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Changjun Lee

dblp:210/1461 · DBLP profile ↗
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5ranked-venue papers
3as first author
3since 2021 · last 2026
0000-0002-8859-9796ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 3 · 1 first-author · 3 since 2021Databases, data management, data science and information retrieval · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
3 papers
Memory systems · 53% Cloud and datacenter computing · 42% Hardware accelerators and domain-specific architectures · 5%
Network and information security
1 paper
Systems and software security · 100%
Software engineering, system software, and programming languages
1 paper
Operating systems · 100%

Topics — the 13 heaviest of 13, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Systems and software security › virtualization security
container security
1.012026
CofferOS: Hardening OS-level Virtualization with Rust · EuroSys 2026
Systems and software security
operating system security
1.012026
CofferOS: Hardening OS-level Virtualization with Rust · EuroSys 2026
Operating systems › system security › operating system security › protection mechanism › isolation
container isolation
1.012026
CofferOS: Hardening OS-level Virtualization with Rust · EuroSys 2026
Operating systems › virtualization
OS-level virtualization
1.012026
CofferOS: Hardening OS-level Virtualization with Rust · EuroSys 2026
Memory systems › memory bandwidth
memory bandwidth optimization
1.012026
MTTM: Dynamic Fast Memory Partitioning with Bandwidth Optimization for Multi-tenant Cloud · EuroSys 2026
Memory systems › memory management
memory deduplication
1.012026
BASK: Batch And SmartNIC-offloaded KSM · EuroSys 2026
Cloud and datacenter computing › multi-tenancy
multi-tenant cloud
1.012026
MTTM: Dynamic Fast Memory Partitioning with Bandwidth Optimization for Multi-tenant Cloud · EuroSys 2026
Cloud and datacenter computing › computation offloading › network function offloading
SmartNIC offload
1.012026
BASK: Batch And SmartNIC-offloaded KSM · EuroSys 2026
Memory systems
tiered memory
1.012026
MTTM: Dynamic Fast Memory Partitioning with Bandwidth Optimization for Multi-tenant Cloud · EuroSys 2026
Cloud and datacenter computing › virtualization › containerization
container-based virtualization
0.312026
CofferOS: Hardening OS-level Virtualization with Rust · EuroSys 2026
Memory systems › memory disaggregation
CXL memory
0.312026
MTTM: Dynamic Fast Memory Partitioning with Bandwidth Optimization for Multi-tenant Cloud · EuroSys 2026
Hardware accelerators and domain-specific architectures › network accelerator
SmartNIC
0.312026
BASK: Batch And SmartNIC-offloaded KSM · EuroSys 2026
Cloud and datacenter computing
virtualization
0.312026
CofferOS: Hardening OS-level Virtualization with Rust · EuroSys 2026

Methods — techniques the papers use, named apart from their topics

rust · 3.0kernel isolation · 3.0dynamic memory partitioning · 1.0
YearPublicationVenuePosition
2026 CofferOS: Hardening OS-level Virtualization with Rust
abstract
OS-level virtualization (e.g., Linux containers) has become a cornerstone of modern cloud systems. While it offers the illusion of isolated kernels for processes, these processes share the same underlying kernel, raising critical concerns around security, fault isolation, and the inability to customize kernels. Existing solutions address the issues by employing virtual machines that isolate kernels. However, these approaches incur significant performance overhead.
Minkyu Jung, Chanshin Kwak, Junho Ahn, Sunho Park, Changjun Lee, Jongyul Kim 0001, Jeehoon Kang, Youngjin Kwon
EuroSys5
2026 BASK: Batch And SmartNIC-offloaded KSM
Chanshin Kwak, Jaehyeon Lee, Minkyu Jung, Changjun Lee, Youngjin Kwon
EuroSys4
2026 MTTM: Dynamic Fast Memory Partitioning with Bandwidth Optimization for Multi-tenant Cloud
abstract
Memory tiering, which extends local DRAM by incorporating remote DRAM or NVM via Compute Express Link (CXL), offers a promising solution to the DRAM capacity scaling problem. However, in multi-tenant cloud environments, efficient management of fast memory requires not only optimizing data movement across tiers but also effectively distributing DRAM capacity when tenants compete. Moreover, bandwidth utilization is critically impacted by memory request rejection, which depends on the distribution of local DRAM. While previous research has extensively addressed data movement, DRAM distribution among multiple tenants remains underexplored.
Changjun Lee, Sangjin Choi, Youngjin Kwon
EuroSys1
2019 Capturing information on technology convergence, international collaboration, and knowledge flow from patent documents: A case of information and communication technology
Changjun Lee, Dieter Franz Kogler
Inf. Process. Manag.1
2018 The evolutionary trajectory of an ICT ecosystem: A network analysis based on media users' data
Changjun Lee, Hongbum Kim
Inf. Manag.1