activity
20172021
most citedProtofold II: Enhanced Model and Implementation for Kinetostatic Protein Folding

16 citations · 52 across the 7 of their papers we have counts for

collaborators

9 papers

cs.LG2021

GANTL: Towards Practical and Real-Time Topology Optimization with Conditional GANs and Transfer Learning

Mohammad Mahdi Behzadi, Horea T. Ilies

Many machine learning methods have been recently developed to circumvent the high computational cost of the gradient-based topology optimization. These methods typically require ex…

cs.LG20211 cited

Real-Time Topology Optimization in 3D via Deep Transfer Learning

MohammadMahdi Behzadi, Horea T. Ilies

The published literature on topology optimization has exploded over the last two decades to include methods that use shape and topological derivatives or evolutionary algorithms fo…

cs.CG2018

Practical Shape Analysis and Segmentation Methods for Point Cloud Models

Reed M. Williams, Horea T. Ilieş

Current point cloud processing algorithms do not have the capability to automatically extract semantic information from the observed scenes, except in very specialized cases. Furth…

cs.HC2017

Haptic Assembly and Prototyping: An Expository Review

Morad Behandish, Horea T. Ilies

An important application of haptic technology to digital product development is in virtual prototyping (VP), part of which deals with interactive planning, simulation, and verifica…

cs.CG20173 cited

Shape Complementarity Analysis for Objects of Arbitrary Shape

Morad Behandish, Horea T. Ilies

The basic problem of shape complementarity analysis appears fundamental to applications as diverse as mechanical design, assembly automation, robot motion planning, micro- and nano…

cs.CE201716 cited

Protofold II: Enhanced Model and Implementation for Kinetostatic Protein Folding

Pouya Tavousi, Morad Behandish, Horea T. Ilies +1

A reliable prediction of 3D protein structures from sequence data remains a big challenge due to both theoretical and computational difficulties. We have previously shown that our…