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Recent Submissions

Responsible Wireless Intelligence: Foundations of a New Cross-Layer Paradigm
(2026) Sarieddeen, Hadi ; Abou Faycal, Ibrahim ; Fahs, Jihad ; Chehimi, Mahdi ; Tajeddine, Razane ; Sharafeddine, Sanaa ; Department of Electrical and Computer Engineering; American University of Beirut
Wireless communication systems are evolving beyond information transmission toward wireless intelligence: systems that communicate, sense, learn, infer, and increasingly support autonomous decisions and actions. Advances in integrated sensing and communication (ISAC), artificial intelligence, semantic communications, and emerging quantum technologies are accelerating this evolution. However, increased awareness and autonomy make conventional communication-centric design objectives insufficient. Future systems must balance communication and sensing performance with robustness, privacy, security, energy efficiency, electromagnetic exposure, sustainability, and trust, calling for a fundamental reconsideration of how wireless systems are conceived, designed, and evaluated. This article introduces Responsible Wireless Intelligence (RWI) as a new cross-layer paradigm that elevates responsibility from a set of system constraints to a fundamental design principle spanning physical modeling, information theory, signal processing, artificial intelligence, and application-driven design. We establish the foundations of RWI by showing how physics and information theory define the limits of wireless intelligence, how cross-layer signal processing approaches these limits through model-based optimization and adaptive learning, and how ISAC, semantic communications, privacy-preserving learning, and emerging quantum technologies integrate within this broader framework. RWI thereby exposes fundamental tradeoffs among communication, sensing inference, privacy, resource consumption, and societal objectives, opening a new research agenda on limits, metrics, algorithms, and cross-layer optimization for wireless systems that communicate, sense, learn, reason, and act responsibly.
The Impact of Early Fertility Shocks on Women's Fertility and Labor Market Outcomes
(Springer Nature, 2025-03) Abboud, Ali; Department of Economics; American University of Beirut
This paper evaluates the effect of unplanned fertility shocks on women’s careers. I exploit the early repeal of abortion bans in five US states. This leads to variation in access to abortion across states and birth cohorts, which allows the estimation of the effect of accessing abortion at a certain age on women’s fertility. The evidence suggests that accessing abortion before the age of 21 delayed the age at which women gave birth to their first child by half a year on average. I also document an increase in completed fertility among Black women who received access to abortion early in their fertility cycle. The resulting variation in fertility realizations is then used to estimate the effect of fertility on women’s careers. I find that wages increase significantly as a result of the delay of an unplanned start of motherhood. This increase in wages translates into a 10% increase in labor earnings among Black women, and it is completely offset by the a decrease in labor supply for White women.
A Political Economy of the Tobacco Supply Chain in an Eastern Mediterranean Country: The Case of Lebanon
(Public Library of Science, 2025-03-31) Abboud, Ali; Chalak, Ali; Haddad, Joanne; Radwan, Mariam; Department of Economics; American University of Beirut
The literature on tobacco has traditionally focused on health effects, public policies for tobacco control, and smoker profiles. However, there is a notable gap in understanding the supply chains and industry practices within the tobacco market. This paper addresses this gap by examining the structure of the tobacco market in Lebanon. Using an exploratory qualitative research approach, this paper maps the tobacco supply chain in Lebanon and investigates the interactions among various stakeholders, including key policymakers, regulators, researchers, and industry experts, as well as their underlying interests. Lebanon is a compelling case study due to its high smoking prevalence, the presence of a state-owned tobacco monopoly (the Regie Libanaise de Tabacs et Tombacs (Regie)), and the ongoing financial crisis that has affected various sectors, including the tobacco industry. The findings reveal three key issues: a complex political economy centered around monopolization and conflicting interests, the absence of a clear national strategy on tobacco leading to ineffective policy formulation, and inefficient tobacco cultivation practices requiring reforms for sustainable agricultural development. To address these issues, it is proposed to foster a more competitive and revenue-efficient tobacco market through the dissolution of the Regie monopoly via horizontal and vertical integration. This includes adopting an excise-specific tax on domestically manufactured tobacco goods and optimizing sales taxes on locally traded items. Secondly, expanding antitrust laws to encompass the tobacco industry and introducing legislative measures for fees and taxes are recommended to create an enabling environment for competition and revenue generation. Thirdly, reforming tobacco cultivation practices requires abolishing the current cultivation licensing framework, offering financial compensation to existing license holders, and supporting farmers in transitioning to alternative crops.
Lebanon Pulse Index Simulation: A Comparative Analysis of Alternative Economic Sentiment Methodologies
(Department of Economics, 2026-09) El Awar, Noura; El Sayed, Leila; Keaik, Layan; Department of Economics; American University of Beirut
The Lebanon Pulse Index is the Labor and Equity Lab at the American University of Beirut's measure of consumer confidence and economic sentiment in Lebanon. Ahead of its construction, this paper uses pilot data from 182 respondents to examine established economic-sentiment methodologies for design choices that could inform the index. We benchmark four such methodologies, from the United States, Germany, Japan, and India, against the same seventeen-item question set, examine the underlying structure of the six core and eleven standby items through principal component analysis, and assess how sensitive each methodology's composite score is to the addition of individual standby items. The core six items behave as a single, coherent construct, supporting simple equal-weighted averaging. Within that construct, the three present-oriented and three future-oriented items separate cleanly into two related but distinct components, providing empirical support for building the Lebanon Pulse Index as separate present and future sub-indices rather than one undifferentiated score. The sensitivity analysis further shows that progressive-weighting methodology, which retains the intensity of a response rather than collapsing it into a binary positive or negative category, is more responsive to the concentration of extreme responses present in the pilot data. We recommend that the production Lebanon Pulse Index draw on progressive weighting, combined with a present and future sub-index structure grounded in the six core items, rather than adopting any single benchmarked methodology wholesale.
AI-based calorie and macronutrient estimation for Lebanese dishes using single-view images
(2026-09-23) Elbassuoni, Shady; Department of Computer Science; American University of Beirut
This dataset is used for the study "AI-based calorie and macronutrient estimation for Lebanese dishes using single-view images". It contains image data used for food classification and for the evaluation of the proposed system under real-world conditions. The dataset includes: (1) a food-classification dataset containing web-collected food images and synthetic food images generated using a GAN, Gemini, and Sora. The synthetic data are organized according to the study’s 174 food classes; (2) a final real-world test set containing 225 food images obtained from wearable-camera recordings collected from children in free-living settings in Lebanon as part of the SCALE study; and (3) an Excel file containing the corresponding food-class labels and ground-truth portion weights for the 225 wearable-camera images.