Ray Harli's Portfolio

SELECTED WORKS ARCHITECTURE, URBAN DESIGN + RESEARCH & DEVELOPMENT

Portfolio RAY HARLI Address

Contact

Address: 9 Tudor Road, Barnet

Web: LinkedIn

London EN5 5NL

Email: rharli@gmail.com

United Kingdom

Phone: +44 786 137 3451

01 Selected Works

ARCHITECTURE

National Marine Research Institute A state-of-the-art research center was developed with cutting edge facilities that enhanced vital national marine research and development services.

CLIENT:

The Marine Institute

LOCATION Summary

Oranmore

Country Galway, Ireland

A large office complex to house the state agency responsible for marine research, technology development and innovation in Ireland. It is an extensive scheme to house marine scientists and their associated functions including offices, auditoriums, libraries and research laboratories.

The latest concepts and innovations in office and laboratory design were incorporated in order to meet specialist international accreditation requirements.

Portfolio | 01

SIZE

51,200 sq.m

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The institute carries out environmental, fisheries, and aquaculture surveys and monitoring programmes to meet Ireland’s national and international legal requirements. They provide scientific and technical advice to Government to help inform policy and to support the sustainable development of Ireland’s marine resource.

Portfolio | 04

State Laboratories Project Goal

This is the Irish Government’s principal chemistry laboratory and provides a comprehensive analytical and advisory service to clients across a range of different disciplines

Portfolio | 05

Summary The complex brought together a number of different laboratories having a variety of functions into the one building. Ray played a key role in the production of tender drawings and detailed technical designs. As part of this project he initiated the implementation and use of Building Information Modeling (Revit) to assist in streamlining the design and production process.

CLIENT

Department of Agriculture, Food + Marine

LOCATION

County Kildare Ireland

SIZE

9,550 sq. m

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Moses Mabhida Station Project Goal

An ambition for the station was to integrate architectural vision, civic identity and urban context within the rigorous requirements of passenger flows and operational demands.

Summary Ray played a key role as lead architect on the successful delivery of the new award winning train station which was central to the 2010 World Cup events held at the adjacent football stadium. The station combines the highest international standards of comfort, ease of movement, visibility and security.

Portfolio| 12

CLIENT

LOCATION

South Africa

South Africa

Passenger Rail Agency of

Durban,

SIZE

25,000 sq. m

Portfolio| 13

Johannesburg International Transport Interchange Project Goal

The success of any transportation hub rests in its ability to connect multiple modes of transport within a compact area.

Summary A new state-of-the-art, multi-modal mixed-use transport hub, encompassing retail, office, recreational, and storage facilities. Centrally located in Johannesburg’s inner-city, this project integrates comprehensive long-distance bus and rail facilities. My role as lead development manager involved innovative design solutions and strategic planning, contributing significantly to the cities public transport network enhancement. The project stands as a testament to modern urban infrastructure development, offering a seamless, efficient transit experience.

Portfolio | 14

CLIENT

Department of Transport

LOCATION

Johannesburg,

SIZE

52,000 sq. m

South Africa

Portfolio | 15

Prior to developing the concept scheme the design team invested a significant amount of time to research the local dynamics and inner workings of the site’s immediate setting. It was of paramount importance to ensure that the scheme would seamlessly integrate into the urban context and work in unison with the complex surrounds.

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One of the most significant designs challenges was to safely harmonize the movement of taxis, buses, and pedestrians all under one roof. In order to assist with this process a series of high tech vehicular and pedestrian traffic models were developed. This allowed us to simulate flows and address bottlenecks up front. Entrances and exists needed to be carefully considered.

Portfolio | 17

Police Stations Project Goal

Ray made a noteworthy contribution to the development and realisation of the Police Building Programme in Ireland.

Summary He was project architect from inception through to completion on several large stations involving of a number of specialised office, security and administrative related functions.

Some of the sites were of great historical importance and as such an extensive amount of research and conservational work was carried out in order to ensure that the designs seamlessly responded to the sensitive urban fabric.

CLIENT An Garda Síochána, National Security Service of Ireland

LOCATION Dublin, Ireland

SIZE

4350 - 23,200 sq.m

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Another crucial aspect is the emphasis on sustainability and adaptability. The stations incorporated environmentally friendly design elements such as energy-efficient lighting, heating, and cooling systems, and the use of sustainable building materials.

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One fundamental principle was the creation of a welcoming yet secure environment. This was achieved through the use of transparent materials and open layouts in public areas, fostering a sense of accessibility and trust between the police and the community.

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02 Selected Works

URBAN DESIGN

Tshwane Masterplan Project Goal

The strategic masterplan and implementation framework offered to guide the regeneration of South Africa’s capital city.

Summary Ray formed part of the architectural team on this project which provided a detailed masterplan and urban framework for several large government office precincts within the inner city and the immediate surrounding areas of the City of Tshwane. The masterplan was commissioned as an ambitious, overarching framework document to guide the evolution of the entire city.

CLIENT

City of Tshwane

LOCATION

Tshwane, South Africa

SIZE

38.8 Hectares

Portfolio | 09

03 Selected Projects

Computational Innovation

Model Integrity Dash European Union Offices warnings per MB

400

4.00 6.00

2.00

842

0

200

800

418

8.00 0

total warnings

400,000

600

1000

file size in MB

elements performance

423

model groups

11k

detail groups

CAD imports

200,000

800,000

201k

0

521

in-place families

55

duplicates

2156

total views

1531

hidden elements

links

0

skp imports

200

800

932

1mil 0

total placed elements

600

1000

purgable elements

views

imports

6

400

600,000

742

custom obj styles

15

raster images

6

revit links

2521

not on sheets

155 sheets

worksets & options

0

cad links

8

worksets

3

design options

Using Machine Learning and AI in urban and architectural processes Firefly

Fumbrella

This research seeks to harness the power of dronebased photogrammetry and artificial intelligence to create a low-cost urban wildfire diagnostic tool.

By interpreting this data with AI, the aim was to identify, categorize, and diagnose urban structural and environmental issues effectively, ultimately promoting sustainable urban development. web-link

The Fumbrella project is an urban installation concept designed to tackle water and energy crises. It merges a funnel and umbrella structure to collect water and sunlight. Users can customise Fumbrella designs through a web app, adjusting variables like height and funnel size. The app outputs details such as water collection potential, material costs, and covered area. This innovative approach integrates urban design with sustainability, offering a practical tool for resource harvesting in city environments. web-link

Adappt The Addappt project, developed at the Institute for Advanced Architecture of Catalonia (IAAC), is a computational tool designed to help architects assess the adaptability of building designs in the early stages. Using geometrical data and machine learning, it analyses factors like building depth, shape, and structural grid to determine how adaptable a design is. The tool provides real-time feedback, highlighting adaptable designs in green and non-adaptable ones in red, facilitating more sustainable, flexible architectural solutions. web-link

Bio-Inspired Structures The Performative Bio-Inspired Structures project, developed at IAAC, explores using biological principles like cellular autonomy for architectural form generation. It leverages computational design and tools such as Karamba to create structures that evolve and adapt in response to environmental and functional demands.

The project focuses on how buildings can embody evolutionary processes, resulting in innovative, complex forms that enhance structural performance and sustainability. web-link

Routable This research makes use of Graph Machine Learning to provide accessible route planning for people with disabilities. It offers information on accessible routes, transportation options, and points of interest for individuals in unfamiliar environments. web-link 4Sight The 4sight project, developed at IAAC, uses machine learning to predict the impact of new urban infrastructure on city areas and property values. It processes vast amounts of urban data and presents insights through a user-friendly interface, helping stakeholders like citizens, planners, and investors understand how changes might affect urban environments. By evaluating factors like land use, transport, and amenities, the tool facilitates more balanced city development. web-link

Bio-Inspired Structures Cellular autonomy for form generation The Performative Bio-Inspired Structures project, developed at IAAC, explores using biological principles like cellular autonomy

for architectural form generation. It leverages computational

design and tools such as Karamba to create structures that evolve and adapt in response to environmental and functional demands. The project focuses on how buildings can embody

evolutionary processes, resulting in innovative, complex forms that enhance structural performance and sustainability.

Click here to link to more info

4SIGHT App Description

Using Machine Learning to Analyse Urban Data The 4sight project, developed at IAAC, uses machine learning to predict the impact of new urban infrastructure on city areas and property values. It processes vast amounts of urban data and presents insights through a user-friendly interface, helping stakeholders like citizens, planners, and investors understand how changes might affect urban environments. By evaluating factors like land use, transport, and amenities, the tool facilitates more balanced city development.

Click here to link to more info

2019/01/22

Page 1

Bulk Square Meters phase 2

phase 1

% by Usage

Resi Type Breakdown

377K (40.01%)

43

Educational

272K (28.85%)

31

0

phase 3

Resi Type C

Light Industrial

29

Residential

15

Recreational

0 27

Sum(Table1 ...

10 Resi Type D

Office

0 Resi Type A Resi Type B

6 0

10

20

99 0

293K (31.14%)

9

0 12

Retail

14

Phases

30

Column1 and Column3

1/1

Fire Spread Analysis

FIREFLY

vegetation 1

convert point cloud to data frame create a data structure that can be processed.

2

Density-Based Spatial Clust er ing perform clustering using DBSCAN algorithm (SKlearn).

3

Calculate cluster c e nt r o ids group by cluster and calculate mean coordinates

4

create spat ial index of centroids using KDTree efficiently query distances between clusters

5

construct a graph

each node represents a vegetation cluster, and each edge represents a possible path for fire spread.

7

v isualise back to original point cloud

6

analyse no. of de gr e e s pe r no de

label problematic clusters (red) and overlay to original point cloud visual clusters that have many connections marked as "hotspots" for fire spread, the darker the red the more connections or 'degrees' that it has

Link to live html file

FIREFLY

Back End Workflow 5

4

3

2

1 Data Capture

3D reconstruction

Mesh to Point Cloud

Point Cloud Refinement

Semantic Segmentation

entry level drones

Photogrammetry

Open 3D / Pymesh

Down sampling

Define PointNet++ Model

Clean Mesh

trim outliers

Specify Training Options

low-tech non-lidar

Define sampling

autonomous drone missions

Train Model Segment Point Cloud Evaluate Results

Front End Workflow A

Input lo cat io n: The user inputs a specific urban location they're interested in assessing.

Generate drone route: Based on the provided location, our system generates an optimized route for drone flight.

Key Extraction

Paths

Dr o ne flight & dat a capt ur e: The user uses their drone to fly the generated route, capturing point cloud data of the urban area.

C

U plo ad dat a: The user uploads the captured photographs to our cloud platform.

D

Dat a P r o cessing: Our algorithms analyse and process the mesh and points clouds.

Providing a basis for the in-depth analytics

E

F

P r eventive m easur es assessm ent : Based on the analysis, our system proposes a set of preventive measures to mitigate the risk of fire spread.

O ut put : The user receives an in-depth report on potential fire spread zones and suggested preventive actions.

6

Vegetation Vegetation

Clusters

Normal angles Normal faces

8 Summary Risk Report

Slope & Aspect

Poisson surface

distances

B

7

Density

Buildings Ground Points

Define Grid Compute Heights

Building Density

Contour Densities

OpenWeather API

UV unwrap Segment (SAM)

Pressure

Materials Analysis Humidity

Object Detection (DINO) Area + Risk Calculations

3D Object Detection

Wind Speed Temperature Precipitation

Hello, I'm Ray Ray Harli is an architect focused on the intersection of technology, design, and development economics with computational, architectural and property development degrees. He is a licensed architect in the UK, Ireland and South Africa and has successfully completed several award-winning mega projects. He has extensive experience in a broad range of sectors including: residential, retail, commercial, industrial, healthcare, educational, transitorientated-developments, masterplanning, renovation and sustainability, showcasing his versatility and depth across both local and global landscapes.

Ray is a recognised industry leader having pioneered the integration of AI and machine learning within the architectural field, setting new benchmarks for innovation and efficiency and has assisted in the creation of commercially successful VR apps now used by the industry and academia.

RAY HARLI Address

Contact

Address: 9 Tudor Road, Barnet

Web: LinkedIn

London

Email: rharli@gmail.com

EN5 5NL

Curriculum Vitae

United Kingdom

Phone: +44 786 137 3451