Parnian Afshar

39 papers B 6Misc 4Journal 27Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Forget to Know, Remember to Use: Context-Aware Unlearning for Large Language Models. CoRR Yuefeng Peng, Parnian Afshar, Megan Ganji, Thomas Butler, Amir Houmansadr, Mingxian Wang, Dezhi Hong
2025	J	`jnl`	Lung Nodule Malignancy Classification Integrating Deep and Radiomic Features in a Three-Way Attention-Based Fusion Module. J. Imaging Sadaf Khademi, Shahin Heidarian, Parnian Afshar, Arash Mohammadi, Abdul Sidiqi, Elsie T. Nguyen, Balaji Ganeshan, Anastasia Oikonomou
2023	J	`jnl`	Improving the Accuracy of Beauty Product Recommendations by Assessing Face Illumination Quality. CoRR Parnian Afshar, Jenny Yeon, Andriy Levitskyy, Rahul Suresh, Amin Banitalebi-Dehkordi
2023	Misc	`conf`	Spatio-Temporal Hybrid Fusion of CAE and SWin Transformers for Lung Cancer Malignancy Prediction. ICASSP Sadaf Khademi, Shahin Heidarian, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2022	J	`jnl`	Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark. CoRR Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis, Keyvan Farahani, Justin S. Kirby, Anastasia Oikonomou, Amir Asif, Leonard Wee, Andre Dekker, Xin Wu, Mohammad Ariful Haque, Shahruk Hossain, Md. Kamrul Hasan, Uday Kamal, Winston H. Hsu, Jhih-Yuan Lin, M. Sohel Rahman, Nabil Ibtehaz, Sh. M. Amir Foisol, Kin-Man Lam, Zhong Guang, Runze Zhang, Sumohana S. Channappayya, Shashank Gupta, Chander Dev
2022	J	`jnl`	Spatio-Temporal Hybrid Fusion of CAE and SWIn Transformers for Lung Cancer Malignancy Prediction. CoRR Sadaf Khademi, Shahin Heidarian, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2021	J	`jnl`	CAE-Transformer: Transformer-based Model to Predict Invasiveness of Lung Adenocarcinoma Subsolid Nodules from Non-thin Section 3D CT Scans. CoRR Shahin Heidarian, Parnian Afshar, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2021	J	`jnl`	COVID-FACT: A Fully-Automated Capsule Network-Based Framework for Identification of COVID-19 Cases from Chest CT Scans. Frontiers Artif. Intell. Shahin Heidarian, Parnian Afshar, Nastaran Enshaei, Farnoosh Naderkhani, Moezedin Javad Rafiee, Faranak Babaki Fard, Kaveh Samimi, Seyed Farokh Atashzar, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2021	J	`jnl`	COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans. CoRR Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee, Parnian Afshar, Shahin Heidarian, Arash Mohammadi, Konstantinos N. Plataniotis, Farnoosh Naderkhani
2021	Misc	`conf`	Ct-Caps: Feature Extraction-Based Automated Framework for Covid-19 Disease Identification From Chest Ct Scans Using Capsule Networks. ICASSP Shahin Heidarian, Parnian Afshar, Arash Mohammadi, Moezedin Javad Rafiee, Anastasia Oikonomou, Konstantinos N. Plataniotis, Farnoosh Naderkhani
2021	J	`jnl`	Diagnosis/Prognosis of COVID-19 Chest Images via Machine Learning and Hypersignal Processing: Challenges, opportunities, and applications. IEEE Signal Process. Mag. Arash Mohammadi, Yingxu Wang, Nastaran Enshaei, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Moezedin Javad Rafiee, Helder Cesar Rodigues de Oliveira, Svetlana N. Yanushkevich, Konstantinos N. Plataniotis
2021	J	`jnl`	Human-level COVID-19 Diagnosis from Low-dose CT Scans Using a Two-stage Time-distributed Capsule Network. CoRR Parnian Afshar, Moezedin Javad Rafiee, Farnoosh Naderkhani, Shahin Heidarian, Nastaran Enshaei, Anastasia Oikonomou, Faranak Babaki Fard, Reut Anconina, Keyvan Farahani, Konstantinos N. Plataniotis, Arash Mohammadi
2021	B	`conf`	Hybrid Deep Learning Model For Diagnosis Of Covid-19 Using Ct Scans And Clinical/Demographic Data. ICIP Parnian Afshar, Shahin Heidarian, Farnoosh Naderkhani, Moezedin Javad Rafiee, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2021	J	`jnl`	MIXCAPS: A capsule network-based mixture of experts for lung nodule malignancy prediction. Pattern Recognit. Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Moezedin Javad Rafiee, Arash Mohammadi, Konstantinos N. Plataniotis
2021	J	`jnl`	Robust Automated Framework for COVID-19 Disease Identification from a Multicenter Dataset of Chest CT Scans. CoRR Shahin Heidarian, Parnian Afshar, Nastaran Enshaei, Farnoosh Naderkhani, Moezedin Javad Rafiee, Anastasia Oikonomou, Akbar Shafiee, Faranak Babaki Fard, Konstantinos N. Plataniotis, Arash Mohammadi
2020	J	`jnl`	BayesCap: A Bayesian Approach to Brain Tumor Classification Using Capsule Networks. IEEE Signal Process. Lett. Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis
2020	—	`conf`	BoostCaps: A Boosted Capsule Network for Brain Tumor Classification. EMBC Parnian Afshar, Konstantinos N. Plataniotis, Arash Mohammadi
2020	J	`jnl`	COVID-CAPS: A Capsule Network-based Framework for Identification of COVID-19 cases from X-ray Images. CoRR Parnian Afshar, Shahin Heidarian, Farnoosh Naderkhani, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2020	J	`jnl`	COVID-CAPS: A capsule network-based framework for identification of COVID-19 cases from X-ray images. Pattern Recognit. Lett. Parnian Afshar, Shahin Heidarian, Farnoosh Naderkhani, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2020	J	`jnl`	COVID-CT-MD: COVID-19 Computed Tomography (CT) Scan Dataset Applicable in Machine Learning and Deep Learning. CoRR Parnian Afshar, Shahin Heidarian, Nastaran Enshaei, Farnoosh Naderkhani, Moezedin Javad Rafiee, Anastasia Oikonomou, Faranak Babaki Fard, Kaveh Samimi, Konstantinos N. Plataniotis, Arash Mohammadi
2020	J	`jnl`	COVID-FACT: A Fully-Automated Capsule Network-based Framework for Identification of COVID-19 Cases from Chest CT scans. CoRR Shahin Heidarian, Parnian Afshar, Nastaran Enshaei, Farnoosh Naderkhani, Anastasia Oikonomou, Seyed Farokh Atashzar, Faranak Babaki Fard, Kaveh Samimi, Konstantinos N. Plataniotis, Arash Mohammadi, Moezedin Javad Rafiee
2020	J	`jnl`	CT-CAPS: Feature Extraction-based Automated Framework for COVID-19 Disease Identification from Chest CT Scans using Capsule Networks. CoRR Shahin Heidarian, Parnian Afshar, Arash Mohammadi, Moezedin Javad Rafiee, Anastasia Oikonomou, Konstantinos N. Plataniotis, Farnoosh Naderkhani
2020	J	`jnl`	Diagnosis/Prognosis of COVID-19 Images: Challenges, Opportunities, and Applications. CoRR Arash Mohammadi, Yingxu Wang, Nastaran Enshaei, Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Moezedin Javad Rafiee, Helder Cesar Rodigues de Oliveira, Svetlana N. Yanushkevich, Konstantinos N. Plataniotis
2020	Misc	`conf`	MDR-SURV: A Multi-Scale Deep Learning-Based Radiomics for Survival Prediction in Pulmonary Malignancies. ICASSP Parnian Afshar, Anastasia Oikonomou, Konstantinos N. Plataniotis, Arash Mohammadi
2020	J	`jnl`	MIXCAPS: A Capsule Network-based Mixture of Experts for Lung Nodule Malignancy Prediction. CoRR Parnian Afshar, Farnoosh Naderkhani, Anastasia Oikonomou, Moezedin Javad Rafiee, Arash Mohammadi, Konstantinos N. Plataniotis
2019	Misc	`conf`	Capsule Networks for Brain Tumor Classification Based on MRI Images and Coarse Tumor Boundaries. ICASSP Parnian Afshar, Konstantinos N. Plataniotis, Arash Mohammadi
2019	B	`conf`	Capsule Networks' Interpretability for Brain Tumor Classification Via Radiomics Analyses. ICIP Parnian Afshar, Konstantinos N. Plataniotis, Arash Mohammadi
2019	J	`jnl`	From Handcrafted to Deep-Learning-Based Cancer Radiomics: Challenges and opportunities. IEEE Signal Process. Mag. Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis, Anastasia Oikonomou, Habib Benali
2019	J	`jnl`	Lung Cancer Radiomics: Highlights from the IEEE Video and Image Processing Cup 2018 Student Competition [SP Competitions]. IEEE Signal Process. Mag. Arash Mohammadi, Parnian Afshar, Amir Asif, Keyvan Farahani, Justin S. Kirby, Anastasia Oikonomou, Konstantinos N. Plataniotis
2018	J	`jnl`	A hierarchical stochastic modelling approach for reconstructing lung tumour geometry from 2D CT images. J. Exp. Theor. Artif. Intell. Parnian Afshar, Abbas Ahmadi, Azadeh Mohebi, M. H. Fazel Zarandi
2018	B	`conf`	Brain Tumor Type Classification via Capsule Networks. ICIP Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis
2018	J	`jnl`	Brain Tumor Type Classification via Capsule Networks. CoRR Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis
2018	B	`conf`	CARISI: Convolutional Autoencoder-Based Inter-Slice Interpolation of Brain Tumor Volumetric Images. ICIP Parnian Afshar, Atefeh Shahroudnejad, Arash Mohammadi, Konstantinos N. Plataniotis
2018	J	`jnl`	Capsule Networks for Brain Tumor Classification based on MRI Images and Course Tumor Boundaries. CoRR Parnian Afshar, Konstantinos N. Plataniotis, Arash Mohammadi
2018	J	`jnl`	From Hand-Crafted to Deep Learning-based Cancer Radiomics: Challenges and Opportunities. CoRR Parnian Afshar, Arash Mohammadi, Konstantinos N. Plataniotis, Anastasia Oikonomou, Habib Benali
2018	—	`conf`	Improved Explainability of Capsule Networks: Relevance Path by Agreement. GlobalSIP Atefeh Shahroudnejad, Parnian Afshar, Konstantinos N. Plataniotis, Arash Mohammadi
2016	B	`conf`	Conceptual Framework for RoboDoc: A New Social Robot for Research Assistantship. ICSR Azadeh Mohebi, Ramin Golshaie, Soheil Ganjefar, Ammar Jalalimanesh, Parnian Afshar, Ali Aali Hosseini, Seyyed Alireza Ghoreishi, Amir Badamchi
2016	J	`jnl`	Intelligent breast cancer recognition using particle swarm optimization and support vector machines. J. Exp. Theor. Artif. Intell. Abbas Ahmadi, Parnian Afshar
2016	B	`conf`	Lung tumor area recognition in CT images based on Gustafson-Kessel clustering. FUZZ-IEEE Parnian Afshar, Abbas Ahmadi, M. H. Fazel Zarandi

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.