Yasir Zaki

• PhD
• Lecturer at New York University Abu Dhabi

Free-flow road networks, such as suburban highways, are increasingly experiencing traffic congestion due to growing commuter inflow and limited infrastructure. Traditional control mechanisms, such as traffic signals or local heuristics, are ineffective or infeasible in these high-speed, signal-free environments. We introduce self-regulating cars, a...

Over 2.6 billion people remain without access to the Internet in 2025. This phenomenon is especially pronounced in developing regions, where cost and infrastructure limitations are major barriers to connectivity. In response, we design SONIC, a low-cost, scalable data delivery system that builds on existing infrastructures: FM radio for downlink br...

As the knowledge of large language models (LLMs) becomes outdated over time, there is a growing need for efficient methods to update them, especially when injecting proprietary information. Our study reveals that comprehension-intensive fine-tuning tasks (e.g., question answering and blanks) achieve substantially higher knowledge retention rates (4...

Large Language Models (LLMs) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reliant on them for an enormous variety of tasks, a body of academic research has developed to examine these models for inherent biases, especially political biases, often fi...

Text-to-image generative AI models such as Stable Diffusion are used daily by millions worldwide. However, the extent to which these models exhibit racial and gender stereotypes is not yet fully understood. Here, we document significant biases in Stable Diffusion across six races, two genders, 32 professions, and eight attributes. Additionally, we...

Bias in news reporting significantly impacts public perception, particularly regarding crime, politics, and societal issues. Traditional bias detection methods, predominantly reliant on human moderation, suffer from subjective interpretations and scalability constraints. Here, we introduce an AI-driven framework leveraging advanced large language m...

Generative Artificial Intelligence (AI) is a cutting-edge technology capable of producing text, images, and various media content leveraging generative models and user prompts. Between 2022 and 2023, generative AI surged in popularity with a plethora of applications spanning from AI-powered movies to chatbots. This paper investigates the potential...

Citations are widely considered in scientists’ evaluation. As such, scientists may be incentivized to inflate their citation counts. While previous literature has examined self-citations and citation cartels, it remains unclear whether scientists can purchase citations. Here, we compile a dataset of ~1.6 million profiles on Google Scholar to examin...

Accessing the internet in regions with expensive data plans and limited connectivity poses significant challenges, restricting information access and economic growth. Images, as a major contributor to webpage sizes, exacerbate this issue, despite advances in compression formats like WebP and AVIF. The continued growth of complex and curated web con...

TikTok is a major force among social media platforms with over a billion monthly active users worldwide and 170 million in the United States. The platform's status as a key news source, particularly among younger demographics, raises concerns about its potential influence on politics in the U.S. and globally. Despite these concerns, there is scant...

Bluetooth Low Energy (BLE) location trackers, or "tags", are popular consumer devices for monitoring personal items. These tags rely on their respective network of companion devices that are capable of detecting their BLE signals and relay location information back to the owner. While manufacturers claim that such crowd-sourced approach yields accu...

The Global South faces unique challenges in achieving digital inclusion due to a heavy reliance on mobile devices for internet access and the prevalence of slow or unreliable networks. While numerous studies have investigated web accessibility within specific sectors such as education, healthcare, and government services, these efforts have been la...

The web experience in developing regions remains subpar, primarily due to the growing complexity of modern webpages and insufficient optimization by content providers. Users in these regions typically rely on low-end devices and limited bandwidth, which results in a poor user experience as they download and parse webpages bloated with excessive thi...

This paper investigates the efficacy of Next.js as a framework addressing the challenges posed by React.js, particularly in performance, SEO, and equitable web accessibility. By constructing identical websites and web applications in both frameworks, we aim to evaluate the frameworks' behavior under diverse network conditions and capabilities. Beyo...

License plate recognition (LPR) involves automated systems that utilize cameras and computer vision to read vehicle license plates. Such plates collected through LPR can then be compared against databases to identify stolen vehicles, uninsured drivers, crime suspects, and more. The LPR system plays a significant role in saving time for institutions...

Despite increasing mobile Internet penetration in developing regions, mobile users continue to experience a poor web experience due to two key factors: (i) lack of locally relevant content; (ii) poor web performance due to complex web pages and poor network conditions. In this paper, we describe our design, implementation and deployment experiences...

Traditional cellular service was designed for global connectivity, but business and logistical constraints led to its fragmentation, with deployments limited to individual countries and regions. Initiatives like Mobile Virtual Network Operators (MVNOs), Mobile Network Aggregators (MNAs), and regulations like ''roam-like-at-home'' have partially res...

Social media platforms play a pivotal role in shaping public opinion and amplifying political discourse, particularly during elections. However, the same dynamics that foster democratic engagement can also exacerbate polarization. To better understand these challenges, here, we investigate the ideological positioning of tweets related to the 2024 U...

The widespread dissemination of hate speech, harassment, harmful and sexual content, and violence across websites and media platforms presents substantial challenges and provokes widespread concern among different sectors of society. Governments, educators, and parents are often at odds with media platforms about how to regulate, control, and limit...

Technologies for recognizing facial attributes like race, gender, age, and emotion have several applications, such as surveillance, advertising content, sentiment analysis, and the study of demographic trends and social behaviors. Analyzing demographic characteristics based on images and analyzing facial expressions have several challenges due to t...

The manner in which different racial and gender groups are portrayed in news coverage plays a large role in shaping public opinion. As such, understanding how such groups are portrayed in news media is of notable societal value, and has thus been a significant endeavour in both the computer and social sciences. Yet, the literature still lacks a lon...

Recent breakthroughs in Large Language Models (LLMs) have led to their adoption across a wide range of tasks, ranging from code generation to machine translation and sentiment analysis, etc. Red teaming/Safety alignment efforts show that fine-tuning models on benign (non-harmful) data could compromise safety. However, it remains unclear to what ext...

In recent years, we have witnessed myriad flavours of Mobile Network Aggregators (MNAs) which exploit the coverage footprint of a handful of base operators to provide global mobile connectivity. Under the MNA model, emerging operators reap the benefits of network softwarization and virtualization, including eSIM technology or control/data-plane sep...

As of 2022, about 2.78 billion people in developing countries do not have access to the Internet. Lack of Internet access hinders economic growth, educational opportunities, and access to information and services. Recent initiatives to ``connect the unconnected'' have either failed (project Loon and Aquila) or are characterized by exorbitant costs...

Large language models (LLMs) demonstrate impressive zero-shot and few-shot reasoning capabilities. Some propose that such capabilities can be improved through self-reflection, i.e., letting LLMs reflect on their own output to identify and correct mistakes in the initial responses. However, despite some evidence showing the benefits of self-reflecti...

Over two-thirds of the U.S. population uses YouTube, and a quarter of U.S. adults regularly receive their news from it. Despite the massive political content available on the platform, to date, no classifier has been proposed to classify the political leaning of YouTube videos. The only exception is a classifier that requires extensive information...

The technological and online experiences of billions worldwide are dominated by a handful of companies known as “Big Tech.” Despite this being a cause for concern in governmental, economic, and ethical spheres, the literature lacks a study exploring the impact of public scandals on, and the global sentiment toward, Big Tech. Here, we quantify the p...

The rapid growth of satellite network operators (SNOs) has revolutionized broadband communications, enabling global connectivity and bridging the digital divide. As these networks expand, it is important to evaluate their performance and efficiency. This paper presents the first comprehensive study of SNOs. We take an opportunistic approach and dev...

The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work—a possibility that has sparked ample discussion on the in...

With over two billion monthly active users, YouTube currently shapes the landscape of online political video consumption, with 25% of adults in the United States regularly consuming political content via the platform. Considering that nearly three quarters of the videos watched on YouTube are delivered via its recommendation algorithm, the propensi...

As the use of Large Language Models (LLMs) in text generation tasks proliferates, concerns arise over their potential to compromise academic integrity. The education sector currently tussles with distinguishing student-authored homework assignments from AI-generated ones. This paper addresses the challenge by introducing HowkGPT, designed to identi...

The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work -- a possibility that has sparked discussions on the inte...

The World Wide Web has become increasingly complex in recent years. This complexity severely affects users in the developing regions due to slow cellular data connectivity and usage of low-end smartphone devices. Existing solutions to simplify the Web are generally evaluated using several different metrics and settings, which hinders the comparison...

Location tags enable tracking of personal belongings. This is achieved locally, e.g., via Bluetooth with a paired phone, and remotely, by piggybacking on the location reported by location-reporting devices which come into proximity of a tag. There has been anecdotal evidence that location tags are also misused to stalk people. This paper studies th...

The evolution of natural language processing techniques has led to the development of advanced conversational tools such as ChatGPT, capable of assisting users with a variety of activities. Media attention has centered on ChatGPT’s potential impact, policy implications, and ethical ramifications, particularly in the context of education. As such to...

The World Wide Web (WWW) empowers people in developing regions by eradicating illiteracy, supporting women, and generating economic opportunities. However, their reliance on limited bandwidth and low-end phones leaves them with a poorer browsing experience compared to privileged users across the digital divide. To evaluate the extent of this phenom...

Mobile phones are nowadays the predominant way for users to access the Internet. Despite modern phones are often more powerful than fixed devices, the majority of users worldwide still rely on simple devices, with limited hardware capabilities (small CPUs and memory, 2.4Ghz WiFi). In this paper, we investigate the user experience of low-end mobile...

As global cellular networks converge to 5G, one question lingers: Are we ready for the 5G challenge? A growing concern surrounds how well do existing congestion control algorithms perform in diverse 5G networks. Given that 5G networks are not yet widely deployed, assessing the performance of existing congestion control algorithms in realistic 5G se...

The amount of JavaScript used in web pages has substantially grown in the past decade, leading to large and complex pages that are computationally intensive for handheld mobile devices. Due to the increasing usage of these devices to access today’s web, and to accommodate the needs of a large number of mobile web users who solely rely on low-end de...

The number of Autonomous Vehicles (AVs) coexisting with conventional human-driven vehicles is expected to increase significantly in the coming years. This coexistence will last decades before full AV adoption is achieved worldwide. However, the cautious nature of AVs and the aggressive behavior of some human drivers could create unprecedentedly cha...

Classifying objects within aerial Light Detection and Ranging (LiDAR) data is an essential task to which machine learning (ML) is applied increasingly. ML has been shown to be more effective on LiDAR than imagery for classification, but most efforts have focused on imagery because of the challenges presented by LiDAR data. LiDAR datasets are of hig...

The amount of JavaScript embedded in Web pages has substantially grown in the past decade, leading to large and complex pages that are computationally intensive for mobile devices. In this paper, we propose JSAnalyzer, an easy-to-use tool that enables Web developers to quickly optimize and generate simpler versions of existing web pages for mobile...

The increasing complexity of JavaScript in modern mobile web pages has become a critical performance bottleneck for low-end mobile phone users, especially in developing regions. In this paper, we propose SlimWeb, a novel approach that automatically derives lightweight versions of mobile web pages on-the-fly by eliminating the use of unnecessary Jav...

JavaScript contributes to the increasing complexity of today's web. To support user interactivity and accelerate the development cycle, web developers heavily rely on large general-purpose third-party JavaScript libraries. This practice increases the size and the processing complexity of a web page by bringing additional functions that are not used...

Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable networks such as cellular networks. This paper proposes a Model-Driven Interpretability (MDI) congestion control framework, which derives a model version of a delay-based p...

Analyzing and interpreting the exact behavior of new delay-based congestion control protocols with complex non-linear control loops is exceptionally difficult in highly variable networks such as cellular networks. This paper proposes a Model-Driven Interpretability (MDI) congestion control framework, which derives a model version of a delay-based p...

It is well known that transport protocol performance is severely hindered by wireless channel impairments. We study the applicability of Machine Learning (ML) techniques to predict congestion status of 5G access networks, in particular mmWave links. We use realistic traces, using the 3GPP channel models, without being affected using legacy congesti...

Millimeter wave (commonly known as mmWave) is enabling the next generation of last-hop communications for mobile devices. But these technologies cannot reach their full potential because existing congestion control schemes at the transport layer perform sub-optimally over mmWave links. In this paper, we show how existing congestion control schemes...

Despite increasing mobile Internet penetration in emerging regions, the growth of web page complexity combined with inadequate content delivery mechanisms and lack of relevant local content make the web experience poor for users in these regions. In this paper, we propose GAIUS, a content ecosystem that enables the efficient creation and disseminat...

End-users in emerging markets experience poor web performance due to a combination of three factors: high server response time, limited edge bandwidth and the complexity of web pages. The absence of cloud infrastructure in developing regions and the limited bandwidth experienced by edge nodes constrain the effectiveness of conventional caching solu...

This book constitutes the refereed post-conference proceedings of the 8th International Conference on Mobile Networks and Management, MONAMI 2016, held in Abu Dhabi, United Arab Emirates, in October 2016. The 14 revised full papers were carefully reviewed and selected from 18 submissions. The papers are organized thematically in four parts, startin...

All over the world, road congestion is among the most prevalent transport challenges usually in urban environments which not only increases fuel consumption and emission of harmful gases, but also causes stress for the drivers. Intelligent Transportation System (ITS) enables a better use of the infrastructure by connecting vehicles to other vehicle...

Machine-to-Machine (M2M) communication is one of the emerging fields today and expected to play a major role in interconnecting various types of devices for different applications, such as logistics. Mobile communication standards, such as Long Term Evolution Advanced (LTE-A), have high data rate capability and are designed to provide broadband ser...

Legacy congestion controls including TCP and its variants are known to perform poorly over cellular networks due to highly variable capacities over short time scales, self-inflicted packet delays, and packet losses unrelated to congestion. To cope with these challenges, we present Verus, an end-to-end congestion control protocol that uses delay mea...

Modern web pages are very complex; each web page consists of hundreds of objects that are linked from various servers all over the world. While mechanisms such as caching reduce the overall number of end-to-end requests saving bandwidth and loading time, there is still a large portion of content that is re-fetched -- despite not having changed. In...

Machine-to-Machine (M2M) communication is the communication between two or more devices which communicate with each other autonomously. The concept of mobile M2M communication has emerged due to the wide range, coverage provisioning and decreasing costs of future mobile networks. Consequently, M2M traffic poses significant challenges to mobile netw...

The LTE (Long Term Evolution) provides mobile users high throughput and low latency. In order to meet the requirements of future mobile data traffic, the 3rd Generation Partnership Project (3GPP) has introduced advanced features to the LTE system, including Carrier Aggregation (CA), enhanced MIMO (Multiple Input Multiple Output), and coordinated mu...

Long term evolution (LTE) uses orthogonal frequency division multiple access (OFDMA) and single carrier frequency division multiple access (SC-FDMA) as the downlink and uplink transmission schemes respectively. The Quality of Service (QoS) provision to users is one of the key objectives of the wireless network operators. This paper analyses an upli...

Web access is prohibitively slow in many developing regions despite substantial effort to increase bandwidth and network penetration. In this paper, we explore the fundamental bot- Tlenecks that cause poor web performance from a client's perspective by carefully dissecting webpage load latency con- Tributors in Ghana. Based on our measurements from...

Cellular networks are reaching their physical limits providing capacity that is almost near the Shannon theory. However, cellular usage is still increasing exponentially with hungry applications demanding higher data rates. As a result, designers are facing significant challenge in meeting the required demands. One of the promising solutions, being...

Machine-to-Machine (M2M) communication is one of the newest research fields today and is expected to play a vital role in business areas such as e-healthcare, logistics etc. Mobile communication standards, such as Long Term Evolution Advanced (LTE-A) are designed to provide high data rate and broadband services to human-based communication. However...

Machine-to-Machine (M2M) communication is one of the emerging fields today and expected to play a major role in interconnecting various type of devices for different applications, such as logistics. Mobile communication standards, such as Long Term Evolution Advanced (LTE-A), have high data rate capability and are designed to provide broadband serv...

In Long Term Evolution Advanced (LTE-A) several new features have been added to deal with the ever-increasing demands for higher data rates and spectral efficiency. One of the key features that the Third Generation Partnership Project (3GPP) has introduced is the Relay Node (RN), a low power low cost device used to increase the spectral efficiency,...

There has been a lot of research focusing on optimizing the Long Term Evolution (LTE) networks performance. A large part of this research focused on how to optimize the LTE radio interface to efficiently distribute the scarce radio resources among the LTE users. Since LTE offers a diverse amount of services, the Quality of Service (QoS) differentia...

Machine-to-Machine (M2M) communication is expected to play a major role within the coming years towards the development of e-healthcare applications. The design of cellular networks, such as Long Term Evolution (LTE), is optimized to serve the data traffic of human-based communication with broadband requirements. E-healthcare traffic has different...

Long Term Evolution (LTE) is the recent standard of wireless communication developed by the Third Generation Partnership Project (3GPP). As the future mobile network, it is currently being rolled out to numerous areas world-wide. Besides other objectives such as enhancing the spectral efficiency and reducing latency for broadband services, LTE has...

Modern mobile devices comprise multiple interfaces for heterogeneous network technologies. However, currently implemented mechanisms to decide which one(s) to use and distribute application flows accordingly (i.e., solving the multihomed flow management problem, MFM) are rather coarse and do not leverage the opportunities. A user-centric quality-aw...

This paper proposes LTE radio scheduler analytical models. The motivation behind the models is to evaluate the performance of the complex LTE system analytically, rather than using simulations or real life experiments (which are not always possible to perform) that are too exhaustive and consumes large computation power and time. The models are dev...

One of the key radio resource management functions in mobile broadband networks is radio scheduling (also called MAC scheduling), which coordinates the access to shared radio resources. In Long Term Evolution (LTE), advanced scheduling algorithms are needed to provide proper QoS for multi-services and optimize the trade-off between QoS and resource...

With the advancement in technology, today most of the end-host devices are equipped with multiple wired/wireless interfaces and capable of using them in parallel. This has led to research in taking advantage of utilizing additional available network resources simultaneously such as multiple paths between the multi-homed end devices to achieve bette...

Machine-to-Machine (M2M) communications is one of the latest research areas. This technology aims to enable machines to communicate with each other, mainly, without human intervention. Looking today how the networking trends are changing, M2M traffic is envisaged to have a big role within the coming years; lots of research projects and standardizat...