Minimizing thermally induced interfacial shearing stress in a thermoelectric module with low fractional area coverage. - Amirkoushyar Ziabari; Ephraim Suhir; Ali Shakouri (Microelectron. J., 2014)

Power Blurring: Fast Static and Transient Thermal Analysis Method for Packaged Integrated Circuits and Power Devices. - Amirkoushyar Ziabari; Je-Hyoung Park; Ehsan K. Ardestani; Jose Renau; Sung-Mo Kang; Ali Shakouri (IEEE Trans. Very Large Scale Integr. Syst., 2014)

Finite element and imaging approaches to analyze multiscale electrothermal phenomena - Amirkoushyar Ziabari (2016)

Physics based modeling for the development of soft segmentation and reconstruction algorithms. - Amirkoushyar Ziabari; Jeffrey M. Rickman; Jeffrey P. Simmons; Charles A. Bouman (ACSSC, 2017)

2.5D Deep Learning For CT Image Reconstruction Using A Multi-GPU Implementation. - Amirkoushyar Ziabari; Dong Hye Ye; Somesh Srivastava; Ken D. Sauer; Jean-Baptiste Thibault; Charles A. Bouman (ACSSC, 2018)

A 2.5d Yolo-Based Fusion Algorithm for 3d Localization Of Cells. - Amirkoushyar Ziabari; Derek C. Rose; Matthew R. Eicholtz; David J. Solecki; Abbas Shirinifard (ACSSC, 2019)

A Two-Tier Convolutional Neural Network for Combined Detection and Segmentation in Biological Imagery. - Amirkoushyar Ziabari; Abbas Shirinifard; Matthew R. Eicholtz; David J. Solecki; Derek C. Rose (GlobalSIP, 2019)

PABO: Pseudo Agent-Based Multi-Objective Bayesian Hyperparameter Optimization for Efficient Neural Accelerator Design. - Maryam Parsa; Aayush Ankit; Amirkoushyar Ziabari; Kaushik Roy 001 (ICCAD, 2019)

X-Ray CT Reconstruction of Additively Manufactured Parts using 2.5D Deep Learning MBIR. - Amirkoushyar Ziabari; Michael Kirka; Vincent C. Paquit; Philip R. Bingham; Singanallur V. Venkatakrishnan (CoRR, 2019)

Physics-Based Regularizer for Joint Soft Segmentation and Reconstruction of Electron Microscopy Images of Polycrystalline Microstructures. - Amirkoushyar Ziabari; Jeffrey M. Rickman; Lawrence F. Drummy; Jeffrey P. Simmons; Charles A. Bouman (IEEE Trans. Computational Imaging, 2019)

Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. - Maryam Parsa; Catherine D. Schuman; Nitin Rathi; Amirkoushyar Ziabari; Derek C. Rose; J. Parker Mitchell; J. Travis Johnston; Bill Kay; Steven R. Young; Kaushik Roy 001 (ICONS, 2021)

Convolutional neural network based non-iterative reconstruction for accelerating neutron tomography. - Singanallur V. Venkatakrishnan; Amirkoushyar Ziabari; Jacob D. Hinkle; Andrew W. Needham; Jeffrey M. Warren; Hassina Z. Bilheux (Mach. Learn. Sci. Technol., 2021)

Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction. - Amirkoushyar Ziabari; Singanallur V. Venkatakrishnan; Abhishek Dubey; Alex Lisovich; Paul Brackman; Curtis Frederick; Pradeep Bhattad; Philip R. Bingham; Alex Plotkowski; Ryan Dehoff; Vincent C. Paquit (ICIP, 2022)

Algorithm-Driven Advances for Scientific CT Instruments: From model-based to deep learning-based approaches. - S. V. Venkatakrishnan 001; K. Aditya Mohan; Amirkoushyar Ziabari; Charles A. Bouman (IEEE Signal Process. Mag., 2022)

Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications. - Muralikrishnan Gopalakrishnan Meena; Amirkoushyar Ziabari; Singanallur V. Venkatakrishnan; Isaac Lyngaas; Matthew R. Norman; Bálint Joó; Thomas L. Beck; Charles A. Bouman; Anuj J. Kapadia; Xiao Wang 004 (High Performance Computing for Imaging, 2023)

Deep Learning Based Workflow for Accelerated Industrial X-Ray Computed Tomography. - Obaidullah Rahman; Singanallur V. Venkatakrishnan; Luke Scime; Paul Brackman; Curtis Frederick; Ryan Dehoff; Vincent C. Paquit; Amirkoushyar Ziabari (ICIP, 2023)

2.5D Super-Resolution Approaches for X-Ray Computed Tomography-Based Inspection of Additively Manufactured Parts. - Haley Duba-Sullivan; Obaidullah Rahman; Singanallur V. Venkatakrishnan; Amirkoushyar Ziabari (IEEECONF, 2024)

Edge Projection-Based Adaptive View Selection for Cone-Beam CT. - Jingsong Lin; Singanallur V. Venkatakrishnan; Gregery T. Buzzard; Amirkoushyar Ziabari; Charles A. Bouman (IEEECONF, 2024)

Adapting Segment Anything Model (SAM) to Experimental Datasets via Fine-Tuning on GAN-based Simulation: A Case Study in Additive Manufacturing. - Anika Tabassum; Amirkoushyar Ziabari (CoRR, 2024)

YOLO2U-Net: Detection-guided 3D instance segmentation for microscopy. - Amirkoushyar Ziabari; Derek C. Rose; Abbas Shirinifard; David J. Solecki (Pattern Recognit. Lett., 2024)

A Learnt Half-Quadratic Splitting-Based Algorithm for Fast and High-Quality Industrial Cone-beam CT Reconstruction. - Aniket Pramanik; Singanallur V. Venkatakrishnan; Obaidullah Rahman; Amirkoushyar Ziabari (CoRR, 2025)

A Fast, Scalable, and Robust Deep Learning-based Iterative Reconstruction Framework for Accelerated Industrial Cone-beam X-ray Computed Tomography. - Aniket Pramanik; Obaidullah Rahman; Singanallur V. Venkatakrishnan; Amirkoushyar Ziabari (CoRR, 2025)

Plug-and-Play with 2.5D Artifact Reduction Prior for Fast and Accurate Industrial Computed Tomography Reconstruction. - Haley Duba-Sullivan; Aniket Pramanik; S. V. Venkatakrishnan 001; Amirkoushyar Ziabari (CoRR, 2025)