Abbavaram Gowtham Reddy

24 papers A* 7C 1Journal 16

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference. ICLR Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma
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`	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
2025	A*	`conf`	Teaching Transformers Causal Reasoning through Axiomatic Training. ICML Aniket Vashishtha, Abhinav Kumar, Atharva Pandey, Abbavaram Gowtham Reddy, Kabir Ahuja, Vineeth N. Balasubramanian, Amit Sharma
2025	J	`jnl`	When Shift Happens - Confounding Is to Blame. CoRR Abbavaram Gowtham Reddy, Celia Rubio-Madrigal, Rebekka Burkholz, Krikamol Muandet
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	J	`jnl`	Debiasing Machine Unlearning with Counterfactual Examples. CoRR Ziheng Chen, Jia Wang, Jun Zhuang, Abbavaram Gowtham Reddy, Fabrizio Silvestri, Jin Huang, Kaushiki Nag, Kun Kuang, Xin Ning, Gabriele Tolomei
2024	A*	`conf`	Detecting and Measuring Confounding Using Causal Mechanism Shifts. NeurIPS Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2024	J	`jnl`	Detecting and Measuring Confounding Using Causal Mechanism Shifts. CoRR Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2024	A*	`conf`	NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation. AAAI Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
2024	J	`jnl`	Teaching Transformers Causal Reasoning through Axiomatic Training. CoRR Aniket Vashishtha, Abhinav Kumar, Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian, Amit Sharma
2024	A*	`conf`	Towards Learning and Explaining Indirect Causal Effects in Neural Networks. AAAI Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin Godfrey L, Varshaneya V, Vineeth N. Balasubramanian, Satyanarayan Kar
2023	J	`jnl`	Causal Inference Using LLM-Guided Discovery. CoRR Aniket Vashishtha, Abbavaram Gowtham Reddy, Abhinav Kumar, Saketh Bachu, Vineeth N. Balasubramanian, Amit Sharma
2023	J	`jnl`	Learning Causal Attributions in Neural Networks: Beyond Direct Effects. CoRR Abbavaram Gowtham Reddy, Saketh Bachu, Harsharaj Pathak, Benin L. Godfrey, Vineeth N. Balasubramanian, Varshaneya V, Satya Narayanan Kar
2023	J	`jnl`	Rethinking Counterfactual Data Augmentation Under Confounding. CoRR Abbavaram Gowtham Reddy, Saketh Bachu, Saloni Dash, Charchit Sharma, Amit Sharma, Vineeth N. Balasubramanian
2022	J	`jnl`	Counterfactual Generation Under Confounding. CoRR Abbavaram Gowtham Reddy, Saloni Dash, Amit Sharma, Vineeth N. Balasubramanian
2022	J	`jnl`	Estimating Treatment Effects using Neurosymbolic Program Synthesis. CoRR Abbavaram Gowtham Reddy, Vineeth N. Balasubramanian
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
2022	A*	`conf`	On Causally Disentangled Representations. AAAI Abbavaram Gowtham Reddy, Benin Godfrey L, Vineeth N. Balasubramanian
2021	J	`jnl`	Causal Regularization Using Domain Priors. CoRR Abbavaram Gowtham Reddy, Sai Srinivas Kancheti, Vineeth N. Balasubramanian, Amit Sharma
2021	C	`conf`	Causality in Neural Networks - An Extended Abstract. AIES Abbavaram Gowtham Reddy
2021	J	`jnl`	Causality in Neural Networks - An Extended Abstract. CoRR Abbavaram Gowtham Reddy
2021	J	`jnl`	On Causally Disentangled Representations. CoRR Abbavaram Gowtham Reddy, Benin Godfrey L, Vineeth N. Balasubramanian

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.