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Nour Alkhaja Architecture Portfolio MArch. Bartlett School of Architecture | Distinction Graduate


Nour AlKhaja Email: n.alkhaja.17@ucl.ac.uk / noura-alkhoujah@hotmail.com Mobile: +971 55 752 6212 Naitionality: Syria Current Location: UAE -Sharjah. Education: Khalifa University of Science and Technology – Abu Dhabi, UAE Research Assistant at the Urban Research Lab.

04/ 2021 - Present

PhD Studentship (incomplete)- Engineering Systems and Management:

08/ 2019 - 01/ 2021

Final Rate: GPA (3.6). Research Topic: Evaluating the current status of the cities of Dubai and Abu Dhabi, bu using computational tools to develop better Understanding the role of street networks’ efficiency and centrality in city design. UCL, The Bartlett School of Architecture – London, UK M.Arch Architectural Design: Final Rate: Distinction. Research Topic: Living Architecture developed a machine learning algorithm that evaluates the quality of generated spaces using a ‘Wave Function Collapse’ algorithm. Damascus University, Faculty of Architectural Engineering – Damascus, Syria B.Eng. Architecture, Final Rate: Very Good. Research Experience: Khalifa University (PhD Studnet - Resaerch Assistant): - Use computational tools to evaluate street network performance for pedestrians. - Use excel and Python to conduct data analysis. - Organize and supervise the analysis workflow being doen by the master degree studnets, and prepare weekly reports. - Collaborate with the lab scientists and engineers. - Provide support to the team in terms of theoretical framework.

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- Prepare and conduct training sessions and manuals about the use of computational tools to help the master degree students. - Explore the potential of using optimization algorithms in enhancing walkability, by retrofitting land-use allocation. Professional Experience: KFA: Khaled Al Fahaam Architects, Planners and Designers (Design Architect – Damascus Syria):

05/ 2012 - 05/ 2017

- Develop the concept design according to the client’s needs. - Conduct relevant research I terms of site analysis, feasibility study and urban context. - Delegate and direct manpower and plan delivery orders for construction materials and equipment’s for the project. - Prepare schematic CAD drawings and detailing plans. - Prepare and participate in client’s meetings and presentations. - Prepare and update rendering shots using VRay. - Coordinate work with other team members to meet deadlines. - Liaise with municipality principles to get necessary permits. Key Projects: Villa Complex, Emran: Head Office and showroom, Al Badia Cement head Office, Syriatel TV Studio, Propharma stores, Mercedes -Benz:VIP Lounge, Syrian Insurance company: Head Office, National Sugar Company: Head Office. Skills: Scripting Languages: C# - Intermediate proficiency. Python - Intermediate proficiency. Grasshopper: Full proficiency. GIS ArcMaps: Intermediate proficiency. Gurobi Optimization Solver: Intermediate proficiency. 3D Modelling : Rhino – Full proficiency. Revit - Elementary proficiency. 3D Max - Full proficiency. Sketchup - Full proficiency. AutoCad: Full proficiency.

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Rewards: Institute of International Education : Fully funded scholarship to study the master degree at UCL, The Bartlett. Licenses & Certifications: Artificial Intelligence for Resilient Urban Planning - AIT Austrian Institute of Technology GmbH : Short course as part of Digital Futures. Language: - Arabic: Native proficiency. - English: Full professional proficiency- IELTS :8.00 - German: Elementary professional proficiency

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BPro Show- The Bartlett School of Architecure 2018, RC3 display space.


BPro Show- The Bartlett School of Architecure 2018, RC3 display space.

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ArchiGo : MArch Project | Bartlett School of Architecture


Studio Research Framework: Living Architecture // Tyson Hosmer, Octavian Gheorghiu, David Reeves “The role of the architect here, I think, is not so much to design a building or city as to catalyze them; to act that they may evolve. That is the secret of the great architect.” Gordon Pask “Traditionally we are taught to use top-down methodologies to design buildings. As the master of our design we look at the physical, social, and historical context of a project in its site as a set of inputs and we envision form and space to fit. Yet almost all meaningful social, biological, and economic systems are organized and “designed” from the bottom-up. Architects turn to diagrams and other abstract machines as both analytical and generative devices. Like a set of architect’s x-ray goggles, they are asked to “reveal” the underpinnings of the design. Utilising their power of abstraction, diagrams are called upon to liberate the architect by stripping away superfluous information to “reveal” ordered relationships between contextual layers. The conversion or hinge between analysis and generation is where the true instrumentality of the diagram consistently breaks down. What is the diagram’s relationship to form and material? Is it form? Can it be a physical construct? The mathematician John Von Neumann said that “Life is a process, which can be abstracted away from any particular medium”. He believed that the basis of life is in information and asked the question “What kind of logical organization is sufficient for an automation to reproduce itself?”

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An architecture conceived by the mind of AI : The use of intelligent computational algorithms implies the existence of a system that handles the production of built spaces. It also presumes that such system is capable of learning and producing continuously modified structures. It would be valid then to expect an outcome of highly responsive and adaptive structures when thinking of an architecture produced by AI. A debate that has been raised over 50 years ago by Nicholas Negroponte who presented to the world his idea about an architecture machine that can engage in partnership with the human designer to produce architecture. The proposed ArchiGo system Uses a combination of algorithms to generate reconfigurable aggregations of spatial tiles, the reconfigurability aspect is a response to changes in the input parameters derived from either the context of where the structure is being articulated in, or from the constraints and needs defined by the architect. This strategy brings both the human designer and the artificial intelligence to a symbiotic partnership to produce adaptable responsive spaces. The symbiotic approach (between the user, the designer and the algorithm) re-examines the boundaries of the architect’s role , and suggest a possibility that the only way for the architect- in the future- to influence the design is by interacting with the system, the architect would then become a user, or rather an informed user. Most machine learning algorithms rely on optimizing search tree algorithms , but one of the most revolutionary ones is the Monte-Carlo .It was used to train an artificial intelligence to teach itself how to play win the board game Go which entails an infinite number of possible moves and outcomes .” Monte Carlo tree search (MCTS)11,12 uses Monte Carlo rollouts to estimate the value of each state in a search tree. As more simulations are executed, the search tree grows larger and the relevant values become more accurate.The policy used to select actions during search is also improved over time, by selecting children with higher values. Asymptotically, this policy converges to optimal play, and the evaluations converge to the optimal value function”.1 The idea is to grow a tree of possible moves (actions) and results (states) , where an AI agent is capable of predicting the outcome of it’s actions , driving its behavior towards a more desirable results and refining the results of the training outcome. archiGo has optimized similar strategy to teach a machine learning agent how to produce reconfigurable structures. At each run of the training , an aggregation is produced , evaluated and stored within a search tree , the agent will iterate though this tree during the tile propagation and examines tile clustering similarities to avoid the repetition of clusters that leads to less appropriate aggregations.

1.Source: Mastering the game of Go with deep neural networks and tree search , David Silver 10


Basic Concept :

Basic Tile Set Design :

The space articulation is influenced by the geometrical constraints on one hand , that are imposed by the geometry placement within each tile ( how it allows other tiles to be connected to based on its direction within the tile) , and on the architectural criteria imposed by the context on the other , such as stability , total area requirement and the density of the overall aggregation. 11


The Alogorethmic approach : Machine Learning takes the use of computational algorithms a step further by optimizing the ability of statistical and search algorithms to develop an intelligence, an ability to reason about solutions for problems that are ill-defined and often challenging to humans due to their complexity. It’s also about building a general model that can process large data quantities, classify them in a comprehensive manner, and infer knowledge or solutions via machine learning. This presents an opportunity for architects to experiment with this technology when confronted with unusual building scenario such as Mars,where the structure should be considered for a highly fluctuating and unstable environment. The ArchiGo model has been developed to take inputs from both the environment and the user, where it processes a set of predefined discreet spatial parts into a coherent structure that optimizes both the constraints derived from the mars environment and the user requirements defined by the architect. The ArchiGo model uses an AlphaGo search like method that allows for predictive problem solving by back tracking through a search tree. The search tree is made up of matched states and outcomes and continues to grow and branch as the solver progress through learning iterations. The overall model was a hybrid of WFC algorithm , typical machine learning algorithms , and the adaption of Mont Carlo tree search used in AlphaGo . The WFC algorithm is able to solve a given space and fill it with tiles based solely on constraints defined by the tile geometry , the resulting aggregations is a combination of tiles that lacks architectural qualities , the tile selector within the WFC algorithm infers a range of possible tiles to be placed at each vertex based on the neighboring tiles constraints and randomly selects a tile . When Machine learning was used , a virtual value is added to refine the tile selections process called the “tile weight “ , it indicates the probability of the tile to be selected when having a higher value for the weight , the agent training then is designed to stimulate the selection of tiles that produces aggregations with more desired architectural qualities by favoring them during the selection process via assigning higher weight values . At each run of the learning episode an aggregation is produced by the WFC solver , where tiles violating parameters such as displacement and density are labeled as weak tiles and their weights are consequently reduced . This type of evaluation is limited in producing optimized aggregations because it does not fully allow the ML algorithm to associate desired values with the types of proper tiles that can produce such aggregations , the evaluation happens based on global assessment of the whole aggregation regardless of the local tile clustering behavior that influences how the solver propagate . 12


With the implementation of the tree search , the agent could track back through previous aggregations ( comprehensive data classification )and makes predictive decisions by avoiding the repetition of tile placements that leads to undesired aggregations. The training is designed to award the agent based on the overall aggregation quality produced by the agent , where it takes over the ctor role in the WFC algorithm . The aggregation is evaluated against three main aspects at each run : the stability , the density , and the required area . The accumulative value of these criteria will decide the aggregation quality of which the agent is rewarded based on.

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The training environment is devised to encourage associations between goals and states to be formed. At the beginning of the training episode the agent observes initial values such as the required area , the density constraints , the stability constraints , .. etc.The agent will start processing the tile placement but with tracking back through the tree of previously stored aggregations , the agent will iterate through each one and compare between the tile neighborhood being processed for tile selection and any similar neighborhood situations in previous aggregations , if a match is found , the agent moves to check whether the central tile is available in the domain of possible tiles and reduces its weight if it was labeled as a weak tile in that aggregation and vise versa if not . This minimizes the opportunity of bad tile clustering that leads to bad aggregation to be produced again. The training is by itself conducted with the use of artificial neural networks where a number of hyperparameters (parameters that cannot be directly linked to the training scenario) influence the training quality . When the number of those artificial neural networks and elements designated in each of those layers is increased ,the training quality and results is significantly enhanced.

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Yellow tiles indicate weak tiles that are under the influnce of stress and torque values that approaches the break point limits. With the training progress the gent learns how to produce more stable structure by choosing tile cluters that leads to more stable aggregations.

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The final outcome is an application interface were the user can input criteria of required space , density and the shape of the terrain , a trained brain would handle generating multiple choices of aggregation with high evaluation quality along with all its related data for the user to choose from.

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ArchiGo debated architecture as a system , or rather the product of anIntelligent system that with the collaboration of a human architect can Produce architecture .In extreme environments such as Mars’s, a highly fluctuating environment demands equally highly responsive system that can accumulate large data quantities , process them , and response by producing adapted built spaces. Photo Credit: ArchiGo team ( NOUR ALKHAJA , JELENA PELJEVIC , YEKTA TEHRANI, SHAHRZAD FEREIDOUNI) 23


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Light Writing | Bartlett School of Architecture


Experiencing spatiality with form is a result of wanting to define boundaries and thresholds through space. As architects we express this movement and narrative through drawing these expressions with the mediums available to us. With acknowledgment to the technology age architects have been opened up to an entire different genre within architecture where visualization and theorising space has become much faster and crucial. Within this project we have used the opportunity to document the choreography of the robot to trace its movement through time in one image. Each contour evaluates the length and the average of points existing within every closed looped to switch between colors (Red, Green and Yellow) using a LED light. Red being the longest loop with the most amount of control points, green the shortest lines with the least amount of control points and yellow being the average amount respectively. The final product visualizes the translation of that color calculation to simulate three-dimensional movement through space using an abstract form to trace accordingly.

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GH experiment | Gradient Distribution of openings on Surfaces


This grasshopper definition is designed to test the distribution of opening on surfaces in a gradual manner that is relative to cut-out geometry . The definition could be broken down into different stages , where isocurves on the U direction a divided into tow groups , later some of them are excluded based on the surface topography , then the division points generated along each of those isocurves are refined into groups in relation to their distance from the centre of the main cut-out geometry . Their size , shape and distribution is then manipulated via graph mappers to create the gradient effect . Each of those points is restricted in its location movement to a domain that takes into consideration the different adjacent edges.

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CA Tables! | Bartlett School of Architecture


Emergent forms with the use of Cellular Automata: This approach relies on optimizing the density as a primary tool to control the emergence of the pattern. By dividing the density into 4 distinct ranges , followed by a sequence of other conditional statements to further produce a controlled effect on certain frames or locations within the grid,increasing the ability to incite certain formations within the pattern. Other tools can be used also such as altering the growth rules based on the current state of the voxel itself or a specified neighbouring voxels , or by locating certain voxels within the grid based on their address . By following through this gradual focus on certain areas within the grid we are able to trigger certain patterns to emerge by setting a combination of rules that would control the future growth of the voxels either by setting their future state or the maximum age they can reach. By deciding which conditional statement is first to be used , we change how each frame is evaluated and calculated. The four distinct ranges of density provide more flexible use of the code by identifying which range produce more change by altering the set rules within it.The used density in the following experiments is a one based on a 2D neighbourhood surrounding any given voxel with a maximum number of 8 neighbouring voxels. if if if if

(aliveNeighbours (aliveNeighbours (aliveNeighbours (aliveNeighbours

>= 8)//High Range Density :: completly packed neighborhood > inst3 && aliveNeighbours < 8)//Mid-High Range Density (bewteen 3 or 4 upto 7) >= inst0 && aliveNeighbours < inst3) ////Mid-Low Range Density (bewteen 1 or 4 upto 3 or4) < inst0)////Low Range Density (less than 1)

This Neighbourhood force the code to check each voxel based on the number of the available nearby living voxels within the range of a 3*3 grid of squares , later on , a more specified condition is crafted based on the state of certain voxels within this neighbourhood and the content of this condition is what will decide the future state of the central voxel when the condition is satisfied. All of the experiments were based on the same seed image to show the potential of the coded rules to produce pattern variation despite using the same seed image , by altering the method of reading it at each frame. The following pages would demonstrate the variation resulting from altering the initial condition by choosing a different tool to evaluate each frame .

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The code is divided into 5 main parts according to the gradual density ranges , through multiple tests it has been concluded that while the “Mid-High” density range holds a minor effect on the overall resulting form, the “Mid-Low “ range hold higher potential for influencing the pattern when the conditional statements within it are changed .This is why it has been optimized through tow different zones (upper and lower part) through frame count to produce local desirable results. The lower part of the table is subject to the influence of a number of control zones and tools,but the interplay among each other to produce the overall form .The first tow tools are the rule change conditional statements repeated at each experiment which change the number of the neighboring voxels at a threshold frame count of 20 , while the mid-low density is defined through a threshold frame count condition of 30 , the 10 frame count difference is what causing the gradual growth voxel growth at the tip of the tow columns , the observed increased density within this critical zone of frames is caused by the fact that more voxels are considered valid to be evaluated by the conditional statements since rule allows for more neighboring voxels . Since each frame is evaluated through each conditional statement , we can isolate certain parts of the code to observe its individual affect on the emergent from , the “Mid-High” density range has minimum affect since the conditions within it a unlikely to be satisfied unlike the ones within the mid-low density ,it was crafted on purpose in that manner to prevent dense voxels to grow. Within the “Mid-Low” density range has minimum affect since the conditions within it a unlikely to be satisfied unlike the ones within the mid-low density ,it was crafted on purpose in that manner to prevent dense voxels to grow. Within the “Mid-Low” density range we can find the condition encourage a push toward the back of the grid since it is also instructing the growth of the upper tow corners of the neighborhood , a fact checked by flipping the content of the conditional statement to satisfy the lower corners instead of the upper ones.

If we examined the “mid-low”density part of the code within the frame count higher than(30) we find it divided into also parts depending on the state of the examined voxel,we find the conditions are inverted between these tow parts,if the current state is (1)we are instructing the code to keep the voxel alive but kill the four voxels on the corner while if its initial state is(0) we are instructing the code to keep it dead but to set the future state for the voxel corners to alive .This creates an alternate effect between the rows of either continuous growth or complete death as shown during the growth process.

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Student Housing | Damascus University - Graduation Project


Reshaping youth housing experience: Student housing is an opportunity to test the ability of forms to converge from public to privet .By creating a futuristic urban experience ,an impact to the surrounding urban fabric would initiate a possible future change for adapting a more flexible liberated architecture. The design Strategy relied on a number of key points : a. Social Interaction : Student housing could be considered an extent to the educational environment , thus adopting some of the main design principles used when considering educational spaces( fostering diversity - spaces that encourage engagement and exchange of ideas ) was necessary . b. Adaptability : considering the fact that the chosen plot is adjacent to the campus , an intent to impose a high degree of adaptability in space design and allocation to allow for a future reuse and different adaptation .Many of the social spaces included in the housing units are versatile and can be used for a number of different functions ( for example : the social platform in the Unit Type B. can be used as a series of lecture or event halls). c- Self Sufficiency : each housing unit is considered a self sufficient unit in terms of functions .i.e.: it includes all the required functions and therefore it can be re-adapted individually in the site without compromising the other units. d. Privacy : Insuring the design meets the requirements of privacy and noise free environment . Urban Design Strategy: The plot is adjacent to the faculty of mechanical engineering , with a close proximity to the main road , surrounded by a low rise blocks . The plot would represent a transition between the campus and any future developments that would occupy the rest of the nearby empty plots . This notion of transition was embodied in the design seed as series of Stripes representing a set of lines transferring form one point to another linking different parts of the plot to eventually form a connective tissue . These Stripes were later subject to a set of variables such as orientation , pedestrian movement ...,turning them gradually into masses emerging from the ground.

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Academic Projects - Damascus University (2006 -2011)


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Academic Projects - Damascus University (2006 -2011)


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Academic Projects - Damascus University (2006 -2011)

Study for a train platfrom coverage - 5th Year | Train Station Upgrdae

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Flexible Housing | Competition : Honourable mention


Flexible housing aims to cater for a wider range of changing household circumStances, lifeStyle or demographic changes and takes a more holictic view for the potential of adapting the housing unit prior to occupation as well as the ability to adjust it over time. Flexible housing thus works across the life of a housing development. Basic guidelines for achieving Flexibility : 1-Space: There is a correlation between amount of space and amount of flexibility. Some recent schemes have exploited this correlation by providing more space but at lower specification . 2- Condtruction: There is a relationship between conctruction techniques and flexibilty in housing schemes .It relies on simple and robust structure, which allow future intervention, or at least place the specialist elements such as services in easily accessible and separate zones so that only one set of specialists is needed to make changes. 3-Design for adaptation: the placing of staircases, service cores or entrances should allow future adaptibility at no extra cost. However, for this approach to be successful the designer has to project future scenarios and adaptations onto the plan to see what can be accommodated. Design Concept: The intention was to create a general frame that would guide future growth and allow for a greater degree of flexibility in terms of space usage , the idea is to use a basic minimum housing unite that could accommodate the housing functions ,and that is also adaptable for various uses , and flexible in terms changeability .Future spaces can be joined and re subtracted later without affecting the structure or the service ,these service areas are allocated also in strategic positions where it allows for optimum use even when the dwelling is expanded. This housing unite is based on a 60 cm grid with a 100 sq Meter total area,and a slack space is used between the housing units,which is initially used a condenser for social interaction , it’s shared between tow housing units, acting as a backyard that can be transformed easily to be included either one or both of the unites.An adaptable partition is used to seperate the unites from this slack space.Fexibility also applies to the modular parts separating the adjacent housing units that allows for larger dwelling arrangment.These basic three options for expantion can also be mixed allowing for a wide range of growth possibilities to suit almost all user different needs and social classes. 49


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General Layout

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Partition System | Competition : Honourable mention


Micro Architecture is the abstract from of Architecture itself , when reduced to its minimum representation of ( Surface + Structure + Function ) . Designing a flexible functional mean to inhabit the main space in order to generate more spaces and more surfaces to maximize the user usability of the space .Other important criteria had to be also taken into consideration such as : •( Temporariness ) = the ability to use it only when needed . • ( Flexibility ) = a robust system of panels that could be connected and expanded and could form corners depending on the need of the user, this notion of flexibility would also affect the fixture points( Joints & Track) . •( Durability )= which concerns the stability of the structure of itself and its ability to withstand the forces and momentum generated by drag and rotate actions when applied to the panels . •( cost effective manufacturing ) = The system is combined of modular parts that allows for efficient use and reduce the cost of the manufacture of materials , the main panel along with the joints and the guidance track are all able to be adapted into modular parts. •( Ease of Installation ) =The modular system has to be of a minimum number of parts to insure fast and easy installation both indoor and outdoor. •( Materials ) = The main tow materials used in the design are Aluminum and Bamboo , ( The main surface area is of a solid bamboo panel with CNC). In order to optimize the previous principles in an aesthetically appealing result panel system, a fold like system with repeated panels with minimum fixture point subtracted only to one point at the ground allowing to free the other point for angular and rotation possibility .The modular panels are also provided with a hook type of joint on its surface to allow for a projection or display images. The Bamboo surface is inhabited by a small scale “Muqarnas” derived from Arabic architecture , to add a minimum touch of visual appealing to the surface with obstructing its use a display.

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GH experiment | Dynamic Skin


This grasshopper exploration aim was to create a dynamic pattern that can applied to surfaces but could acquire structural qualities . The challenge was to manage the data flow throughout the definition while marinating a pattern when the data tree change ( when the UV counts change).

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Master Planning& Urban Design | Collaboration with AREP

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A prominent real estate developer in the UAE contracted with AREP to provide a study for a large scale mixed development on the coast of Muscat in Oman . AREP advertised it’s need for temporary architects to collaborate on the design . My role was to help in developing a concept study for the residential zone which comprised of privet villas of various scales . The developer insisted on large green open areas and minimum car routes within the residential part so we resorted to parking pockets on the prefatory of the residential zone while keeping in mind minimum walking distance considering the harsh weather during summer time . The housing concept also comprised large canopies that extended for large spans to provide shading inspired also from the narrow traditional environment of the old Muscat markets , where small alleys are shaded with light weight elements . Other features were included within the residential zone such as water fountains ,tennis & basketball play grounds , community gathering spaces and shaded foot paths , creating a harmonic weaved enclosed living zones . The water front was dedicated to hotels and shopping plazas , while a water canal was suggested to accommodate VIP villas with direct water access .

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3 Star Hotel - Iraq | Privet commission


This study is a privet commission to provide a concept study for a 3 star hotel in Iraq . The owner wanted to reflect a classical simple but elegant theme for his hotel , which was located on a prominent plot in the city of Najaf . The study was challenging due to the extreme proximity of the neighbouring residential buildings , and the difficulty to organize the car routes in and out of the hotel . It consisted of 256 rooms , tow restaurants , a gym with a swimming pool and a large lounge/reception are . Another challenge was to fit all the services such as the laundry , the kitchens , the HAVC rooms within the underground space while maintaining a separate rout for the service vehicles.

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Twin Villas | KFA Syria

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During my work at KFA Syria , I was responsible for developing floor plans for many projects , this twin villa had a major problem. The construction was stopped at the first floor level after the owner had realized that the old floor plans were wrong and comprised many issues such as inadequate allocation for spaces ..etc . The challenge was to remodel the floor plans while being restricted to a very wrong and inappropriate structure , but I managed to solve the problem.

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Gaming Capsul Design


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Industrial Design | Bike Helmet


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Industrial Design | Chair


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Interior design | KFA Syria

Interior study for a for a turkish bath > 72


< Interior study for a for a light fixtures shop

< Interior study for a for an insurance company

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Blender Design Exploration with Tissue tool


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