GAD Academy Booklet by Kemal Arda Alkin

GAD ACADEMY BOOKLET 2020-2021 KEMAL ARDA ALKIN August,2021

Photo taken from GAD Academy Exhibition space, June 2021

GAD Academy Exhibition , June 2021 Aslihan Musaoglu,Su Abac, Gokhan Karakus, Gokhan Avcioglu, Kemal Arda Alkin,Ebru Mert, Irem Yilmazer

GAD Academy is an educational program within GAD Architecture. The programme consists of workshops , rapid manifacturing strategies and computational design thinking while preserving architectural perspective and discourse. The works of all students and workshops could be found in this booklet. Thanks to all of my students and mentors through out this process. It was an incredible journey.

Kemal Arda Alkin, GAD Academy Instructor

CONTENTS

01-Procedural Structures

1-6

02-Extraterrestial Tower

7-12

03-Data Visualisation

13-18

04-Material Workshop

19-22

05-AI and ML

23-28

06-Studio Projects

29-38

Procedural Structures

Course Duration: 2 weeks Software Used: Rhino, Grasshopper, TwinMotion, KeyShot,Illustrator, After Effects This workshop aims to teach the basis of the computational geometry manipulation. Students are taught main principles Rhino and Grasshopper. By utilizing simple tools such as , attractor points , voronoi , octree as much as simple data manipulations with flatten,graft and simplify. After the results from grasshopper, form has been rendered by Twinmotion and Keyshot . Also in the end students composed a video of their rendering by exporting single pages and combining them within Adobe After Effects.

Extraterrestrial Tower

Course Duration: 8 weeks Software Used:Maya, ZBrush, KeyShot, Photoshop We are used to thinking about time as a linear quasi-mathematical dimension with almost no intersection point with space. Students are challenged with the preconception of architecture as a static object by using animation as a design tool. Philosophically this workshop also has readings from philosophers such as Gilles Deleuze, Jacque Derrida, Jean Baudrillard ,Henri Bergson and asks questions about Time and how it could be a design element. This workshop utilizes a unique set of software to produce complex designs and architecture projects deploying a parametric workflow. Students will be provided with a set of tools and examples in order to build an aesthetic vocabulary that merges space and time into a new unicuum that generates unprecedented design results. In-Depth learning of Autodesk Maya, Grasshopper and Keyshot will expose the participants to an all-inclusive workflow that will cover software basics, complex geometry, hybrid mesh-nurbs modeling, animation design techniques, rendering, and final presentation.

Screen Capture from Maya

Screen Capture from ZBrush 8

Data Visualisation

Course Duration:4 weeks Software Used: Rhino, Grasshopper, Excel, Pyhton, Kepler GL, ArcGIS Workshop starts with questining the data and how it is stored within lists and files. Students created a data set as according to their wishes and proceed to forming linear connection between different set of datas. Istanbul Municipality releases public data sets for public analysis and usage. By analysing the traffic record on the lights and cameras we procudes an animation of traffic of Istanbul. Lists and datas collected by Microsoft Excel and then imported into Grasshopper.

BATMAN BEGINS

INCEPTION

I AM LEGEND

PA T RE IG NT E M S A OW MIA E IM UT MA ! IFU MIT N L AT ION MIN LEO GA D N: T TH M E EP HE IAN PR OF IST ESS ION AL DOG TOO TH THE PLAT FOR M PARAS ITE THE SN OWPIERC ER THE BOY IN THE STRIPPED PAJAMAS

EA TE

PIRATE S OF TH E CARI THE C BBEAN HRON ICLES REQ OF N UIEM ARNIA F OR A COR DRE PSE AM BRID TIT AN E IC AVA TAR TH E FIN SHA WS HA UP DING NK NE TO RE MO DE TH Y S MP T TIO OR PO E L N O Y LA RD 1 R O EX F TH PR E ES RI S NG S

GLADIATOR

E TH

SCREAM

SAW H RINT LABY T PAN'S MIS THE R ME UM FS H SO EC PE DAY S 'S S 500 MB ING LA EK AN HE TH RY FT IX TE EO TR IVA NC PR MA ORK ILE G E ES TH VIN TH TW OW SA NE SH TA AL T AN DE CI SO UM EN TR Vz R FO V

E TH

HER

TI M E IN YO AN UR A TH DR TOL E IA AG GI SO FT ON UL SH KI OP TC HE 3I DIO N RA TA TS TO UIL LE OL DB OY BIG FIS CITY H THE OF G ROY OD AL T ENEN BAUM S SPIRIT ED AW AY SNATCH

BEING JOHN MALKOVICH

SCARY MOVIE

AMERICAN HISTORY X G THE LION KIN T LER'S LIS SCHIND

A N

RUNNER JOKE R THE SHA PE O SHR FW EK ATE R SE VE N TH ER EV LIF EN EO AN LA T FP LA I UN LA ND W FO ON RG TH I DE VE E N TR R EE O F LI FE

S AR ST S UR O ES IN IN PP T HA UL GE F FA E A VE TO FI UI IC ST RS FA PU OK E L R TH AL NA YF AG E SK EET :R MIL STR OR EN LL TH RE WA EG OF TH LF WO R LLA THE E T ERS INT LLAS DFE GOO GS R DO RVIO RESE

N RE TIO NTU N C E A DV TIO A IMA APHY ANOGR BI MEDY CO AMA DR TASY FAN RY HISTO MUSICAL MYSTERY SCIENCE FICTION THRILLER THE KI TE

THE MARTIAN LIONAIRE SLUMDOG MIL MY SON ER AND MY FATH MIND TLESS E SPO TH F NTO INE O EME M SH N SU NAL SU T SU ETER AYE ES CIN ABL CH OU IRE INT NF S YO D EM A TG AL S OF CU OG N IT U A FD TR AX O R E IM PO CL NYA ISL O AX I.T M H AD AS M L IP H W

3 Idiots 500 Days of Summer A Beautiful Mind American History X Avatar Avengers Batman Begins Being John Malkovich Big Fish Cinayet Süsü City of God Climax Corpse Bride Dogtooth Eternal Sunshine of the Spotless Mind Exit Through the Gift Shop Fast Five Fault In Our Stars Finding Nemo Forest Gump Gladiator Goodfellas Harry Potter and the Sorcerer's Stone Her How to Train Your Dragon I am Legend I.Tonya Ice Age Inception Interstellar Intouchables Isle of Dogs Joker La La Land Leon: The Professional Life of Pi Mad Max Mamma Mia! Meet the Parents Memento My Father and My Son Name Oldboy Once Upon a Time in Anatolia Pan's Labyrinth Parasite Pirates of the Caribbean Polar Express Portrait of a Lady on Fire Ratatouille Requiem For a Dream Reservior Dogs Saving Private Ryan Saw Scary Movie Schindler's List Scream Seven Shrek Skyfall Slumdog Millionaire Snatch Soul Kitchen Spirited Away Star Wars The Boy in the Stripped Pajamas The Chronicles of Narnia The Greatest Showman The Green Mile The Immitation Game The King's Speech The Kite Runner The Lion King The Martian The Matrix The Mist The Pianist The Platform The Prestige The Pursuit of Happiness The Revenant The Royal Tenenbaums The Shape of Water The Shawshank Redemption The Silence of the Lambs The Snowpiercer The Social Network The Tree of Life The Truman Show The Wolf of Wall Street Thor: Ragnarok Titanic Toy Story 1 Uncut Gems Unforgiven Up V for Vendetta Whiplash Wonder Wonder

D EN

ON ST

A : I ST R RS ED TE zT TJ GE AS EN Y PO :L AV S R R AR HA R W A ST

R'S

E ER

Belgium Afghanistan Australia Brazil Canada Country of Production Czech Republic France Germany Greece India Japan Netherlands New Zealand Poland South Korea Spain Taiwan Turkey United Kingdom United States

Alejandro González Iñárritu Ali Atay Andrew Adamson Andrew Stanton Ang Lee Banksy Bong Joon-ho Brad Bird Çagan Irmak Carlos Saldanha Céline Sciamma Chris Columbus Chris Sanders Christopher Nolan Clint Eastwood Craig Gillespie Damien Chazelle Danny Boyle Darren Aronofsky David Fincher Director Fatih Akin Fernando Meirelles Francis Lawrence Frank Darabont Gabriele Muccino Galder Gaztelu-Urrutia Gaspar Noé George Miller Gore Verbinski Guillermo del Toro Guy Ritchie Hayao Miyazaki James Cameron

James McTeigue James Wan

Jay Roach Joe Russo John Lasseter Jonathan Demme Josh Boone Josh Safdie Justin Lin

Keenen Ivory Wayans Lana Wachowski Luc Besson Marc Forster Marc Webb Mark Herman Martin Scorsese

Michael Gracey Michel Gondry Morten Tyldum Nuri Bilge Ceylan Olivier Nakache Park Chan-Wook Pete Docter Peter Weir

Phyllida Lloyd Quentin Tarantino Rajkumar Hirani Ria Johnson Ridley Scott Rob Minkoff Robert Zemeckis Roman Polanski Ron Howard Sam Mendes Spike Jonze Stephen Chbosky Steven Spielberg Taika Waititi Terrence Malick Tim Burton Todd Phillips Tom Hooper Tony Kaye Wes Anderson Wes Craven Yorgos Lantimos Yorgos Lantimos

Material Behaviour Analysis

Course Duration:4 Weels Software Used: Rhino,AutoCad, Lazer Cutting This workshop focuses on the material behaviour. What are the properties that forms a particular behaviour and how it does balances the forces that it had been exposed to ? Material selection for this workshop is Polypropylene. Students formed their structures via experimentation, the core idea was to understand the approaches and experimentations of the material deformation and connectibility via joints that had been inside of the system.

Material Behaviour Analysis Matter Constraints PROJECT DESCRIPTON

What is material behaviour and how we control it ?

The study for the project began with the exploration and understanding of the physical properties of polypropylene sheets, which are flat 0.7mm thick materials produced as sheets. The aim was to generate a free-standing form that will consist of different geometries connected by using various deformation and connection methods.

Knowledge of a material’s properties, and how it behaves under various loading conditions is essential in design.

The physical properties of polypropylene include; semi-rigidity, toughness, good fatigue resistance, and integral hinge property. All of these properties make polypropylene a preferable material for such applications. We started with a primitive quadrilateral shape and applied different folding techniques such as bending and squeezing to its control points to develop several iterations. These trials have helped us to evaluate the intensity and the position of the control points required. While working on the iterations that we have created, we searched for a proper prototype that will be adaptable, modular, flexible and will allow us to create different combinations of that prototype by using different deformation and connection techniques.

- Materials are selected for specific applications dependent on their properties and characteristics. The behaviour of a material under load is markedly different depending on whether the material response is elastic or plastic.

Our Material : POLYPROPYLENE Polypropylene (PP) is a thermoplastic “addition polymer” made from the combination of propylene monomers. It is used in a variety of applications to include packaging for consumer products, plastic parts for various industries including the automotive industry, special devices like living hinges, and textiles.

In the end, we were able to produce various combinations and tessellations using the prototype that we have created. Connection methods and the connection pieces that we have used differed according to the manipulation and deformation techniques that have used.

Some of the most significant properties of polypropylene are: Chemical Resistance , Elasticity and Toughness , Fatigue Resistance , Insulation and Transmissivity.

RhinoVAULT - Designing funicular form in Rhinoceros RhinoVAULT is an open-source research and development platform for funicular form-finding built with COMPAS, a Python-based framework for computational research and collaboration in Architecture, Engineering, and Digital Fabrication. The development of RV2 is currently supported by the Block Research Group at ETH Zurich. RhinoVAULT emerged from research on structural form finding using the Thrust Network Analysis (TNA) approach to intuitively create and explore compression-only structures. For the ETH Zurih Block Research Group they use reciprocal diagrams, RhinoVAULT provides an intuitive, fast funicular form-finding method, adopting the same advantages of techniques such as Graphic Statics, but offering a viable extension to fully three-dimensional problems. Their goal is to share key aspects of their research in a comprehensible and transparent setup to let us not only create beautiful shapes but also to give you an understanding of the underlying structural principles. The resistant virtues of the structure that we seek depend on their form; it is through their form that they are stable, not because of an awkward accumulation of material. Block Reasearch Group at ETH Zurich , RhinoVAULT Project . Represented by Prof. Dr. Philippe Block

Parametric Self-Supporting Surfaces Via Direct Computation of Airy Stress Functions This project presents a method that employs parametric surfaces as surface geometry representations at any stage of a computational process to compute self-supporting surfaces. This approach can be differentiated from existing relevant methods because such methods represent surfaces by a triangulated mesh surface or a network consisting of lines. The proposed method is based on the theory of Airy stress functions.

Rippmann M.Funicular Shell Design: Geometric Approaches to Form Finding and Fabrication of Discrete Funicular Structures,ETH Zurich, Department of ArchitectureZurich,2016 (February) pg:5

Rippmann M.Funicular Shell Design: Geometric Approaches to Form Finding and Fabrication of Discrete Funicular Structures,ETH Zurich, Department of ArchitectureZurich,2016 (February) pg :12

Free - Form Tile Vault

Although some existing methods are also based on this theory, they apply its discrete version to discrete geometries. The proposed method simultaneously applies the theory to parametric surfaces directly and the discrete theory to the edges of parametric patches. The discontinuous boundary between continuous patches naturally corresponds to ribs seen in traditional vault masonry buildings. It shows the method of material and its behaviour.

This research project is designed by Block Research Group ETH Zurih and it presents advances in timbrel vaulting, made possible through innovation in form finding, guidework systems and construction methods. It is used for form finding method and it is a great example for material function.

Block Reasearch Group at ETH Zurich , Parametric self-supporting Project . New York

Thrust Network Analysis : A New Methodology For Three Dimensional Equilibrium

The concept of casting concrete in fabrics, fabric formwork technology, has resurfaced at various times and in different forms throughout the past century. The structure shows that have used fabrics for concrete formwork, including different types of flexible formwork, controlled permeability formwork and pneumatic formwork.

This project presents a new methodology for generating compression-only vaulted surfaces and networks. The method finds possible funicular solutions under gravitational loading within a defined envelope. Using projective geometry, duality theory and linear optimization, it provides a graphical and intuitive method, adopting the same advantages of techniques such as graphic statics, but offering a viable extension to fully three-dimensional problems. It is analysis of masonary arches and vaults.

P. Block, J. Ochsendorf, Lower-bound analysis of masonry vaults (2008) , pg: 25

P. Block, J. Ochsendorf, Lower-bound analysis of masonry vaults (2008) , pg: 26

CATALOGUE OF COMPONENT ARRANGEMENTS Folding Techniques

Connection Design

Connector A works as a stiffener to support the bending body, while connector B1, B2, and B3 are for connnecting the individual prototype pieces to each other to be able to produce several iterations.

The components are attached to each other with nuts and screws, and the friction between the components also influences the curvature achieved

Connection Techniques

Connection Technique I: A & B1

Connection Technique I: A & B2

Connection Technique I: A & B3

CATALOGUE OF COMPONENT ARRANGEMENTS

TRIAL I

TRIAL II

TRIAL III

TRIAL IV

Introduction to AI and ML

Course Duration:6 weeks Software Used: RunwayML. Google Colab,Anaconda In response to recent integration of Artificial Intelligence within architecture, this workshop proposes a rethinking of the architectural design process by introducing nested generative design processes. A new design workflow is offered, for chaining a nested deep learning structure with generative models, to simultaneously address various stages and tasks of the architectural design process. Our approach expands the flexibility of Ai-assisted design, by proposing a series of complementary deep neural networks, establishing a logical continuity in the design decisions while also challenging and augmenting the designer’s agency. This framework encourages the adoption of machine-assisted creativity for tackling various architectural systems, including formal articulation, structural logic, and enclosure responsiveness. Through the combination of parametric and AI models for “representation learning” and “domain-transfer”, parallel iterative workflows address design at the Urban and Architectural scales, using chained supervised and unsupervised neural networks. The instructors are interested to evaluate the impact of multi-designer presence on architectural design, leveraging on the interface among various human design agents

Video Contents

Introduction to ML and Ai in Architecture , is a clip of my lectures and experimentations wrapped up around 15 mins.

Student works combined in a Playlist

AI CREATES SALVADOR DALI PAINTINGS

It is easily understood that algorithms and data have a strong integration. In this way, it is aimed to elaborate different parameters and coding systems and colors and structures. In Computer Science, the term artificial intelligence (AI) refers to any human-like intelligence exhibited by a computer, robot, or other machine. In this process, we have studied ways to create intelligent programs and machines that can creatively solve problems that have always been considered a human privilege. The rush in artificial intelligence development is likely due to the sudden availability of large amounts of data and The Associated development and wide availability of computer systems that can process all data faster and more accurately than humans. During the design process, studies were conducted in the field of deep learning or deep neural learning. The goal is to use different algorithms to follow digitization closely and to do so integrate all aspects of art with history promotional images.

Algoritmaların ve verilerin güçlü bir entegrasyona sahip olduğu kolayca anlaşılmaktadır. Bu sayede farklı parametreler ve kodlama sistemleri ile renk ve yapıların detaylandırılması hedeflenmektedir. Bilgisayar bilimlerinde, yapay zeka (AI) terimi, bir bilgisayar, robot veya başka bir makine tarafından sergilenen herhangi bir insan benzeri zekayı ifade eder. Her zaman bir insan ayrıcalığı olarak kabul edilen sorunları yaratıcı bir şekilde çözebilecek akıllı programlar ve makineler oluşturmanın yollarını bu süreçte inceledik. Yapay zeka gelişimindeki acele, büyük miktarda verinin ani mevcudiyeti ve tüm verileri insanlardan daha hızlı ve daha doğru bir şekilde işleyebilen bilgisayar sistemlerinin ilgili gelişimi ve geniş kullanılabilirliği ile muhtemeldir. Tasarım sürecinde derin öğrenme veya derin sinirsel öğrenme alanında çalışmalar yapıldı. Amaç farklı algoritmalar kullanmak dijitalleşmeyi yakınından takip etmek ve bunu yapmak sanatı tüm yönleri ile tarihe tanıklık yapmış resimlere entegre etmek olmuştur.

More than 1000 Salvador Dali pictures were processed through the StyleGAN algorithm, and the computer analyzed the morphology of these photos for new coding techniques into the making of the pictures. The resulting videos created an iterative vector in the most recent field of information collected from the dataset. And the photos were taken and shared from that secret space.

StyleGAN algoritması aracılığıyla 1000'den fazla Salvador Dali resimleri işlendi ve bilgisayar bu fotoğrafların morfolojisini resimlerin yapımına yeni kodlama teknikleri için analiz etti. Sonucunda açığa çıkan videolar, veri kümesinden toplanan bilginin en son alanında yinelemeli bir vektör oluşturdu. Ve fotoğraflar da o gizli alandan çekilip paylaşılmıştır.

AI CREATES STRUCTURES Generative modeling is an unsupervised learning task in machine learning that involves automatically discovering and learning the regularities of the input data, patterns, forms, and intonations, and can be used to create new instances that can be reasonably extracted from the original dataset of models. The system generates art by looking at art and learning about style and becomes creative by increasing the arousal potential of the generated art by deviating from the learning styles.

Üretken modelleme, girdi verilerinin, kalıpların, formların ve tonlamaların düzenliliklerinin otomatik olarak kesfedilmesini ve öğrenilmesini içeren ve orijinal model veri kümesinden makul bir şekilde çıkarılabilen yeni örnekler oluşturmak için kullanılabilen, makine öğreniminde denetimsiz bir öğrenme görevidir. Sistem, sanata bakarak ve üslup hakkında bilgi edinerek sanat üretir ve öğrenme tarzlarından saparak üretilen sanatın uyarılma potansiyelini artırarak yaratıcı hale gelir.

This study proposes a new system for producing art. The data set was created from 1000 different architectural structures was re-encoded with GAN algorithms. It is proposed to make the model capable of producing new creative art by maximizing deviation from established styles and minimizing deviation from art distribution. Their ability to produce creative products in original designs with GAN algorithms has been experienced.

Bu çalışma sanat üretmek için yeni bir sistem önermektedir. 1000 farklı mimari yapıdan oluşturulan veri seti GAN algoritmaları ile yeniden kodlanmıştır. Yerleşik tarzlardan sapmayı en üst düzeye çıkararak ve sanat dağıtımından sapmayı en aza indirerek modelin yeni yaratıcı sanat üretme yeteneğine sahip hale getirilmesi önerilmektedir. GAN algoritmalar ile özgün tasarımlarda yaratıcı ürünler üretme yetenekleri deneyimlenmiştir.

AI MERGES URBAN PLANS WITH PATTERNS IN NATURE The aim of this workshop was to use different GAN algorithms to visualize different data sets. In my research, I wanted to use different GAN algorithms to show similarities between city plans and natural patterns found in nature. I have collected city plans from all over the world, which shows their organic and grid-like structure, and have analyzed their resemblances to the patterns found in nature. These natural patterns included; the structure of an animal/plant cell, veins of a leaf, a spider web, ocean waves, sand patterns in a desert, clouds, veins found in human eye, layers of a red cabbage, tiger’s skin, bird feather, animal fur, snowflake, finger print, shattered glass…etc. Various style GANs have been used in this process to visualize the similarities between city plans and patterns in nature. Most of these yields state-of-the-art results in data-driven unconditional generative image modeling. The algorithm has exposed and analyzed several of the characteristics of both the city plans and the pattern images, and proposed changes in both model architecture and training methods to address them. Even though the result that was obtained from each GAN algorithm was different, all of them were still able to highlight the similarities between nature and city planning. The organic structure of the cities are derived from the nature itself.

Bu çalışmanın amacı farklı GAN algoritmalarını kullanarak elimizdeki verileri görselleştirmekti. Yaptığım araştırmada, farklı GAN algoritmalarını kullanarak şehir planları ile doğadaki örüntü ve desenlerin arasındaki benzerlikleri göstermek istedim. İnternetten 100’e yakın dünyanın farklı yerlerinden şehir planları toplayıp, bu planların organik ve gridal yapılarını inceledim ve daha sonra bu şehir dokularının doğadaki örüntü ve desenlerle olan benzerliklerini analiz ettim. Doğa bulduğum örüntü görselleri hayvan/bitki hücreleri, yaprak damarları, örümcek ağları, okyanus dalgaları, çöllerde kumların oluşturduğu dalga örüntüleri, gökyüzündeki bulutlar, gözdeki retina, kırmızı lahana yaprakları, kaplan kürkünün deseni, kuş tüyleri, kar taneleri, parmak izi, kırılmış çam, böcek kanatları., kuru toprak dokusu, balıkların pulları ...vb. oluşmaktadır. Farklı GAN stillerini kullanarak şehir planlarını ve doğa örüntülerini ve desenlerini birleştirip bu birleşimin görsellerini oluşturdum. Kullandığım farklı algoritmalar ile şehir planları ve doğa görselerini farklı farklı analiz edip daha sonra birbirleri arasındaki benzerlikleri gösterip, bu benzerlikleri görselleştirdim. Her ne kadar, her farklı GAN algoritmasından üretiğim görsel farklı olsada, bütüne baktığımızda şehirlerin organik dokularının aslında doğada bulunan örüntü ve desenlerden esinlenerek ortaya çıktığını görüyoruz. Çalışmanın da amacı zaten bu benzerliği görsellerştirebilmekti.

AI CREATES NATURE Intention is to generate art that does not involve a human artist in the creative process, but does involve human creative products in the learning process. An essential component in art-generating algorithms is relating their creative process to art that has been produced by human artists throughout time. I believe this is relevant becausea human’s creative process utilizes priorexperience of and exposure to art. More than 1000 nature photos were processed through the StyleGAN algortihm, and computeranalyzed the morphology of these photos torecode them into the structure of nature. Thisvideo is an iterative walking vector in the latentspace of the knowledge gathered from the data set.

Amacım, yaratıcı sürece bir sanatçıyı dahil etmeyen, ancak ögrenme sürecine insan yaratıcı ürünlerini dahil eden bir sanat yaratmaktır. Sanat üreten algoritmaların önemli bir bileşeni, yaratıcı süreçlerini zaman içinde sanatçılar tarafından üretilen sanatla ilişkilendirmektir. Bunun konuyla ilgili olduguna inanıyorum çünkü bir insanın yaratıcı süreci, sanatın önceki deneyimlerini ve maruziyetini kullanır. StyleGAN algoritması aracılıgıyla 1000'den fazla doga fotografı işlendi ve bilgisayar bu fotografların morfolojisini doganın yapısına yeniden kodlamak için analiz etti. Videolar, veri kümesinden toplanan bilginin en son alanında yinelemeli bir yürüyüş vektörüdür. Ve fotograflar da o gizli alandan çekildi.

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06 Studio Projects Course Duration: 4 weeks Software Used: Rhino,MayaZBrush,Houdini,Scripting,Adobe Suite Studio works are unique to each student, during the final month of the programme the idea was to combine every technical aspect of digital design and approach students tried to solve a problem by utilizing technology and data as a design tool and approach. Aslihan Musaoglu, analyzed Balat neighbourhood and propose a new strategy for interior design within an age of pandemic for the future developments. Ebru Mert , proposed an underground station located by the behavoiur of slime mold within a closed system. Utilizing data and displacement of population by different times of day, we analysed Istanbul traffic flow and proposed a Urban Transportation Hub. Irem Yilmazer, proposed an emergency strategy for the Istanbul earthquake in Balat region. Since the region is so dense and packed most of the roads will be unavailabel during such a disaster. The approach we took was using coast as a transportation and emergency area. Su Abac, proposed a Virtual Reality Hub, where user experiences different intensities of reality. As humans we are already living in the virtual and by looking at projects like `Fun Palace` we tried to look at reality and what architecture within a virtual discourse could achieve. Student prensentations and opening lecture could be found from the QR Code !