Sai Srinivas Kancheti

17 papers A* 1Journal 11Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Conformal Prediction in the Age of Multimodal Foundation Models: A Survey. The Importance of Being Learnable Christian Stavan, Kunal Tilaganji, Sai Mathura Krishnan, Sai Srinivas Kancheti, Vineeth N. Balasubramanian
2025	J	`jnl`	Efficient Vocabulary-Free Fine-Grained Visual Recognition in the Age of Multimodal LLMs. CoRR Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2025	J	`jnl`	Efficient Vocabulary-Free Fine-Grained Visual Recognition in the Age of Multimodal LLMs. Trans. Mach. Learn. Res. Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2025	J	`jnl`	HARE: Human-in-the-Loop Algorithmic Recourse. Trans. Mach. Learn. Res. Sai Srinivas Kancheti, Rahul Vigneswaran, Bamdev Mishra, Vineeth N. Balasubramanian
2025	J	`jnl`	Interpretable Model Drift Detection. CoRR Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Gaurav Sinha
2025	J	`jnl`	Semantic Alignment for Prompt-Tuning in Vision Language Models. Trans. Mach. Learn. Res. Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2024	J	`jnl`	Can Better Text Semantics in Prompt Tuning Improve VLM Generalization? CoRR Hari Chandana Kuchibhotla, Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2024	—	`conf`	Interpretable Model Drift Detection. COMAD/CODS Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Gaurav Sinha
2023	—	`conf`	Algorithmic Recourse based on User's Feature-order Preference. COMAD/CODS Manan Singh, Sai Srinivas Kancheti, Shivam Gupta, Ganesh Ghalme, Shweta Jain, Narayanan C. Krishnan
2022	A*	`conf`	Matching Learned Causal Effects of Neural Networks with Domain Priors. ICML Sai Srinivas Kancheti, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma
2021	—	`conf`	Beyond VQA: Generating Multi-Word Answers and Rationales to Visual Questions. CVPR Workshops Radhika Dua, Sai Srinivas Kancheti, Vineeth N. Balasubramanian
2021	J	`jnl`	Causal Regularization Using Domain Priors. CoRR Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Amit Sharma
2021	—	`conf`	Instance-Wise Causal Feature Selection for Model Interpretation. CVPR Workshops Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian
2021	J	`jnl`	Instance-wise Causal Feature Selection for Model Interpretation. CoRR Pranoy Panda, Sai Srinivas Kancheti, Vineeth N. Balasubramanian
2021	J	`jnl`	Linguistically-aware attention for reducing the semantic gap in vision-language tasks. Pattern Recognit. Gouthaman KV, Athira M. Nambiar, Sai Srinivas Kancheti, Anurag Mittal
2020	J	`jnl`	Beyond VQA: Generating Multi-word Answer and Rationale to Visual Questions. CoRR Radhika Dua, Sai Srinivas Kancheti, Vineeth N. Balasubramanian
2020	J	`jnl`	Linguistically-aware Attention for Reducing the Semantic-Gap in Vision-Language Tasks. CoRR Gouthaman KV, Athira M. Nambiar, Sai Srinivas Kancheti, Anurag Mittal

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.