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24
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Introduction
PhD Student in Computer Science
Current institution
Publications
Publications (24)
This paper investigates the emotional reasoning abilities of the GPT family of large language models. We advocate a component perspective on evaluation that decomposes models into different aspects of emotional reasoning (appraisal derivation, affect/intensity derivation, and consequent derivation). We report two studies. A correlational study exam...
Language is far more than a communication tool. A wealth of information - including but not limited to the identities, psychological states, and social contexts of its users - can be gleaned through linguistic markers, and such insights are routinely leveraged across diverse fields ranging from product development and marketing to healthcare. In fo...
Large language models (LLMs) show promising capabilities in predicting human emotions from text. However, the mechanisms through which these models process emotional stimuli remain largely unexplored. Our study addresses this gap by investigating how autoregressive LLMs infer emotions, showing that emotion representations are functionally localized...
This paper extends recent investigations on the emotional reasoning abilities of Large Language Models (LLMs). Current research on LLMs has not directly evaluated the distinction between how LLMs predict the self-attribution of emotions and the perception of others' emotions. We first look at carefully crafted emotion-evoking stimuli, originally de...
Addressing safety risks in construction is an ongoing priority, and integrating safety considerations into construction scheduling is a crucial aspect of this effort. A notable challenge is the safety risk posed by concurrent tasks, which has received limited attention in prior research. This study aims to address this research gap by introducing a...
Unmanned aerial vehicles (UAVs) are experiencing a rapid expansion in their applications across various domains, including goods delivery, video capturing, and traffic control. The crucial aspect for UAVs to execute successful target tracking and obstacle avoidance maneuvers lies in the accuracy of their path planning operations. This research pape...
This paper investigates the emotional reasoning abilities of the GPT family of large language models via a component perspective. The paper first examines how the model reasons about autobiographical memories. Second, it systematically varies aspects of situations to impact emotion intensity and coping tendencies.
Even without the use of prompt eng...
Construction productivity estimation lacks a comprehensive, standard, and task-type-independent framework to generate and serialize Machine Learning (ML) models. This research aims to develop an ML management framework for estimating the work crew productivity (crew outputs over their working hours) by addressing various operation and project types...
This paper investigates the emotional reasoning abilities of the GPT family of large language models via a component perspective. The paper first examines how the model reasons about autobiographical memories. Second, it systematically varies aspects of situations to impact emotion intensity and coping tendencies. Even without the use of prompt eng...
Building materials, mainly steel and concrete used in residential buildings, significantly impact CO 2-eq emissions. Nowadays, carbon tax policy is used in some countries to reduce carbon emission effects. However, few comprehensive studies have been conducted to investigate the overall impact of such a carbon tax policy on minimizing building CO 2...
Despite the acknowledged promises of adopting technologies such as BIM and AR, research addressing the challenges and opportunities of such synergies in cost and schedule risk management is still limited. This paper contributes to the literature by presenting an integrated, proactive BIM-Augmented Reality (AR) risk management system enabling an onl...
To maintain underground utilities in a safe condition, the need for a comprehensive management and maintenance system is becoming more prominent. There are several problems with the current operation maintenance applications in underground utilities, including the lack of a digitalized 3D model with a comprehensive database for dynamically editing...
This paper presents a crane simulator system developed in the virtual reality (VR) environment integrated with a database of comprehensive lift studies and a detailed crane path planning system. This interactive system evaluates the lift operation quantitatively in real time in terms of its safety and practicability for the entire operation (entire...
Harbor caissons are regarded as one of the most critical infrastructures, and any disruption in their operation would have dramatic economic consequences. The need for a health monitoring system for these structures is thus evident. The primary aim of this study is to develop a structural health monitoring (SHM) system to effectively detect damage...
Heavy industrial construction, particularly when modularization is adopted, requires thorough heavy-lift studies to manage the extensive use of mobile cranes in congested and dynamic site layouts. This study introduces an integrated 4D crane simulation and onsite operation management framework for multiple concurrent mobile crane operations in the...
Improper planning and management of heavy lifts is a major cause of cost overruns, delays, and, more importantly, safety incidents in industrial megaprojects. Automated lift planning is widely acknowledged as an effective solution. This research presents an automated lift path planning system for mobile cranes leveraging space discretization and an...
In the past two decades, extensive research has been conducted to evaluate the seismic performance of Knee-element Connection Frames (KCFs) and to determine the most efficient configurations. KCFs are of particular advantage over other load-resisting systems in terms of their ample access for maintenance and enhanced structural performance. This pa...
Modularization is becoming more popular in industrial construction to enhance various project management aspects, including time, cost, safety, quality, and productivity. Although many studies have highlighted the differences between modular and conventional (stick-built) construction, little research is conducted to evaluate alternative fabricatio...
This paper studies the application of Knee-element Connection Frames (KCFs) as a seismic load resisting systems for pipe racks. This structural system only uses simple connections and provides a zonular rigid connection compared to the concentrated rigid connections used in Moment-resisting frames (MRFs). KCFs are of particular advantage over other...
Nowadays, one of the most prominent and globally discussed topics is presenting scientific methods to evaluate potential structural damages to improve infrastructure disaster risk management. Structural Health Monitoring (SHM) systems have been developed in recent years to aptly determine the damage contingency, level, and location before the struc...
