PhD Thesis 2024
Parametric-Based Models for Artistic Representations
Manuel Ladron de Guevara
PhD-CD
Advised by Ramesh Krishnamurti, Daragh Byrne
Professor, Director of the Design and Computation Research GroupCore Facultysoa.cmu.edu/ramesh-krishnamurtiramesh@cmu.edu
Ramesh Krishnamurti is Professor at Carnegie Mellon Architecture and Director of the Design and Computation Research Group (DCRG). His research focuses on computational approaches to design thinking, shape grammars, generative systems, and formal methods in architectural design.
How This Connects
3 LABS4 PROJECTS3 THEMES1 COURSES
Affiliated with
Contributed to
Teaches
Work
Research 2023–2025
Deep Time Architectural Data
Daniel Cardoso Llach
This research investigates the long-term archival and interpretation of architectural design data, exploring how computational design artifacts persist, decay, and transform acros…
Situated Computation Lab (SitCodeLab) Design and Computation Research Group (DCRG) Situated Computation & Culture
Conference Paper 2020
An Academy of Spatial Agents - Generating spatial configurations with deep reinforcement learning
Pedro Veloso, Ramesh Krishnamurti
eCAADe 2020: Anthropologic : Architecture and Fabrication in the cognitive age
Journal Article 2020
Multi-resolution in architecture as a design driver for additive manufacturing applications
Manuel Ladron de Guevara, Daragh Byrne, Ramesh Krishnamurti
International Journal of Architectural Computing
Journal Article 2019
Context-rich Urban Analysis Using Machine Learning
Jinmo Rhee, Daniel Cardoso Llach, Ramesh Krishnamurti
MS Thesis 2017
Design Games and Machine Learning: A Method for the Application of Machine Learning in Design Environments.
Michael Jeffers
MSCD
Advised by Ramesh Krishnamurti, Daniel Cardoso Llach, Joshua Bard
PhD Thesis 2024
Computational Methods for the Identification and Comparative Analysis of Urban Form Types: A Case Study of Rust Belt Cities
Jinmo Rhee
PhD-CD
Advised by Daniel Cardoso Llach, Ramesh Krishnamurti
PhD Thesis 2021
A Computational Approach to Predicting Thermal Conductivity of Construction Material: Towards Rapid In-Situ Energy Evaluation of Existing Buildings
Noreen Saeed
PhD-CD
Advised by Ramesh Krishnamurti
Conference Paper 2020
Integrating building footprint prediction and building massing - an experiment in Pittsburgh
Jinmo Rhee, Pedro Veloso, Ramesh Krishnamurti
CAADRIA 2020: RE:Anthropocene
PhD Thesis 2020
Machine Learning for Multi-Discipline Parametric Analysis in Architectural Practice
Victor Okhoya
DDeS
Advised by Ramesh Krishnamurti, Daniel Cardoso Llach
MS Thesis 2019
Context-rich Urban Analysis Using Machine Learning: A Case Study in Pittsburgh, PA
Jinmo Rhee
MSCD
Advised by Daniel Cardoso Llach, Ramesh Krishnamurti, Molly Wright Steenson, Daragh Byrne, Eddy Man Kim
PhD Thesis 2023
An Academy of Spatial Agents
Pedro Veloso
PhD-CD
Advised by Ramesh Krishnamurti
Journal Article 2020
Multimodal Word Sense Disambiguation in Creative Practice
Manuel Ladron de Guevara, Daragh Byrne, Ramesh Krishnamurti
arXiv e-prints
Conference Paper 2020
Multimodal Word Sense Disambiguation in Creative Practice
Manuel Ladron de Guevara, Daragh Byrne, Ramesh Krishnamurti
2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)
Journal Article 2019
Robotic free-oriented additive manufacturing technique for thermoplastic lattice and cellular structures
Manuel Ladron de Guevara, Jeremy Ficca, Daragh Byrne, Ramesh Krishnamurti
Proc. CAADRIA 2019
MS Thesis 2018
Architecture Narratives: Framework for Geometry Adaptation through Representations of Voxels and Tetra-Meshes
Adie Alnobani
MSCD
Advised by Daniel Cardoso Llach, Ramesh Krishnamurti