Ahmed Mustafa
Postdoctoral Research Fellow at Urban systems lab
Spatial data scientist - Land use - Urbanist
I am a spatial data scientist and broadly trained in the field of urban studies. My research focuses on the development and use of methodological approaches that work with complex data sources to study urban systems.
Urban systems lab
Greater New York City Area
Postdoctoral Research Fellow
University of Liège
https://www.linkedin.com/company/university-of-liege
Liège Area, Belgium
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Postdoctoral Researcher
University of Liège
https://www.linkedin.com/company/university-of-liege
I have been involved in an important research program dealing with the impact of climate change on flood risks in urban areas. The research, supported by an ARC grant (Wallonia-Brussels Federation, Belgium), specifically investigated the influence of land-use and urban configurations on future inundation hazard and flood exposure. I have been working with multiple colleagues from a range of disciplinary backgrounds in Geography, Urban Planning, Transportation, Hydrology, and Computer Science to approach future flood risks till 2100 from several angles and at different spatial scales. We have developed many models and used various data mining and information fusion methods to simulate land-use change, urban systems, and transport.
Liège Area, Belgium
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PHD Candidate
Purdue University
https://www.linkedin.com/company/purdue-university
▪ Visiting Scholar in the Department of Computer Science.
▪ Working with Professor Daniel Aliaga's team on developing a procedural generation system for designing urban layouts that passively reduce water depth during flood using C++.
Lafayette, Indiana Area
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Visiting Scholar
DBi Services – Global Leader in Infrastructure Operations and Maintenance
https://www.linkedin.com/company/dbiservices
▪ Defining customer requirements.	
▪ Participating in developing various applications using JAVA & .NET. 
▪ Providing training and technical support 
▪ Performing analysis on vector and raster data; and preparing reports and maps
▪ Performing QC on data processing projects
UAE and Egypt
https://media-exp1.licdn.com/dms/image/C4E0BAQGPXS0FxohASA/company-logo_100_100/0/1629152255325?e=1655942400&v=beta&t=S0CDoboX2qnvDub9r4X4agVO78BGJiLAk5aAQwWo8To
GIS Technical Engineer
Arabian GeoInformatics-Member of Al Ghurair Construction
• Participating in data integrity and quality assurance tasks.
• Testing, releasing and documenting GIS applications. 
• Presenting demos and briefs to help end-users understand the developed GIS tools.
Egypt and UAE
GIS Application Engineer
Africa for construction
Cairo, Egypt
Architect
Doctor of Philosophy - PhD
Engineering and Technology Sciences
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University of Liège
https://www.linkedin.com/school/university-of-liege/
Master of Science (MSc)
Geographic Information Science
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Lund University
https://www.linkedin.com/school/lunduniversity/
MSc preliminary academic year
Environmental Architecture, Sustainability and Alternative Energy
https://media-exp1.licdn.com/dms/image/C560BAQGYnGDX58wwLQ/company-logo_100_100/0/1519883636339?e=1655942400&v=beta&t=bIqxOjGuLWGarezcPmSIBfTciZY63fVXnZYArUL9qxE
Cairo University
https://www.linkedin.com/school/cairo-university/
Graduate diploma
Information Technology (GIS major)
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Information Technology Institute (ITI)
https://www.linkedin.com/school/information-technology-institute-iti-/
Bachelor of Engineering - BEng
Architecture
https://media-exp1.licdn.com/dms/image/C510BAQGGbtxS55FL-A/company-logo_100_100/0/1519885954444?e=1655942400&v=beta&t=uiQhz6Yf6HGe4XqHl5uQ3gfFHLep1UEQvZXmCcptbUw
Al-Azhar University
https://www.linkedin.com/school/al-azhar-university/
People who are especially vulnerable to COVID-19 also tend to be more affected by extreme weather events. Examples include elderly people and those living in densely populated cities. As the pandemic continues, scientists should help politicians to develop plans and policies that protect those most susceptible to the cascade of socio-economic risks that could arise when these hazards combine.
We need to find out how human behaviour is changing in response to COVID-19, how this affects demands for food, energy, the Internet and transportation, and whether these altered demands are likely to increase or decrease people’s susceptibility to the effects of extreme weather. Heatwaves could make COVID-19 shelter-in-place policies dangerous, for example, if elderly people or those with low incomes do not have air conditioning.
Cities and scientists must work together to protect urban residents. They need to improve city infrastructure, expand data sharing and create open communication channels between policymakers, planners and researchers. They should focus first on those most in need.
Heat and coronavirus can be twin killers
Nature
https://www.nature.com/articles/d41586-020-01627-8
The interest to find cost-optimal zero-energy solutions for building, using multi-objective optimization, has risen dramatically over the last decade. Accordingly, several studies have been carried out, proposing new methods and tools. None, however, has introduced a simplified approach that is viable by a broader range of users. This study addresses this lack, offering a methodology that supports the decision making process on cost-optimal zero energy building, using a novel approach, namely Multi-Objective Parametric Analysis (MOPA), rather than optimization algorithms. This study adds to the domain of roof stacking construction by setting the weight of construction as a third objective. The current methodology is applied to a newly developed theoretical Reference Building (RB) for a Belgian passive roof stacking house. Different options of the building’s superstructure components (walls, roof, and windows) have been examined. MOPA follows three consecutive steps: modeling setup, parametric simulation, and ends up with evaluation and selection. The results show cost-optimal zero-energy and lightweight packages of design variables for the building envelope.
Methodology for design decision support of cost-optimal zero-energy lightweight construction
Energy and Buildings
https://doi.org/10.1016/j.enbuild.2020.110170
Urban sprawl is widely acknowledged as an environmental and socio-economic challenge worldwide. This study examines urban sprawl in Belgium over six decades from 1950 to 2010. We assume that sprawl is a self-reinforcing process, i.e., sprawl is fueling further sprawl over time. The main objective of this study is to examine this assumption. We measure urban sprawl at four different levels in this study: country, regions, municipalities, and 1-km2 cells. Three sprawl indices are employed: the degree of urban dispersion, degree of urban permeation of the landscape, and built-up land uptake per capita. These three indices consider both the growth of built-up areas and population density to measure the magnitude of sprawl. The drivers of urban sprawl have been analyzed at a 1-km2 level. The examined drivers are previous urban dispersion patterns, distance to urban cores, elevation, and slope degree by means of linear regression. Urban sprawl significantly increased between 1950 and 1980, whereas its increase was more moderate between 1980 and 2010. Urban dispersion and permeation strongly affect the Brussels and Flanders regions. The results show that the increase in the degree of dispersion is locally driven by previous values of dispersion; i.e., it provides an adequate milieu for further dispersion. Therefore, our conclusion is that urban sprawl in Belgium tends to be a self-reinforcing process.
Self-Reinforcing Processes Governing Urban Sprawl in Belgium: Evidence over Six Decades
Sustainability
https://doi.org/10.3390/su12104097
This paper presents a systematic analysis of the influence of nine urban characteristics (distance between buildings, mean building size, building coverage, etc.) on surface flow in case of pluvial flooding. Time dependent stored volumes, outflow discharges and mean water depths were computed for a set of 2000 synthetic urban forms, considering various terrain slopes and return periods of the rainfall. An efficient porosity-based surface flow model was used to compute the 2D flow variables. Statistical analysis of the relationship between the flow and urban variables highlights that the flooding severity is mostly influenced by the building coverage.
Influence of urban forms on surface flow in urban pluvial flooding
Journal of Hydrology
https://doi.org/10.1016/j.jhydrol.2019.124493
A great deal of interest in off-site construction has been remarkable over the last decade. However, building on the rooftops of existing building has not been given a significant importance as a subject of research, despite its dependence on off-site construction and prefabrication. Thus, this paper develops a novel conceptual framework to support a multidisciplinary decision making for selecting off-site prefabricated constructional system for roof stacking. The multidisciplinary approach includes each of safety, logistics, cost, time, environmental impact, and quality of construction as major criteria in the decision making process. This paper is the outcome of an exhaustive investigation of more than 136 roof stacking projects built during the last 20 years. The development of framework is supported by a feedback validation loop based on semi-structured interviews with experts in the field of roof stacking and off-site construction.
Conceptual framework for off-site roof stacking construction
Journal of Building Engineering
https://doi.org/10.1016/j.jobe.2019.100873
Aside from modeling geometric shape, three-dimensional (3D) urban procedural modeling has shown its value in understanding, predicting and/or controlling effects of shape on design and urban planning. In this paper, instead of the construction of flood resistant measures, we create a procedural generation system for designing urban layouts that passively reduce water depth during a flooding scenario. Our tool enables exploring designs that passively lower flood depth everywhere or mostly in chosen key areas. Our approach tightly integrates a hydraulic model and a parameterized urban generation system with an optimization engine so as to find the least cost modification to an initial urban layout design. Further, due to the computational cost of a fluid simulation, we train neural networks to assist with accelerating the design process. We have applied our system to several real-world locations and have obtained improved 3D urban models in just a few seconds.
Procedural generation of flood-sensitive urban layouts
Environment and Planning B: Urban Analytics and City Science
https://doi.org/10.1177/2399808318812458
Land change (LC) models are dedicated to a better understanding of land use and land cover dynamics. A fundamental aspect of those models lies in the calibration of spatial parameters underlying such dynamics. Although there are many studies on the calibration of LC models, current efforts have a common goal of seeking to find a single global optimum solution, even though land change dynamics may be inherently heterogeneous throughout a given space. This article presents a calibration approach for finding multiple optimal solutions. A crowding niching genetic algorithm (CNGA) is incorporated into a cellular automata LC model. The model is applied to simulate urban expansion in Wallonia (Belgium) as a case study. Our findings demonstrate the ability of the model to locate multiple solutions simultaneously. In addition, the CNGA performs better than the standard genetic algorithm—besides, the CNGA helps to better understand the properties of land change dynamics within a given landscape.
Benefits of a multiple‐solution approach in land change models
Transactions in GIS
https://doi.org/10.1111/tgis.12482
One of the main objectives of land-use change models is to explore future land-use patterns. Therefore, the issue of addressing uncertainty in land-use forecasting has received an increasing attention in recent years. Many current models consider uncertainty by including a randomness component in their structure. In this paper, we present a novel approach for tuning uncertainty over time, which we refer to as the Time Monte Carlo (TMC) method. The TMC uses a specific range of randomness to allocate new land uses. This range is associated with the transition probabilities from one land use to another. The range of randomness is increased over time so that the degree of uncertainty increases over time. We compare the TMC to the randomness components used in previous models, through a coupled logistic regression-cellular automata model applied for Wallonia (Belgium) as a case study. Our analysis reveals that the TMC produces results comparable with existing methods over the short-term validation period (2000–2010). Furthermore, the TMC can tune uncertainty on longer-term time horizons, which is an essential feature of our method to account for greater uncertainty in the distant future.
A Time Monte Carlo method for addressing uncertainty in land-use change models
International Journal of Geographical Information Science
https://doi.org/10.1080/13658816.2018.1503275
The main goal of this PhD research is to investigate the expected flood damage for future urban patterns at different scales. Four main steps are followed to accomplish this goal. In the first step, a retrospective analysis is performed for the evolution of the urban development in Wallonia (Belgium) as a case study. Afterwards, two land use change models, cellular automata-based and agent-based, are proposed and compared. Based on this comparison, the agent-based model is employed to simulate future urbanization scenarios. An important feature of this research is evident in the consideration of the multiple densities of built-up areas, which enables to study both expansion and densification processes. As the model simulates urbanization up to 2100, forecasting land use change over such time frames entails very significant uncertainties. In this regard, uncertainty in land use change models has been considered. In the third step, 24 urbanization scenarios that differed in terms spatial policies and urbanization rate are generated. The simulated scenarios have then been integrated with a hydrological model. The results suggest that urban development will continue within flood-prone zones in a number of scenarios. Therefore, in the fourth and last step, a procedural urban generation system is developed to analyze the respective influence of various urban layout characteristics on inundation flow, which assists in designing flood-resistant urban layouts within the flood-prone zones.
Spatiotemporal modeling of interactions between urbanization and flood risk: a multi-level approach
University of Liège
http://doi.org/10.13140/RG.2.2.21270.86082
Urban expansion keeps largely dominant in Wallonia, even though a modest shift toward infill development can be observed over the last decade. Densification is largely driven by proximity to already dense areas. It is not related with proximity to railway stations. Proximity to medium- and large-sized cities does neither appear to be a key factor in densification processes, even though it is certainly where infill development is most expected in terms of both real estate value and contribution to sustainable development.
Addressing the determinants of built-up expansion and densification processes at the regional scale
Urban Studies
http://journals.sagepub.com/doi/full/10.1177/0042098017749176
In urban and transportation research, important information is often scattered over a wide variety of independent datasets which vary in terms of described variables and sampling rates. As activity-travel behavior of people depends particularly on socio-demographics and transport/urban-related variables, there is an increasing need for advanced methods to merge information provided by multiple urban/transport household surveys. In this paper, we propose a hierarchical algorithm based on a Hidden Markov Model (HMM) and an Iterative Proportional Fitting (IPF) procedure to obtain quasi-perfect marginal distributions and accurate multi-variate joint distributions. The model allows for the combination of an unlimited number of datasets. The model is validated on the basis of a synthetic dataset with 1,000,000 observations and 8 categorical variables. The results reveal that the hierarchical model is particularly robust as the deviation between the simulated and observed multivariate joint distributions is extremely small and constant, regardless of the sampling rates and the composition of the datasets in terms of variables included in those datasets. Besides, the presented methodological framework allows for an intelligent merging of multiple data sources. Furthermore, heterogeneity is smoothly incorporated into micro-samples with small sampling rates subjected to potential sampling bias. These aspects are handled simultaneously to build a generalized probabilistic structure from which new observations can be inferred. A major impact in term of expert systems is that the outputs of the hierarchical model (HM) model serve as a basis for a qualitative and quantitative analyses of integrated datasets.
An efficient hierarchical model for multi-source information fusion
Expert Systems with Applications
https://www.sciencedirect.com/science/article/pii/S0957417418303646?via%3Dihub
This paper presents a random forests (RF) based approach to estimate an origin-destination (O-D) matrix on the basis of a travel survey. The trips are predicted on a weekly basis to retain a maximum number of recorded trips for model calibration and validation.
A bi-level Random Forest based approach for estimating O-D matrices: Preliminary results from the Belgium National Household Travel Survey
Transportation Research Procedia
http://www.sciencedirect.com/science/article/pii/S2352146517306087
Facing the need to accommodate a growing number of inhabitants in major European cities, this research aimed to establish a methodology that facilitates decision making on urban densification through roof stacking. The methodology adopts a systematic approach on three consecutive levels: urban, engineering, and social.
A methodology to determine the potential of urban densification through roof stacking
Sustainable Cities and Society
http://www.sciencedirect.com/science/article/pii/S2210670717307849
This paper presents a hybrid urban expansion model (HUEM) that integrates logistic regression (Logit), CA and AB approaches to simulate future urban development. A key feature of HUEM lies in its ability to address various people behaviors that are variable over time through AB relying on a sample approach that combines Logit and CA.
Coupling agent-based, cellular automata and logistic regression into a hybrid urban expansion model (HUEM)
Land Use Policy
http://www.sciencedirect.com/science/article/pii/S0264837715302714
The objective of this paper is to investigate the respective influence of various urban pattern characteristics on inundation flow.
Influence of urban pattern on inundation flow in floodplains of lowland rivers
Science of the Total Environment
http://www.sciencedirect.com/science/article/pii/S0048969717333831
In Belgium, river floods are among the most frequent natural disasters and they may have important consequences on travel demand. In order to better understand how the travel patterns vary, we propose to set up a large scale scenario based on MATSim for guarantying an accurate assessment of the impact of river floods on the transportation system.
Investigating the impact of river floods on travel demand based on an agent-based modeling approach: The case of Liège, Belgium
Transport Policy
http://www.sciencedirect.com/science/article/pii/S0967070X16304425
This paper presents a model to simulate built-up expansion and densification based on a combination of a non-ordered multinomial logistic regression (MLR) and cellular automata (CA). Unlike the most commonly used built-up/urban models which simulate built-up expansion, our approach considers expansion and the potential for densification within already built-up areas when their present density allows it.
Modelling built-up expansion and densification with multinomial logistic regression, cellular automata and genetic algorithm
Computers, Environment and Urban Systems
http://www.sciencedirect.com/science/article/pii/S0198971517302405
In this study, urban development process in the Walloon region (Belgium) has been analysed. Two main aspects of development are quantitatively measured: the development type and the definition of the main drivers of the urbanisation process. Unlike most existing studies that consider the urban development as a binary process, this research considers the urban development as a continuous process, characterised by different levels of urban density. Eight urban classes are defined based on the Belgian cadastral data for years 2000 and 2010.
Understanding urban development types and drivers in Wallonia. A multi-density approach
International Journal of Business Intelligence and Data Mining
https://doi.org/10.1504/IJBIDM.2017.10004788
The determination of comprehensive activity-travel patterns is important in the context of agent-based microsimulation modelling. This paper presents an improved method based on profile Hidden Markov Models (pHMMs) able to include information related to the agents’ residential locations.
A Framework to Identify Housing Location Patterns Using Profile Hidden Markov Models
Advanced Science Letters
http://www.ingentaconnect.com/contentone/asp/asl/2016/00000022/00000009/art00012?crawler=true
In this paper, the development trajectory of an integrated framework for the mitigation of future flood risk of the Ourthe river basin in Belgium is discussed. The paper contributes to the state-of-the-art by presenting an integrated multidisciplinary framework capable of making long-term projections (time horizon 2050 and 2100) with the objective of mitigating future flood risk by proposing alternative land-use scenarios. It bridges numerous different fields, including urban planning, transport engineering, hydrology, geology, environmental engineering, and economics.
Development trajectory of an integrated framework for the mitigation of future flood risk: results from the FloodLand project
Transportation Letters
http://www.tandfonline.com/doi/abs/10.1080/19427867.2016.1256120?journalCode=ytrl20
Recent advances in agent-based micro-simulation modeling have further highlighted the importance of a thorough full synthetic population procedure for guaranteeing the correct characterization of real-world populations and underlying travel demands. In this regard, we propose an integrated approach including Markov Chain Monte Carlo (MCMC) simulation and profiling-based methods to capture the behavioral complexity and the great heterogeneity of agents of the true population through representative micro-samples.
Forecasting travel behavior using Markov Chains-based approaches
Transportation Research Part C
http://www.sciencedirect.com/science/article/pii/S0968090X1630095X
Micro-simulation travel demand and land use models require a synthetic population, which consists of a set of agents characterized by demographic and socio-economic attributes. Two main families of population synthesis techniques can be distinguished: (a) fitting methods (iterative proportional fitting, updating) and (b) combinatorial optimization methods. During the last few years, a third outperforming family of population synthesis procedures has emerged, i.e., Markov process-based methods such as Monte Carlo Markov Chain (MCMC) simulations. In this paper, an extended Hidden Markov Model (HMM)-based approach is presented, which can serve as a better alternative than the existing methods. The approach is characterized by a great flexibility and efficiency in terms of data preparation and model training.
Hidden Markov Model-based population synthesis
Transportation Research Part B
http://www.sciencedirect.com/science/article/pii/S0191261515300904
Climate change and urban development are key factors influencing future flood damage. This paper evaluates the sensitivity of future flood damage to a number of urban expansion scenarios for the river Meuse in Belgium. Based on these scenarios, the impact of urban development on flood damage is assessed.
Impacts of urban expansion on future flood damage: A case study in the River Meuse basin, Belgium
Sustainable Hydraulics in the Era of Global Change
http://www.crcnetbase.com/doi/abs/10.1201/b21902-143
Modelling the growth of urban settlements is of considerable interest for different applications, amongst which integrated flood management. This study aims at modeling urban growth for a long time horizon up to 2100 and to integrate the model outcomes with a hydrological model for the same time horizon. Forecasting land-use change over such time frames entails very significant uncertainties. In this regard, the main focus of this paper is attributed to the handling of uncertainty in an urban growth model.
Modelling Uncertainties in Long-Term Predictions of Urban Growth: A Coupled Cellular Automata and Agent-Based Approach
Proceedings of CUPUM 2015
http://web.mit.edu/cron/project/CUPUM2015/proceedings/Content/modeling/284_mustafa_h.pdf
Urban development is a complex process influenced by a number of driving forces, including spatial planning, topography, and urban economics. Identifying these drivers is crucial for the regulation of urban development and the calibration of predictive models. Existing land-use models generally consider urban development as a binary process, through the identification of built versus non-built areas. This study considers urban development as a continuum, characterized by several levels of densities, which can be related to different driving forces.
Urban Development as a Continuum: A Multinomial Logistic Regression Approach
Lecture Notes in Computer Science
https://link.springer.com/chapter/10.1007/978-3-319-21470-2_53
Urban environments are complex dynamic systems whose prediction of the future states cannot exclusively rely on deterministic rules. Although several studies on urban growth were carried out using different modelling approaches, the measurement of uncertainties was commonly neglected in these studies. This paper investigates the effect of uncertainty in urban growth models by introducing a stochastic perturbation method.
Measuring the Effect of Stochastic Perturbation Component in Cellular Automata Urban Growth Model
Procedia Environmental Sciences
http://www.sciencedirect.com/science/article/pii/S1878029614001637
My paper entitled "A Markov Chain Monte Carlo Cellular Automata Model to Simulate Urban Growth" has been selected as one of the best papers presented during the Ninth International Conference on Advanced Geographic Information Systems, Applications, and Services (GEOProcessing 2017, March 19 - 23, 2017 - Nice, France) .
https://www.iaria.org/conferences2017/awardsGEOProcessing17/geoprocessing2017_a4.pdf
GEOProcessing 2017
Best Paper Award
My paper entitled "Modelling Urban Expansion: A Multiple Urban-Densities Approach" has been selected as "Best Paper" in the Eighth International Conference on Advanced Geographic Information Systems, Applications, and Services (GEOProcessing 2016, April 24 - 28, 2016 - Venice, Italy).
https://www.iaria.org/conferences2016/awardsGEOProcessing16/geoprocessing2016_a1.pdf
GEOProcessing 2016
Best Paper Award
The project goal is to demonstrate the feasibility and relevance of an innovative methodology for including the continuous dynamic evolution of landuse into a micro scale flood risk model considering economic impacts both in the floodplain (direct impacts) and beyond (indirect impacts, e.g. disruption costs).
Research: Landuse change and future flood risk: influence of micro-scale spatial patterns
http://orbi.ulg.ac.be/handle/2268/173317
Verified all cadastral data using Imagery land-use, and land surveying data.
Led surveying team.
Industry: Surveying and Map Verification for Eastern Area - Sharjah (UAE)
Participated in developing  Irrigation Water Supply Geo-database and network.
Industry: The Operation,  Maintenance and Repair of Irrigation Water Supply System in Al Ain - Abu Dhabi (UAE)
Integrated Land Information System (ILMS) for Sharjah Directorate of Town Planning and Survey (SDTPS). 
Enterprise GIS system using Bentley solutions: Microstation – Bentley Map – ProjectWise – Geospatial Server & Oracle connector – Geoweb Publisher & Geoweb Solutions.  .Net web application - Oracle 10g & 11g client.
Industry: ILMS- Sharjah, UAE (Phase I, Phase II)
https://fr.linkedin.com/in/mathilde-cuchet-4474441b5
Greater Paris Metropolitan Region
Mathilde CUCHET
Etudiante à l'EPF Ecole d'Ingénieur-e-s, spécialité Energie et Environnement
https://be.linkedin.com/in/shady-attia-14352a7
Liège
Shady Attia
Professor in Sustainable Architecture and Building Technology at Université de Liège
https://be.linkedin.com/in/jacquesteller
Liège
Jacques TELLER
urban planning & housing | Towards an inclusive and sustainable city
https://www.linkedin.com/in/pablo-herreros-cantis
New York, NY
Pablo Herreros Cantis
Flood Risk Mapper, Spatial Analyst and Environmental Justice Researcher
https://www.linkedin.com/in/audreyalysejenkins
Brooklyn, NY
Audrey Jenkins, MPH
Urban Systems Lab Fellow at The New School
https://be.linkedin.com/in/mohamed-el-boujjoufi-282b73a6
Brussels
Mohamed EL BOUJJOUFI
Scientific Researcher chez Universiteit Antwerpen
https://www.linkedin.com/in/michaelcosh
Beltsville, MD
Michael Cosh
Research Hydrologist at USDA-ARS
https://fr.linkedin.com/in/alain-faure-b7b40610
Greater Lyon Area
Alain Faure
Chercheur chez CNRS
https://be.linkedin.com/in/caroline-kints-85402297
Brussels Metropolitan Area
Caroline KINTS
Ingénieur conception durable chez MK Engineering, Building Energy Design
https://in.linkedin.com/in/devdattat
Pune
Devdatta Tengshe
Associate Director - GIS
https://th.linkedin.com/in/lorenz-von-seidlein-2681b985
Thailand
Lorenz von Seidlein
Project coordinator at Mahidol - Oxford Research Unit
https://tr.linkedin.com/in/fatih-terzi-129b5144
Istanbul
Fatih Terzi
Professor of Urban Planning
https://tz.linkedin.com/in/salum-mshamu-6125a311b
Tanzania
Salum Mshamu
Consultant - Medical research at CSK research solutions LTD
https://nl.linkedin.com/in/kim-baraka-56578a4b
Amsterdam
Kim Baraka
Assistant Professor at Vrije Universiteit Amsterdam (VU Amsterdam)
Human-Robot Interaction researcher // Dance artist
Mostly interested in bidirectional human-robot teaching
https://www.linkedin.com/in/alireza-karbalayghareh-81513879
New York, NY
Alireza Karbalayghareh
Postdoctoral Researcher, ML & CompBio
https://www.linkedin.com/in/vishwaparekh
Baltimore, MD
Vishwa Parekh
AI | Radiology | Oncology
https://www.linkedin.com/in/enrique-lin-shiao-ph-d-b6841553
San Francisco Bay Area
Enrique Lin Shiao, Ph.D.
Associate, Asset Acquisitions at BridgeBio
https://www.linkedin.com/in/roozbeh-dehghannasiri-2996a52b
Stanford, CA
Roozbeh Dehghannasiri
Postdoctoral Research Fellow at Stanford University
Hazem Barakat
      
          



            
              
        
              
  

    
        Ahmed worked with me for several years (approx. 2010 to 2013). During those years, Ahmed has shown great sense of commitment and dedication, hard work, and innovative approaches to solving problems and satisfy clients. I wish him all the best in his career. 
https://qa.linkedin.com/in/ahmed-mustafa-36b4bb55
Qatar
Ahmed Mustafa
Organized and detail-oriented logistics specialist with more than four years of experience of careful management of transportation, equipment and materials, schedules, routes, and inventory.
https://uk.linkedin.com/in/amustafa999
London
Ahmed Mustafa
TV News Presenter, News Programs and Talk Shows Presenter
https://ao.linkedin.com/in/ahmed-mustafa-84a67b13
Angola
Ahmed Mustafa
Senior NPO Project Manager at Nokia Networks, PMP®
https://ng.linkedin.com/in/ahmed-mustafa-073898a8
Nigeria
Ahmed Mustafa
Truck and trailer sales
https://eg.linkedin.com/in/ahmed-mustafa-393321a9
New Cairo
ahmed mustafa
senior emergency physician  at Ministry of Health & Population - Egypt
ASPRS
https://media-exp1.licdn.com/dms/image/C5607AQG_YJjjfYFWUw/group-logo_image-shrink_200x200/0/1631436265349?e=1647687600&v=beta&t=FJJYK7_3mOmwZfAdwfsRcl_8M29X6k1wHkU4u0i9tSE
https://www.linkedin.com/groups/2745128
R
https://media-exp1.licdn.com/dms/image/C4D07AQHNmr1LIX99hQ/group-logo_image-shrink_200x200/0/1631373473349?e=1647687600&v=beta&t=sRRilGkMakaHVUPkAUDQyOftc90pJWPu0Tk99ZjXeyg
https://www.linkedin.com/groups/2613414
Python Developers Community (moderated)
https://media-exp1.licdn.com/dms/image/C4D07AQHwzHzy4qrgaw/group-logo_image-shrink_92x92/0/1631004564272?e=1647687600&v=beta&t=WgQW8q6eNd5zacyonZtC0RrTxJRLnW2uCzIKgPHLMOA
https://www.linkedin.com/groups/25827
QGIS
https://media-exp1.licdn.com/dms/image/C5607AQFHarNAK-_5Jw/group-logo_image-shrink_200x200/0/1631435759618?e=1647687600&v=beta&t=df7blcuDZhoGUhriSwonhe_zv-isOmra4Frj9JyywT0
https://www.linkedin.com/groups/2290177
Gis Jobs
https://media-exp1.licdn.com/dms/image/C5607AQFAOCMAcoJ0_w/group-logo_image-shrink_92x92/0/1521157955750?e=1647687600&v=beta&t=HrDlEaPAnK-6z1bNvjcVUPzwK9xoqwLxTeTT_gJLZMQ
https://www.linkedin.com/groups/2864431
Friends of GITA (Geospatial Information & Technology Association)
https://media-exp1.licdn.com/dms/image/C4E07AQGzO7mvSmQPiw/group-logo_image-shrink_92x92/0/1635183369728?e=1647687600&v=beta&t=S-cYF9wvmIsGUJ1kRuQtNY1ibikcBcT6bXs0cRlcFzo
https://www.linkedin.com/groups/82885
" HORIZON EUROPE " Framework Programme for Research and Innovation
https://media-exp1.licdn.com/dms/image/C4E07AQEdpTdPUnKfPQ/group-logo_image-shrink_200x200/0/1631004331558?e=1647687600&v=beta&t=tF5dY8eBX6MimKAZ0vBiqc_RGICnMG9noR9nAxp3nHY
https://www.linkedin.com/groups/3731775
Gulf GIS Jobs
https://static-exp1.licdn.com/sc/h/4h1ldzvvebtszyx75ve7dst1v
https://www.linkedin.com/groups/3667291
GEOinformatics
https://media-exp1.licdn.com/dms/image/C4E07AQGKnPC-dzuZyg/group-logo_image-shrink_200x200/0/1631370157976?e=1647687600&v=beta&t=jbGuJK15VQ3BeL16EOdYraPtAXGvjqeYaxDjlVjpTZc
https://www.linkedin.com/groups/853857
ACM SIGSPATIAL GIS
https://media-exp1.licdn.com/dms/image/C5607AQGqkQpj7oXBkw/group-logo_image-shrink_200x200/0/1631405058445?e=1647687600&v=beta&t=t47Svczr7p2Rz70aor0lX5firSfsLnWpribSDUeNqfY
https://www.linkedin.com/groups/4162155
Lund University Alumni Network (official)
https://media-exp1.licdn.com/dms/image/C5607AQF6w_6RhrZBYQ/group-logo_image-shrink_92x92/0/1521158369804?e=1647687600&v=beta&t=sNNuy-EXW3qpwhAB_p7Tkjey9biDp9BkRRDJK59FhGQ
https://www.linkedin.com/groups/36437
GIS Jobs Sweden
https://media-exp1.licdn.com/dms/image/C4E07AQGjKlqyOOVFkQ/group-logo_image-shrink_200x200/0/1631367416858?e=1647687600&v=beta&t=0XGNXjcf4t80nZYxZQfqNbgJHA5REiB7R5cdOpVT2sQ
https://www.linkedin.com/groups/3987658
Open Geospatial Consortium (OGC) Users Group
https://media-exp1.licdn.com/dms/image/C5607AQHoiOKVcs-LNA/group-logo_image-shrink_92x92/0/1636379228061?e=1647687600&v=beta&t=Evfe_m0Sm5y3QRhYlqwAS8pI7-SVmHCBEdT03UQ7ODw
https://www.linkedin.com/groups/55322
Land Information Systems
https://media-exp1.licdn.com/dms/image/C4D07AQFIcDdGtgKPfg/group-logo_image-shrink_200x200/0/1631365342703?e=1647687600&v=beta&t=rF8UsbHUF-feWfiNOuL-bdo9txoLZO91bZPd3moaUIQ
https://www.linkedin.com/groups/1788768