Tamoghna Chattopadhyay

19 papers Journal 4Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Multi-modal Imputation for Alzheimer's Disease Classification. CoRR Abhijith Shaji, Tamoghna Chattopadhyay, Sophia I. Thomopoulos, Greg Ver Steeg, Paul M. Thompson, José Luis Ambite
2025	J	`jnl`	Diffusion Bridge Models for 3D Medical Image Translation. CoRR Shaorong Zhang, Tamoghna Chattopadhyay, Sophia I. Thomopoulos, José Luis Ambite, Paul M. Thompson, Greg Ver Steeg
2025	J	`jnl`	ERMoE: Eigen-Reparameterized Mixture-of-Experts for Stable Routing and Interpretable Specialization. CoRR Anzhe Cheng, Shukai Duan, Shixuan Li, Chenzhong Yin, Mingxi Cheng, Heng Ping, Tamoghna Chattopadhyay, Sophia I. Thomopoulos, Shahin Nazarian, Paul M. Thompson, Paul Bogdan
2025	—	`conf`	Evaluation of Deep Learning Algorithms to Predict Multiple Dementia-Related Neuropathologies from Brain MRI, Clinical and Genetic Data. SIPAIM Tamoghna Chattopadhyay, Rudransh Kush, Pavithra Senthilkumar, Christopher Patterson, Conor Owens-Walton, Emma J. Gleave, Sophia I. Thomopoulos, Sterling C. Johnson, Elizabeth C. Mormino, Timothy J. Hohman, Paul M. Thompson
2025	—	`conf`	Generating diffusion MRI scalar maps from T1-weighted images using Reversible GANs. SIPAIM Tamoghna Chattopadhyay, Gautam Mehendale, Sophia I. Thomopoulos, Himanshu Joshi, Ganesan Venkatasubramanian, John P. John, José Luis Ambite, Greg Ver Steeg, Paul M. Thompson
2025	—	`conf`	Predicting Longitudinal Cognitive Decline via Multimodal Deep Learning Fusing Brain MRI and Clinical Data. SIPAIM Tamoghna Chattopadhyay, Pavithra Senthilkumar, Rahul H. Ankarath, Christopher Patterson, Emma J. Gleave, Sophia I. Thomopoulos, Heng Huang, Li Shen, Lei You, Degui Zhi, Paul M. Thompson
2025	—	`conf`	Using Diffusion Transformers to Generate Synthetic Diffusion Scalar Maps for Data Augmentation. SIPAIM Tamoghna Chattopadhyay, Chirag Jagad, Pavithra Senthilkumar, Sophia I. Thomopoulos, Julio E. Villalon-Reina, Paul M. Thompson
2024	—	`conf`	Brain Age Analysis and Dementia Classification using Convolutional Neural Networks trained on Diffusion MRI: Tests in Indian and North American Cohorts. EMBC Tamoghna Chattopadhyay, Neha Ann Joshy, Saket Ozarkar, Ketaki Buwa, Yixue Feng, Emily Laltoo, Sophia I. Thomopoulos, Julio Villalon, Himanshu Joshi, Ganesan Venkatasubramanian, John P. John, Paul M. Thompson
2024	—	`conf`	Comparison of Explainable AI Models for MRI-Based Alzheimer's Disease Classification. SIPAIM Tamoghna Chattopadhyay, Neha Ann Joshy, Chirag Jagad, Emma J. Gleave, Sophia I. Thomopoulos, Yixue Feng, Julio E. Villalon-Reina, Emily Laltoo, Himanshu Joshi, Ganesan Venkatasubramanian, John P. John, Greg Ver Steeg, José Luis Ambite, Paul M. Thompson
2024	—	`conf`	Deep Normative Tractometry for Identifying Joint White Matter Macro- and Micro-structural Abnormalities in Alzheimer's Disease. EMBC Yixue Feng, Bramsh Qamar Chandio, Julio E. Villalon-Reina, Sebastian M. Benavidez, Tamoghna Chattopadhyay, Sasha Chehrzadeh, Emily Laltoo, Sophia I. Thomopoulos, Himanshu Joshi, Ganesan Venkatasubramanian, John P. John, Neda Jahanshad, Paul M. Thompson
2023	—	`conf`	Can Structural MRIs be used to Detect Amyloid Positivity using Deep Learning? SIPAIM Tamoghna Chattopadhyay, Dheeraj Komandur, Jayati Naik, Ketaki Buwa, Saket Ozarkar, Sophia I. Thomopoulos, Paul M. Thompson
2023	—	`conf`	Comparison of Anatomical and Diffusion MRI for detecting Parkinson's Disease using Deep Convolutional Neural Network. EMBC Tamoghna Chattopadhyay, Amit Singh, Emily Laltoo, Christina P. Boyle, Conor Owens-Walton, Yao-Liang Chen, Philip A. Cook, Corey McMillan, Chih-Chien Tsai, Jiun-Jie Wang, Yih-Ru Wu, Ysbrand D. van der Werf, Paul M. Thompson
2023	—	`conf`	Predictive Modeling Of Alzheimer's Disease Prognosis Using Anatomical & Diffusion MRI. EMBC Nikita Goel, Sophia I. Thomopoulos, Tamoghna Chattopadhyay, Paul M. Thompson
2023	—	`conf`	The Influence of Brain MRI Defacing Algorithms on Brain-Age Predictions via 3D Convolutional Neural Networks. EMBC Ryan J. Cali, Ravi R. Bhatt, Sophia I. Thomopoulos, Shruti Gadewar, Iyad Ba Gari, Tamoghna Chattopadhyay, Neda Jahanshad, Paul M. Thompson
2023	—	`conf`	Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice Models. ISBI Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Paul M. Thompson, Greg Ver Steeg
2023	J	`jnl`	Transferring Models Trained on Natural Images to 3D MRI via Position Encoded Slice Models. CoRR Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Paul M. Thompson, Greg Ver Steeg, Alzheimer's Disease Neuroimaging Initiative
2023	—	`conf`	Unsupervised harmonization of brain MRI using 3D CycleGANs and its effect on brain age prediction. SIPAIM Dheeraj Komandur, Umang Gupta, Tamoghna Chattopadhyay, Nikhil J. Dhinagar, Sophia I. Thomopoulos, Jiu-Chiuan Chen, Dan Beavers, Greg Ver Steeg, Paul M. Thompson
2023	—	`conf`	Variational Autoencoders for Generating Synthetic Tractography-Based Bundle Templates in a Low-Data Setting. EMBC Yixue Feng, Bramsh Qamar Chandio, Sophia I. Thomopoulos, Tamoghna Chattopadhyay, Paul M. Thompson
2022	—	`conf`	FiberNeat: Unsupervised White Matter Tract Filtering. EMBC Bramsh Qamar Chandio, Tamoghna Chattopadhyay, Conor Owens-Walton, Julio E. Villalon-Reina, Leila Nabulsi, Sophia I. Thomopoulos, Eleftherios Garyfallidis, Paul M. Thompson

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.