Geon-Woo Kim - RankMe

15 papers A* 4A 1Journal 7Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training. ICML Geon-Woo Kim, Junbo Li, Shashidhar Gandham, Omar Baldonado, Adithya Gangidi, Pavan Balaji, Zhangyang Wang, Aditya Akella
2025	J	`jnl`	HALoS: Hierarchical Asynchronous Local SGD over Slow Networks for Geo-Distributed Large Language Model Training. CoRR Geon-Woo Kim, Junbo Li, Shashidhar Gandham, Omar Baldonado, Adithya Gangidi, Pavan Balaji, Zhangyang Wang, Aditya Akella
2025	—	`conf`	LLM-based Methodology for Expanding 3D Metadata in Point Cloud. ICACT Geon-Woo Kim, Joo-Chang Kim
2025	J	`jnl`	OMEGA: A Low-Latency GNN Serving System for Large Graphs. CoRR Geon-Woo Kim, Donghyun Kim, Jeongyoon Moon, Henry Liu, Tarannum Khan, Anand Iyer, Daehyeok Kim, Aditya Akella
2025	—	`conf`	StitchLLM: Serving LLMs, One Block at a Time. ACL (1) Bodun Hu, Shuozhe Li, Saurabh Agarwal, Myungjin Lee, Akshay Jajoo, Jiamin Li, Le Xu, Geon-Woo Kim, Donghyun Kim, Hong Xu, Amy Zhang, Aditya Akella
2025	J	`jnl`	Toward Cost-Efficient Serving of Mixture-of-Experts with Asynchrony. CoRR Shaoyu Wang, Guangrong He, Geon-Woo Kim, Yanqi Zhou, Seo Jin Park
2024	J	`jnl`	Extraction of Meta-Data for Recommendation Using Keyword Mapping. IEEE Access Geon-Woo Kim, Woo-Hyeon Kim, Kyungyong Chung, Joo-Chang Kim
2024	A*	`conf`	Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design. NeurIPS Ruisi Cai, Yeonju Ro, Geon-Woo Kim, Peihao Wang, Babak Ehteshami Bejnordi, Aditya Akella, Zhangyang Wang
2024	J	`jnl`	Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design. CoRR Ruisi Cai, Yeonju Ro, Geon-Woo Kim, Peihao Wang, Babak Ehteshami Bejnordi, Aditya Akella, Zhangyang Wang
2023	J	`jnl`	Lovelock: Towards Smart NIC-hosted Clusters. CoRR Seo Jin Park, Ramesh Govindan, Kai Shen, David E. Culler, Fatma Özcan, Geon-Woo Kim, Hank Levy
2022	A*	`conf`	Orca: A Distributed Serving System for Transformer-Based Generative Models. OSDI Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, Byung-Gon Chun
2022	J	`jnl`	Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs. CoRR Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun
2021	A*	`conf`	Terra: Imperative-Symbolic Co-Execution of Imperative Deep Learning Programs. NeurIPS Taebum Kim, Eunji Jeong, Geon-Woo Kim, Yunmo Koo, Sehoon Kim, Gyeong-In Yu, Byung-Gon Chun
2019	—	`conf`	Apache Nemo: A Framework for Building Distributed Dataflow Optimization Policies. USENIX ATC Youngseok Yang, Jeongyoon Eo, Geon-Woo Kim, Jooyeon Kim, Sanha Lee, Jangho Seo, Won Wook Song, Byung-Gon Chun
2017	A	`conf`	Pado: A Data Processing Engine for Harnessing Transient Resources in Datacenters. EuroSys Youngseok Yang, Geon-Woo Kim, Won Wook Song, Yunseong Lee, Andrew Chung, Zhengping Qian, Brian Cho, Byung-Gon Chun

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.