Qidong Su - RankMe

17 papers A 2B 2Journal 10Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	LoRAFusion: Efficient LoRA Fine-Tuning for LLMs. EuroSys Zhanda Zhu, Qidong Su, Yaoyao Ding, Kevin Song, Shang Wang, Gennady Pekhimenko
2025	—	`conf`	APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. ACL (1) Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si
2025	J	`jnl`	Aegis: Taxonomy and Optimizations for Overcoming Agent-Environment Failures in LLM Agents. CoRR Kevin Song, Anand Jayarajan, Yaoyao Ding, Qidong Su, Zhanda Zhu, Sihang Liu, Gennady Pekhimenko
2025	J	`jnl`	LoRAFusion: Efficient LoRA Fine-Tuning for LLMs. CoRR Zhanda Zhu, Qidong Su, Yaoyao Ding, Kevin Song, Shang Wang, Gennady Pekhimenko
2025	A	`conf`	Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization. EuroSys Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu, Qidong Su, Karttikeya Mangalam, Bojian Zheng, Gennady Pekhimenko
2025	J	`jnl`	Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization. CoRR Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu, Qidong Su, Karttikeya Mangalam, Bojian Zheng, Gennady Pekhimenko
2025	—	`conf`	Seesaw: High-throughput LLM Inference via Model Re-sharding. MLSys Qidong Su, Wei Zhao, Xin Li, Muralidhar Andoorveedu, Chenhao Jiang, Zhanda Zhu, Kevin Song, Christina Giannoula, Gennady Pekhimenko
2025	J	`jnl`	Seesaw: High-throughput LLM Inference via Model Re-sharding. CoRR Qidong Su, Wei Zhao, Xin Li, Muralidhar Andoorveedu, Chenhao Jiang, Zhanda Zhu, Kevin Song, Christina Giannoula, Gennady Pekhimenko
2024	J	`jnl`	A Survey on Deep Learning for Theorem Proving. CoRR Zhaoyu Li, Jialiang Sun, Logan Murphy, Qidong Su, Zenan Li, Xian Zhang, Kaiyu Yang, Xujie Si
2024	J	`jnl`	APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. CoRR Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si
2024	B	`conf`	BOOM: Use your Desktop to Accurately Predict the Performance of Large Deep Neural Networks. PACT Qidong Su, Jiacheng Yang, Gennady Pekhimenko
2023	J	`jnl`	The Synergy of Speculative Decoding and Batching in Serving Large Language Models. CoRR Qidong Su, Christina Giannoula, Gennady Pekhimenko
2023	B	`conf`	TorchProbe: Fuzzing Dynamic Deep Learning Compilers. APLAS Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
2023	J	`jnl`	TorchProbe: Fuzzing Dynamic Deep Learning Compilers. CoRR Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
2021	J	`jnl`	Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Graphs. CoRR Da Zheng, Xiang Song, Chengru Yang, Dominique LaSalle, Qidong Su, Minjie Wang, Chao Ma, George Karypis
2020	—	`conf`	DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. IA3@SC Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis
2020	J	`jnl`	DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs. CoRR Da Zheng, Chao Ma, Minjie Wang, Jinjing Zhou, Qidong Su, Xiang Song, Quan Gan, Zheng Zhang, George Karypis

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.