Manuel Ladron de Guevara

I'm an AI and machine learning professional with a focus on computer vision, deep learning, and product development. Rooted in a strong academic background, I am currently finalizing my PhD at Carnegie Mellon University's Computational Design department, where I specialize in innovative techniques like image synthesis, deep painting, and multimodal machine learning.

As a co-founder of tech startups Flumio and the CRAIDL platform, I've gotten hands-on experience in taking an idea from conception to market, aligning technological solutions with business objectives. I also bring instructional leadership to the table, having served as a Studio Instructor at Carnegie Mellon's School of Architecture. This role has sharpened my skills in explaining complex technical topics in an easily digestible manner—a vital asset when liaising between technical and business teams.

My industry experience is highlighted by a tenure as a research scientist intern at Adobe Research, where I contributed to the development of cutting-edge machine learning algorithms. Working under leading AI experts, I gained invaluable insights into transitioning research into scalable production solutions. This aligns well with roles that require a blend of technical depth, strategic thinking, and execution prowess.

Before diving into my PhD journey, I completed a Master's in Robotic Fabrication at Carnegie Mellon, which furnished me with a strong foundation in automation and AI-driven processes. My educational pathway began with a B-Arch and M-Arch in Architecture from the Polytechnic University of Catalonia, where I graduated with honors for my thesis project.

With a robust blend of research acumen, practical industry experience, and entrepreneurial spirit, I am well-prepared for roles as an AI Consultant, Product Manager, Research Scientist, or R&D Lead, focused on turning cutting-edge technologies into real-world solutions.

Email: manuelr [at] andrew [dot] cmu [dot] edu

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profile photo

Startups and Research Labs Founded

Flumio, the first AI driven text-to-fabrication furniture startup
Manuel Ladron de Guevara, Co-founder and CEO, Ardavan Bidgoli, Co-founder and CTO,
Pre-seed Funding, 2023
Creative AI and Design Launchapd (CRAIDL)
Manuel Ladron de Guevara, Ardavan Bidgoli, Pedro Veloso, Jinmo Rhee,
Carnegie Mellon University, 2020

Publications

Cross-modal Latent Space Alignment for Image to Avatar Translation
Manuel Ladron de Guevara, Jose Echevarria, Yijun Li, Yannick Hold-Geoffroy, Cameron Smith, Daichi Ito
Forthcoming ICCV, 2023
Design Intents Disentanglement: A Multimodal Approach for Grounding Design Attributes in Objects
Manuel Ladron de Guevara, Alexander Schneidman, Daragh Byrne, Ramesh Krisnamurti,
CAADRIA, 2022
[Paper] [Code]
Bubble2Floor: A Pedagogical Experience With Deep Learning for Floor Plan Generation
Pedro Veloso, Jinmo Rhee, Ardavan Bidgoli, Manuel Ladron de Guevara,

CAADRIA, 2022
[Paper]
MixerGAN: An MLP-Based Architecture for Unpaired Image-to-Image Translation
George Cazenavette, Manuel Ladron de Guevara,
Preprint, 2021
[Paper]
Artistic style in robotic painting; a machine learning approach to learning brushstroke from human artists
Ardavan Bidgoli, Manuel Ladron de Guevara, Cinnie Hisiung Jean Oh, Eunsu Kang
EEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2020
[Paper] [Presentation] [Video] [Code]
Multimodal Word Sense Disambiguation in Creative Practice
Manuel Ladron de Guevara, Christopher George, Akshat Gupta, Daragh Byrne, Ramesh Krisnamurti,
IEEE International Conference on Machine Learning and Applications , 2020
[Paper]
Multi-resolution in architecture as a design driver for additive manufacturing applications
Manuel Ladron de Guevara, Christopher George, Daragh Byrne, Ramesh Krisnamurti,
International Journal of Architectural Computing (IJAC), 2020
[Paper]
A multi-resolution design methodology based on discrete models
Manuel Ladron de Guevara, Luis Borunda, Ramesh Krisnamurti,
CAAD Futures, 2019
[Paper]
Robotic free-oriented additive manufacturing technique for thermoplastic lattice and cellular structures
Manuel Ladron de Guevara, Luis Borunda, Jeremy Ficca Daragh Byrne, Ramesh Krisnamurti,
CAADRIA, 2019
[Paper]
Design Method for Optimized Infills in Additive Manufacturing Thermoplastic Components
Luis Borunda, Manuel Ladron de Guevara, Jesus Anaya
eCAADE, 2019
[Paper]
Optimized Additive Manufacturing Building Components
Luis Borunda, Manuel Ladron de Guevara, Gianluca Pugliese, Rafael Claramunt, Marta Muñoz, Jesus Anaya
IV International Conference on Technological Innovation in Building, 2019
[Paper]

Commisioned Architecture Work

Principal Architect , Design and Construction Management of a Single Family House, Spain | 2015

Education

Carnegie Mellon University, Pittsburgh, Pennsylvania
Ph.D. in Computational Design | 2018 - Present ,
Carnegie Mellon University, Pittsburgh, Pennsylvania
Masters in Advanced Architectural Design | 2017 - 2018 ,
Polytechnic University of Catalonia, Barcelona, Spain
B.Arch - M.arch in Architecture | 2007 - 2013 ,

Relevant Coursework

10-601 - Machine Learning | Fall 2019 Instructor: Matt Gormley

10-737 - Creative AI | Fall 2019 Instructor: Eunsu Kang & Jean Oh

10-403 - Deep Reinforcement Learning | Spring 2020 Instructor: Katerina Fragkiadaki
11-785 - Introduction to Deep Learning | Spring 2020 | Instructor: Bhiksha Raj

11-611 - Natural Language Processing | Spring 2020 | Instructor: Alan W. Black & David R. Mortensen

11-777 - Multimodal Machine Learning | Fall 2020 | Instructor: Louis-Philippe Morency

11-747 - Neural Networks for NLP | Spring 2021 | Instructor: Graham Neubig

16-726 - Learning-Based Image Synthesis | Spring 2021 | Instructor: Jun-Yan Zhu

16-824 - Visual Learning & Recognition | Fall 2021 | Instructor: Jun-Yan Zhu

Website source from Jon Barron .