Ashif Sikandar Iquebal

Arizona State University — United States

Engineering · Physical Sciences

10h-index327citations51works1.82yr avg
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Research Topics

Additive Manufacturing Materials and Processes(13), Manufacturing Process and Optimization(9), Advanced Surface Polishing Techniques(8), Additive Manufacturing and 3D Printing Technologies(6), Welding Techniques and Residual Stresses(4)

Publications51 total

Complex value autoencoder for machinery audio generation
Manufacturing Letters·2025Open Access
CRONet: A convolutional recurrent operator approximator network to accelerate topology optimization
Manufacturing Letters·2025Open Access
Accelerating Point-Based Value Iteration via Active Sampling of Belief Points and Gaussian Process Regression
arXiv (Cornell University)·2025Open Access
Hypothesis Generation for Materials Discovery and Design Using Goal-Driven and Constraint-Guided LLM Agents
arXiv (Cornell University)·2025· 2 citedOpen Access
Hypothesis Generation for Materials Discovery and Design Using Goal-Driven and Constraint-Guided LLM Agents
2025· 6 citedOpen Access
Characterization of Elastoplastic Properties of Additively Manufactured Specimens From Indentation Data Using Stochastic Inverse Modeling
2024
A Bayesian Spatiotemporal Modeling Approach to the Inverse Heat Conduction Problem
ASME Journal of Heat and Mass Transfer·2024· 2 cited
Dynamic exploration–exploitation trade-off in active learning regression with Bayesian hierarchical modeling
IISE Transactions·2024· 4 cited
SCGAN: Sparse CounterGAN for Counterfactual Explanations in Breast Cancer Prediction
IEEE Transactions on Automation Science and Engineering·2023· 13 citedOpen Access
A Bayesian Spatio-Temporal Modeling Approach to the Inverse Heat Conduction Problem
2023· 4 cited
Surface plastic flow and random planar graph representation in the polishing of rough surfaces (Conference Presentation)
2023
SCGAN: Sparse CounterGAN for Counterfactual Explanations in Breast Cancer Prediction
2023· 3 citedOpen Access
Dynamic Exploration-Exploitation Trade-Off in Active Learning Regression with Bayesian Hierarchical Modeling
arXiv (Cornell University)·2023Open Access
Emulating microstructural evolution during spinodal decomposition using a tensor decomposed convolutional and recurrent neural network
Computational Materials Science·2023· 26 cited
A Novel Data-Driven Emulator for Predicting Electromigration-Mediated Damage in Polycrystalline Interconnects
Journal of Electronic Materials·2023· 2 cited
Emulating the evolution of phase separating microstructures using low-dimensional tensor decomposition and nonlinear regression
MRS Bulletin·2023· 8 cited
CEM and MR Radiomics-based Biomarkers to Predict Immunohistochemistry Breast Cancer Subtypes: A comparative study
Research Square (Research Square)·2022Open Access
Tracking and quantifying spatter characteristics in a laser directed energy deposition process using Kalman filter
Manufacturing Letters·2022· 9 citedOpen Access
Generating Counterfactual Explanations For Causal Inference in Breast Cancer Treatment Response
2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)·2022· 5 citedOpen Access
Datasets and Code for "A Gaussian process model-guided surface polishing process in additive manufacturing"
Zenodo (CERN European Organization for Nuclear Research)·2022Open Access
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Frequent Co-authors

Satish Bukkapatnam(24), Zimo Wang(5), Siqiong Zhou(5), Bhaskar Botcha(4), Upala J. Islam(4), Nicholaus Pfeiffer(4), Imon Banerjee(4), Bhavika Patel(4), Arun R. Srinivasa(4), Ridwan Olabiyi(4), Sanjay Shrestha(3), Guha Manogharan(3), Manoj Kumar Tiwari(3), Peichen Wu(3), Kumar Ankit(3), Shilan Jin(3), Andrew T. Gaynor(3), Yu Ding(3), Woo-Hyun Ko(3), Zhujiang Wang(3)