Paarth Shah - RankMe

19 papers A* 2A 1Journal 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Systematic Study of Data Modalities and Strategies for Co-training Large Behavior Models for Robot Manipulation. CoRR Fanqi Lin, Kushal Arora, Jean Mercat, Haruki Nishimura, Paarth Shah, Chen Xu, Mengchao Zhang, Mark Zolotas, Maya Angeles, Owen Pfannenstiehl, Andrew Beaulieu, Jose A. Barreiros
2026	J	`jnl`	A careful examination of large behavior models for multitask dexterous manipulation. Sci. Robotics Jose A. Barreiros, Andrew Beaulieu, Aditya Bhat, Rick Cory, Eric Cousineau, Hongkai Dai, Ching-Hsin Fang, Kunimatsu Hashimoto, Muhammad Zubair Irshad, Masha Itkina, Naveen Kuppuswamy, Kuan-Hui Lee, Katherine Liu, Dale McConachie, Ian McMahon, Haruki Nishimura, Calder Phillips-Grafflin, Charles Richter, Paarth Shah, Krishnan Srinivasan, Blake Wulfe, Chen Xu, Mengchao Zhang, Alex Alspach, Maya Angeles, Kushal Arora, Vitor Campagnolo Guizilini, Alejandro M. Castro, Dian Chen, Ting-Sheng Chu, Sam Creasey, Sean Curtis, Richard Denitto, Emma Dixon, Eric Dusel, Matthew Ferreira, Aimee Goncalves, Grant Gould, Damrong Guoy, Swati Gupta, Xuchen Han, Kyle Hatch, Brendan Hathaway, Allison Henry, Hillel Hochsztein, Phoebe Horgan, Shun Iwase, Donovon Jackson, Siddharth Karamcheti, Sedrick Keh, Joseph Masterjohn, Masayuki Masuda, Jean Mercat, Patrick Tree Miller, Paul Mitiguy, Tony Nguyen, Jeremy Nimmer, Yuki Noguchi, Reko Ong, Aykut Özgün Önol, Owen Pfannenstiehl, Richard Poyner, Leticia Priebe Rocha, Gordon Richardson, Christopher Rodriguez, Derick Seale, Michael A. Sherman, Mariah Smith-Jones, David Tago, Pavel Tokmakov, Matthew Tran, Basile Van Hoorick, Igor Vasiljevic, Sergey Zakharov, Mark Zolotas, Rares Ambrus, Kerri Fetzer-Borelli, Benjamin Burchfiel, Hadas Kress-Gazit, Siyuan Feng, Stacie Ford, Russ Tedrake
2025	J	`jnl`	Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies. CoRR Chen Xu, Tony Khuong Nguyen, Emma Dixon, Christopher Rodriguez, Patrick Tree Miller, Robert Lee, Paarth Shah, Rares Ambrus, Haruki Nishimura, Masha Itkina
2025	J	`jnl`	CodeDiffuser: Attention-Enhanced Diffusion Policy via VLM-Generated Code for Instruction Ambiguity. CoRR Guang Yin, Yitong Li, Yixuan Wang, Dale McConachie, Paarth Shah, Kunimatsu Hashimoto, Huan Zhang, Katherine Liu, Yunzhu Li
2025	A*	`conf`	Proximity and Visuotactile Point Cloud Fusion for Contact Patches in Extreme Deformation. ICRA Jessica Yin, Paarth Shah, Naveen Kuppuswamy, Andrew Beaulieu, Avinash Uttamchandani, Alejandro M. Castro, James H. Pikul, Russ Tedrake
2025	J	`jnl`	Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets. CoRR Chuning Zhu, Raymond Yu, Siyuan Feng, Benjamin Burchfiel, Paarth Shah, Abhishek Gupta
2025	J	`jnl`	Using Non-Expert Data to Robustify Imitation Learning via Offline Reinforcement Learning. CoRR Kevin Huang, Rosario Scalise, Cleah Winston, Ayush Agrawal, Yunchu Zhang, Rohan Baijal, Markus Grotz, Byron Boots, Benjamin Burchfiel, Masha Itkina, Paarth Shah, Abhishek Gupta
2025	J	`jnl`	Video Generators are Robot Policies. CoRR Junbang Liang, Pavel Tokmakov, Ruoshi Liu, Sruthi Sudhakar, Paarth Shah, Rares Ambrus, Carl Vondrick
2024	J	`jnl`	How Generalizable Is My Behavior Cloning Policy? A Statistical Approach to Trustworthy Performance Evaluation. CoRR Joseph A. Vincent, Haruki Nishimura, Masha Itkina, Paarth Shah, Mac Schwager, Thomas Kollar
2024	J	`jnl`	How Generalizable is My Behavior Cloning Policy? A Statistical Approach to Trustworthy Performance Evaluation. IEEE Robotics Autom. Lett. Joseph A. Vincent, Haruki Nishimura, Masha Itkina, Paarth Shah, Mac Schwager, Thomas Kollar
2024	J	`jnl`	Robot Learning as an Empirical Science: Best Practices for Policy Evaluation. CoRR Hadas Kress-Gazit, Kunimatsu Hashimoto, Naveen Kuppuswamy, Paarth Shah, Phoebe Horgan, Gordon Richardson, Siyuan Feng, Benjamin Burchfiel
2023	J	`jnl`	BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning. IEEE Trans. Robotics Avadesh Meduri, Paarth Shah, Julian Viereck, Majid Khadiv, Ioannis Havoutis, Ludovic Righetti
2023	J	`jnl`	Proximity and Visuotactile Point Cloud Fusion for Contact Patches in Extreme Deformation. CoRR Jessica Yin, Paarth Shah, Naveen Kuppuswamy, Andrew Beaulieu, Avinash Uttamchandani, Alejandro M. Castro, James H. Pikul, Russ Tedrake
2023	A*	`conf`	Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion. ICRA Victor Dhédin, Haolong Li, Shahram Khorshidi, Lukas Mack, Adithya Kumar Chinnakkonda Ravi, Avadesh Meduri, Paarth Shah, Felix Grimminger, Ludovic Righetti, Majid Khadiv, Joerg Stueckler
2022	J	`jnl`	BiConMP: A Nonlinear Model Predictive Control Framework for Whole Body Motion Planning. CoRR Avadesh Meduri, Paarth Shah, Julian Viereck, Majid Khadiv, Ioannis Havoutis, Ludovic Righetti
2022	J	`jnl`	Differentiable and Learnable Robot Models. CoRR Franziska Meier, Austin S. Wang, Giovanni Sutanto, Yixin Lin, Paarth Shah
2022	J	`jnl`	Visual-Inertial and Leg Odometry Fusion for Dynamic Locomotion. CoRR Victor Dhédin, Haolong Li, Shahram Khorshidi, Lukas Mack, Adithya Kumar Chinnakkonda Ravi, Avadesh Meduri, Paarth Shah, Felix Grimminger, Ludovic Righetti, Majid Khadiv, Joerg Stueckler
2021	A	`conf`	Rapid Convex Optimization of Centroidal Dynamics using Block Coordinate Descent. IROS Paarth Shah, Avadesh Meduri, Wolfgang Merkt, Majid Khadiv, Ioannis Havoutis, Ludovic Righetti
2021	J	`jnl`	Rapid Convex Optimization of Centroidal Dynamics using Block Coordinate Descent. CoRR Paarth Shah, Avadesh Meduri, Wolfgang Merkt, Majid Khadiv, Ioannis Havoutis, Ludovic Righetti

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.