disjoin...
Article
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Although the notion of social capital has been extensively studied in various bodies of the literature , there is no universally accepted definition or measure of this concept. In this article, we discuss a new approach for measuring social capital which builds upon cooperative game theory. The new approach not only turns out to be a natural tool f...
Article
Betweenness centrality measures the ability of different nodes to control the flow of information in a network. In this article, we extend the standard definition of betweenness centrality using Semivalues - a family of solution concepts from cooperative game theory that includes, among others, the Shapley value and the Banzhaf power index. Any Sem...
Article
In the Complete Set Partitioning problem we are given a finite set of elements where every subset is associated with a value, and the goal is to partition this set into disjoint subsets so as to maximise the sum of subset values. This abstract problem captures the Coalition Structure Generation problem in cooperative games in characteristic functio...
Article
Full-text available
One key problem is that of identifying the key members of the organization using information about the terrorist network's topology: this capability would enable security agencies to focus severely limited resources on just those key members. many standard measures of centrality from the field of social network analysis can be used. Centrality meas...
Article
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Generalized characteristic function games are a variation of characteristic function games, in which the value of a coalition depends not only on the identities of its members, but also on the order in which the coalition is formed. This class of games is a useful abstraction for a number of realistic settings and economic situations, such as model...
Article
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Two fundamental algorithm-design paradigms are Tree Search and Dynamic Programming. The techniques used therein have been shown to complement one another when solving the complete set partitioning problem, also known as the coalition structure generation problem [5]. Inspired by this observation, we develop in this paper an algorithm to solve the c...
Article
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When the performance of a team of agents exceeds our expectations or fall short of them, we often explain this by saying that there was some synergy in the team---either positive (the team exceeded our expectations) or negative (they fell short). Our aim in this article is to develop a formal and principled way of measuring synergies, both positive...
Article
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An increasing number of businesses and organisations rely on existing users for finding new users or spreading a message. One of the widely used "refer-a-friend" mechanisms offers an equal reward to both the referrer and the invitee. This mechanism provides incentives for direct referrals and is fair to the invitee. On the other hand, multi-level m...
Article
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Coalition formation is a fundamental type of interaction that involves the creation of coherent groupings of distinct, autonomous, agents in order to efficiently achieve their individual or collective goals. Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of de...
Article
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Graph-restricted games, first introduced by Myerson [20], model naturally-occurring scenarios where coordination between any two agents within a coalition is only possible if there is a communication channel(a path) between them. Two fundamental solution concepts that were proposed for such a game are the Shapley value and the Myerson value. While...
Article
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Coalition Structure Generation-the problem of finding the optimal division of agents into coalitions-has received considerable attention in recent AI literature. The fastest exact algorithm to solve this problem is IDP-IP∗ [17], which is a hybrid of two previous algorithms, namely IDP and IP. Given this, it is desirable to speed up IDP as this will...
Conference Paper
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We propose a new representation for coalitional games, called the coalitional skill vector model, where there is a set of skills in the system, and each agent has a skill vector--a vector consisting of values that reflect the agents' level in different skills. Furthermore, there is a set of goals, each with requirements expressed in terms of the mi...
Conference Paper
Full-text available
We study a recently developed centrality metric to identify key players in terrorist organisations due to Lindelauf et al. [2013]. This metric, which involves computation of the Shapley value for connectivity games on graphs proposed by Amer and Gimenez [2004], was shown to produce substantially better results than previously used standard centrali...
Conference Paper
Full-text available
We introduce a new representation scheme for coalitional games, called coalition-flow networks (CF-NETs), where the formation of effective coalitions in a task-based setting is reduced to the problem of directing flow through a network. We show that our representation is intuitive, fully expressive, and captures certain patterns in a significantly...
Article
Full-text available
The Shapley value is arguably the most central normative solution concept in cooperative game theory. It specifies a unique way in which the reward from cooperation can be "fairly" divided among players. While it has a wide range of real world applications, its use is in many cases hampered by the hardness of its computation. A number of researcher...
Conference Paper
Full-text available
In this paper, we present AgentSwitch, a prototype agent-based platform to solve the electricity tariff selection problem. AgentSwitch incorporates novel algorithms to make predictions of hourly energy usage as well as detect (and suggest to the user) deferrable loads that could be shifted to off-peak times to maximise savings. To take advantage of...
Conference Paper
Full-text available
We present AgentSwitch, a prototype agent-based platform to solve the tariff selection problem for homeowners. AgentSwitch incorporates novel algorithms that work on the coarse data provided by smart meters to make predictions of hourly energy usage as well as detect (and suggest to the user) deferrable loads that could be shifted to off-peak times...
Conference Paper
Full-text available
Two-sided matchings are an important theoretical tool used to model markets and social interactions. In many real-life problems the utility of an agent is influenced not only by their own choices, but also by the choices that other agents make. Such an influence is called an externality. Whereas fully expressive representations of externalities in...
Article
Full-text available
We provide the first anytime algorithm for finding the e-core in a nontransferable utility coalitional game. For a given set of possible joint actions, our algorithm calculates ε, the maximum utility any agent could gain by deviating from this set of actions. If ε is too high, our algorithm searches for a subset of the joint actions which leads to...
Conference Paper
Full-text available
The current state-of-the-art algorithm for optimal coalition structure generation is IDP-IP—an algorithm that combines IDP (a dynamic programming algorithm due to Rahwan and Jennings, 2008b) with IP (a tree-search algorithm due to Rahwan et al., 2009). In this paper we analyse IDP-IP, highlight its limitations, and then develop a new approach for c...
Article
Full-text available
Two-sided matchings are an important theoretical tool used to model markets and social interactions. In many real life problems the utility of an agent is influenced not only by their own choices, but also by the choices that other agents make. Such an influence is called an externality. Whereas fully expressive representations of externalities in...
Conference Paper
Full-text available
In many real-life networks, such as urban structures, protein interactions and social networks, one of the key issues is to measure the centrality of nodes, i.e. to determine which nodes and edges are more central to the functioning of the entire network than others. In this paper we focus on betweenness centrality --- a metric based on which the c...
Conference Paper
Full-text available
We provide the first anytime algorithm for finding the e-core in a nontransferable utility coalitional game. For a given set of possible joint actions, our algorithm calculates e, the maximum utility any agent could gain by deviating from this set of actions. If e is too high, our algorithm searches for a subset of the joint actions which leads to...