Lebanese American University

Tomorrow’s Leaders

Projects

Transportation Safety

TLP- Transportation Safety Project

Project Description

The Transportation Safety project focuses on enhancing driver safety by deepening our understanding of the social and behavioral issues important to the transportation of people and goods, mostly within the Lebanese context. The main focus of this project team is to investigate social, behavioral, and cognitive factors related to transportation engineering and driver psychology and behavior.

The project targets simulation scenarios that expand our knowledge of the social and behavioral factors related to high-risk aggressive driving. The research team additionally aims to evaluate the effects of public policy programs that promote safe driving and verify the latter’s benefits through controlled and simulated driving environment.

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Housed in the Engineering Lab and Research Center, the full-scale driving simulator will be utilized to simulate real-life driving scenarios to test drivers (of various backgrounds) to assess driver behavior, aggressiveness, reaction, and interaction with certain design or guidance triggers. The scenarios will test current versus proposed interventions, with an ultimate goal of applying such measures to the Lebanese community through proposed regulations or actual implementations.

Desired Disciplines

Team Leader

Dr. John Khoury
Professor of transportation engineering

Team Co-leaders

Industry Partners

General Directorate of Traffic and Vehicles, Ministry of Interior

Traffic Management Organization

YASA for Safety
Mr. Ziad Akl
CEO, YASA

Electronics - Made in Lebanon

Given the current economic crisis in Lebanon and the devaluation of the local currency, it has become a real challenge to acquire basic/common electronic devices and accessories due to the fact hardly anything is manufactured locally. The aim of this project is to design and build prototypes of common electronic devices and accessories (with unique features) that will address the local market demands with an economically feasible approach. Examples include phone chargers, satellite accessories, battery monitors, stand-by UPS devices etc.

 

Desired Disciplines

Team Leader

Dr. Dani Tannir

Team Co-leaders

To be assigned

Industry Partners

Sleiman (Sam) Chamoun, TriliteTech Inc.

Smart Irrigation System

Project Description

Uses the right amount of water to irrigate plants. This will not only save on water which is becoming scares but will yield quality agricultural products. Sensors will monitor the temperature and soil humidity, and will turn on/off irrigation pumps when need be. LoRa sensors which are long range wireless sensors that require low power to operate will be used. This system will be controlled from a phone application.

 

Desired Disciplines

Team Leader

Dr. Jimmy Issa

Team Co- Leaders

To be assigned

Industry Partners

Mr. Rawad Mouawad, BCMS international

Vision, Intelligence, and Robotics Applications (VIRA) Design Project

 

Understanding how computer vision technologies can be integrated with different artificial intelligence (AI) and robotics applications to design and implement real-life engineering projects defined based on the use cases of industry partners. It is designed to engage undergraduate and graduate students from LAU’s computer, electrical, and mechatronics engineering and computer science programs, to work on developing solutions for open-ended design projects with functional specifications and realistic constraints set by the industry partners. They will prepare the background material to cover the state of the art technologies related to the topics of their projects, ranging from computer vision, virtual reality, machine learning, knowledge engineering (mainly for computer engineering and computer science students), to robotics control, localization, navigation, and mapping (mainly for electrical and mechatronics engineering students). Students following this course will be eligible to conduct internship missions at the partner institutions, where they will work under the co-supervision of our industry partners. The course provides a culminating design implementation experience that is concluded by a written report and an oral presentation. In the process, students will learn about the different afore mentioned technologies to help solve practical industry problems and deliver the desired project outcomes.

 

 

Desired Disciplines

Team Leader

 Dr. Joe Tekli

Team Co-leaders

to be assigned

Industry Partners:

 

Food Waste in Lebanon: Assessment, Valorization and Mitigation (WAVA)

Assessing the food waste generated by the hospitality sector in Lebanon, and valorizing it for use in other applications instead of getting wasted. These applications include nutritional supplements, soap, pet foods, animal feed, among others.

 

Desired Disciplines

Team Leader

Dr. Hussein Hassan

Team Co-Leaders

to be assigned

Industry Partners

to be assigned

AI for Student-Major Fit: Placing the Right Student in the Right Field

Background

“If I were to do it all over again, I would select another major”. “My dream job needs another major, but this is what may parents want me to do”. “My friends chose this field of study, and they convinced me to follow suit”…!!! According to BestColleges Survey (2020), “[If] schools help students align their majors with their ideal career paths — rather than just emphasizing graduating on time — it could improve overall satisfaction in the major.” Accordingly, helping students choose the right major can contribute to a delightful learning experience, graduates with the needed knowledge, skills, motivation for life-long learning, and passion to excel in the job. If employability as a university KPI means empowering students with the skills and knowledge needed in demanded jobs, then success in the job requires additional critical factors:  commitment and passion!

Project

This project intends to design an innovative means to help students choose the right major; bridge the gap between required skills and provided ones; and achieve a higher level of satisfaction with the major.
Using AI, and a system of neural networking and a data warehouse, along with learning and skills analytics, system training will be initiated so as to analyze the major choice by students in comparison to abilities, values, interests, passion, economic considerations, and employability of the major graduates. Data collected will include information from surveys distributed to alumni, Master students, present undergraduate students, and high school students. Machine learning and data analytics will be deployed to relate major choice, major transfer, and satisfaction to personal, economic., major characteristics, motivation, abilities, career interests,…. and so on. The system learning will help predict with a certain level of accuracy the success and matching level of the student to the major and expected career success.

 

Steps

1. Develop a repository of main attributes associated to various (entry) career profiles:
a. Involve experts from corporate HR, career guidance officers, professional syndicates, and psychology to define the factors of importance and frame dataset scope.
b. Data collection from employers and company records
2. Develop a repository of main attributes associated to students (student profiling):
a. Involve experts from education, academic guidance officers, academic programs’ representatives, and psychology to define the factors of importance and frame dataset scope.
b. Data collection from schools and universities
3. Develop a neural network system and train the system using machine learning techniques until a high level of classification and prediction accuracy is achieved.

Impact

Enhance learners’ academic performance and commitment to future career objectives and enhance alignment between students capabilities/skills and career requirements.

Desired Disciplines

Team Leader

 Dr. Manal Yunis

Team Co-leaders

Dr. Wael Nuweihed

Industry Partners

to be assigned

 

Business model development and technical design of shared renewable energy systems in urban areas

The proposed project aims at developing a complete market design and business model for shared renewable energy systems in urban areas. The work will focus on the multi-disciplinary aspects of the project such as the technical engineering design of the electricity trading model (including policy requirements, required technologies to be applied, system operation and so on), the market analysis of the considered case study including the assessment of the involved billing schemes, and the implementation of practical, suitable and secure online trading and management solutions. Attention should also be paid to the social readiness of citizens for such modern models and to the need to identify the main barriers preventing the integration of the proposed solution.


Desired Disciplines

Team Leader

 Dr. Jawad El Khoury

Team Co-Leaders

to be assigned

Industry Partners

UNDP

 

Touch and Feel in Virtual and Augmented Reality

Virtual Reality (VR) technologies are rapidly expanding and are being utilized in countless industries including immersive gaming, education, surgical training, virtual co-working, manufacturing and design. While VR creates a completely simulated virtual environment, Augmented Reality (AR) works by superimposing virtual objects on top of the real world. As realistic as AR/VR technologies are becoming, they still do not provide haptic (touch) or force feedback to the user. The main objective of this project is to develop a ‘glove’ that once worn, provides a degree of realistic force feedback upon interaction with virtual objects in VR/AR. The project entails the following:

  1. Designing a VR/AR platform within which virtual objects can be introduced.
  2. Developing a haptic feedback glove that provides the user with real-time force feedback upon interaction with virtual objects
  3. Making sure both software and hardware are aesthetically pleasing, intuitive and user-friendly
  4. Conducting user-based studies and analysis for an enhanced user experience (UX)

 

Desired Disciplines

Team leader

Dr. Evan Fakhoury

Team Co-leader

Dr. Ali Ammouri

 Industry Partners

to be assigned

 

Development of a highly sensitive urine-on-chip test to diagnose kidney damage early before the establishment of signs and symptoms of chronic kidney dysfunction

Development of a highly sensitive urine-on-chip test to diagnose kidney damage early before the establishment of signs and symptoms of chronic kidney dysfunction.

Desired Disciplines

Team Leader

Dr. Wissam Faour

Team Co-leaders

Dr. Sola Bahous

Industry Partners

to be assigned

Airport 4.0- Opportunities, challenges and Risks of digitization of airports and impact on airline management practices

Airports around the world are constantly implementing new digital initiatives geared towards automating processes through passenger engagement. Digital solutions for airport operations aim at improving commercial and technical efficiency and include: flow monitoring and management, process automation, collaborative decision making, predictive & preventive solutions and customer engagement.
Digital transformations have different stakeholders like airlines, ground handling, duty-free shops and restaurants, service providers, etc. and cross different platforms (e.g., websites, smart phones, GUIs, digital screens, et.) and technologies (e.g., biometric check-in, thermal scanners, and other smart phone applications).
Digital initiatives however are not just about implementing the latest technologies or developing new ones, it involves reshaping the supply chain and the stakeholders/organizations boundaries and interactions in the supply chain. The ultimate goal being that of improving the passenger experience and safety and making the airport business and operations more efficient.
This project addresses the digitization of airports with the opportunities, challenges and risks involved. The project is along 2 tracks: technical and non-technical. The first one is concerned with the development of new digital initiatives/technologies or the design of a system of systems that integrate these solutions in a seamless fashion and well synthesized supply chain. The second track is concerned with addressing the soft aspect of the digitization process, namely, cultural, legal, security and organizational aspects. Quantifying the impact of digital initiatives and estimating the financial gain and associated risks are additional tasks to be investigated in this project.

 

Desired Disciplines

Team Leader

Dr. Pierrette Zouein

Team Co-leaders

Industry Partners

Beirut Airport Authority 

 

Performance analysis, operations, maintenance and staff training for a pilot wastewater treatment plant in a Lebanese Water Authority

The project aims at providing solutions and opportunities to elevate the wastewater facilities to a higher level of performance and optimize costs through efficiencies and investments.

The approach is to create a partnership between the public sector and the private sector (PPP) that focuses on achieving enhanced reliability in the WWTP operations and maintenance. This is achievable through the application of best practices, optimizing the life of the assets and using a solid asset management program, and improve the capabilities of the existing staff through an ongoing training and career development opportunities. Such a PPP may lead to major improvements in the water authority and provide many value-added strategies. Such strategies may target the improvement of treatment to cover the nitrogen compounds, odor and noise control, improve safety on site, and environmental compliance. During the works, the best practices and new and innovative ways will be used, developed, and improved to optimize operations.

 

Desired Disciplines

Team Leader

 Dr. Jean Chatila

Team Co-leaders

To be assigned

Industry Partners

Sustainability Engineering Group LLC (SEG)

 

Implementation of AI-based algorithms for Whole Exome Sequencing analysis and interpretation

Many socio-cultural, geographical and religious factors have favored the practice of consanguineous marriages in the Lebanese population. Intrafamilial unions, allowing the transmission through generations of an ancestral “private” mutation, have led to an increased frequency of orphan genetic disorders in this population.

Early detection and diagnosis of patients with genetic diseases is crucial to provide them with a targeted treatment and to allow the prevention of the disease-associated morbidity and mortality. Advances in the genetics field have revolutionized the molecular diagnosis. With the implementation of Next Generation Sequencing (NGS) approaches, genetic data has become available at a large scale. However, and to date, several challenges are still encountered mainly when dealing with the interpretation of the massively generated data.

Whole Exome Sequencing (WES), one of the applications of NGS, was developed to target specifically all coding regions of the Human genome, and was shown to efficiently improve the molecular diagnosis and to render it more rapid. Nevertheless, several steps are still required for the bioinformatics analysis of the raw data obtained by this technique, which is time consuming due to the size of the outputted data. This is also followed by a thorough interpretation of the generated data requiring the input of human resources including scientists, geneticists and physicians, for the correlation between the genotype and the phenotype.

In parallel, artificial intelligence (AI) is a growing field in computer sciences that aims to develop algorithms and techniques recreating the capabilities of the human mind. Its application in the medical field is currently gaining lots of attention, due to the potential of artificial intelligence (AI) in improving healthcare practices and its positive impact on the acceleration of patients’ diagnosis and on the guidance of chronic disease management.

 This project aims to develop algorithms based on AI in order to efficiently and rapidly analyze and interpret WES raw data based on the clinical presentation of the patient, his laboratory findings and his family history.

 

Desired Disciplines

Team Leader

 Dr. Andre Megarbane

Team Co-leaders

Industry Partners

NVIDIA


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