Raghuram Ramanujan

25 papers A* 5A 3B 2Misc 1Journal 11Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Forward versus Backward: Comparing Reasoning Objectives in Direct Preference Optimization. CoRR Murtaza Nikzad, Raghuram Ramanujan
2025	—	`conf`	A Machine Learning Approach to Expanding the Degrees of Freedom on Phone-Based Head Mounted Displays. VR Workshops Andrew J. Jones, Raghuram Ramanujan, Tabitha C. Peck
2025	J	`jnl`	Sparse Methods for Vector Embeddings of TPC Data. CoRR Tyler Wheeler, Michelle P. Kuchera, Raghuram Ramanujan, Ryan Krupp, Chris Wrede, Saiprasad Ravishankar, Connor L. Cross, Hoi Yan Ian Heung, Andrew J. Jones, Benjamin Votaw
2025	J	`jnl`	Unpaired Translation of Point Clouds for Modeling Detector Response. CoRR Mingyang Li, Michelle P. Kuchera, Raghuram Ramanujan, Adam Anthony, Curtis Hunt, Yassid Ayyad
2024	J	`jnl`	Implicit quantile networks for emulation in jet physics. Mach. Learn. Sci. Technol. Braden Kronheim, Ali Al Kadhim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan
2024	A*	`conf`	Lookahead Pathology in Monte-Carlo Tree Search. ICAPS Khoi P. N. Nguyen, Raghuram Ramanujan
2023	B	`conf`	Lightweight Online Learning for Sets of Related Problems in Automated Reasoning. FMCAD Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett
2023	J	`jnl`	Lightweight Online Learning for Sets of Related Problems in Automated Reasoning. CoRR Haoze Wu, Christopher Hahn, Florian Lonsing, Makai Mann, Raghuram Ramanujan, Clark W. Barrett
2022	J	`jnl`	Lookahead Pathology in Monte-Carlo Tree Search. CoRR Khoi P. N. Nguyen, Raghuram Ramanujan
2021	J	`jnl`	Implicit Quantile Neural Networks for Jet Simulation and Correction. CoRR Braden Kronheim, Michelle P. Kuchera, Harrison B. Prosper, Raghuram Ramanujan
2020	J	`jnl`	A Steering Algorithm for Redirected Walking Using Reinforcement Learning. IEEE Trans. Vis. Comput. Graph. Ryan R. Strauss, Raghuram Ramanujan, Andrew Becker, Tabitha C. Peck
2019	A*	`conf`	G2SAT: Learning to Generate SAT Formulas. NeurIPS Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec
2019	J	`jnl`	G2SAT: Learning to Generate SAT Formulas. CoRR Jiaxuan You, Haoze Wu, Clark W. Barrett, Raghuram Ramanujan, Jure Leskovec
2019	B	`conf`	Learning to Generate Industrial SAT Instances. SOCS Haoze Wu, Raghuram Ramanujan
2018	J	`jnl`	Machine Learning Methods for Track Classification in the AT-TPC. CoRR Michelle P. Kuchera, Raghuram Ramanujan, Jack Z. Taylor, Ryan R. Strauss, Daniel Bazin, Joshua Bradt, Ruiming Chen
2016	A*	`conf`	A.I. as an Introduction to Research Methods in Computer Science. AAAI Raghuram Ramanujan
2016	A	`conf`	Monte-Carlo Tree Search for the Maximum Satisfiability Problem. CP Jack Goffinet, Raghuram Ramanujan
2015	Misc	`conf`	Computational Creativity in the Culinary Arts. FLAIRS Erol Cromwell, Jonah Galeota-Sprung, Raghuram Ramanujan
2012	J	`jnl`	Understanding Sampling Style Adversarial Search Methods CoRR Raghuram Ramanujan, Ashish Sabharwal, Bart Selman
2012	—	`—`	Understanding Sampling-based Adversarial Search Methods. Raghuram Ramanujan
2011	A	`conf`	Applying UCT to Boolean Satisfiability. SAT Alessandro Previti, Raghuram Ramanujan, Marco Schaerf, Bart Selman
2011	—	`conf`	Monte-Carlo Style UCT Search for Boolean Satisfiability. AI*IA Alessandro Previti, Raghuram Ramanujan, Marco Schaerf, Bart Selman
2011	A*	`conf`	Trade-Offs in Sampling-Based Adversarial Planning. ICAPS Raghuram Ramanujan, Bart Selman
2010	A*	`conf`	On Adversarial Search Spaces and Sampling-Based Planning. ICAPS Raghuram Ramanujan, Ashish Sabharwal, Bart Selman
2010	A	`conf`	Understanding Sampling Style Adversarial Search Methods. UAI Raghuram Ramanujan, Ashish Sabharwal, Bart Selman

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.