Selected work

Representative Papers

Abstractions for Network Intelligence: A Reference Architecture for AI at the Wireless Edge

Aug 10, 2026

Current Internet architectures struggle to effectively support the sharing of sensing information between networks and AI applications, limiting the joint optimization of resource utilization and performance. This work proposes AI-EDGE, a reference architecture that introduces, for the first time, a network intelligence abstraction framework tailored for wireless edge AI. By incorporating an “information waist” layer, AI-EDGE enables efficient co-design and collaboration between intelligent networks and intelligent applications. The architecture is compatible with mainstream platforms such as O-RAN and Multi-access Edge Computing (MEC), supporting sensing data sharing, application portability, and rapid prototyping. Validation through diverse representative use cases in O-RAN cellular networks and 3GPP/ETSI edge computing environments demonstrates significant advantages across all these dimensions.

0 citationsRead paper

DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion

Aug 07, 2026

This work addresses the challenge of efficiently generating novel crystalline materials that satisfy crystallographic symmetry, elemental composition, and geometric continuity constraints within a vast compositional and structural space. It proposes a coupled symbolic diffusion framework that dynamically evolves space groups, Wyckoff positions, and elemental assignments, guided by crystallographic group–subgroup relationships to enable structured space-group transitions. A pretrained symmetry codebook is introduced to jointly constrain both the decoder and the geometric model. This approach achieves, for the first time, joint generation of space groups and crystal structures, demonstrating state-of-the-art performance across two independent relaxation evaluation engines. It enables efficient generation of highly stable, novel, and unique crystals, excelling particularly in preserving nontrivial post-relaxation symmetries, while supporting rapid sampling.

0 citationsRead paper

An Actuarial Cost and Revenue Model for Helicopter Emergency Medical Services: Estimating Population-Based Coverage and Sustainability Thresholds

Jun 11, 2026

This study addresses the financial sustainability challenges of Helicopter Emergency Medical Services (HEMS) by developing a transparent, replicable two-stage evaluation framework that integrates actuarial methodologies with real-world insurance reimbursement data. The framework comprises a cost-accounting module and a revenue-prediction model, enhanced through Monte Carlo simulation (10,000 iterations) and multi-scenario sensitivity analyses. Under a baseline scenario assuming 50% commercial insurance reimbursement of billed charges and 24/7 staffing, the model identifies a breakeven threshold of 184 annual transports. However, this requirement surges to over 1,000 missions if reimbursement is limited to Medicare rates or if personnel costs double. For the first time, the model quantifies the minimum population coverage threshold necessary for HEMS viability, offering policymakers and healthcare planners an evidence-based tool for strategic decision-making and resource allocation.

0 citationsRead paper

Identifier-Free Code Embedding Models for Scalable Search

May 05, 2026

Existing approaches struggle to achieve efficient and accurate bidirectional function matching between source code and decompiled code under standard preprocessing conditions that strip identifiers. This work proposes an embedding model based on Qwen3-Embedding, fine-tuned via contrastive learning to construct a semantically aligned embedding space without relying on symbolic information. For the first time, it enables bidirectional cross-representation code matching in fully de-identified settings. The method significantly outperforms current state-of-the-art techniques across multiple function-matching benchmarks, substantially improving both matching accuracy and scalability. Notably, it also demonstrates strong generalization capabilities on constant-algorithm matching tasks, despite not being explicitly trained for them.

0 citationsRead paper

Testing replication for an agent-based model of market fragmentation and latency arbitrage

Apr 21, 2026

This study addresses the reproducibility challenges of the multi-market fragmentation and delayed arbitrage agent-based model proposed by Wah and Wellman (2016), which stemmed from insufficient implementation details and limited quantitative reporting. Leveraging the authors’ subsequently released code, we formalize the modeling process using the ODD protocol and enhance statistical robustness by increasing simulation runs and applying bootstrapping to construct confidence intervals. Our replication achieves relational equivalence across most metrics but rejects quantitative alignment under non-zero delay conditions. Notably, we uncover that conclusions regarding fragmentation effects are highly sensitive to the specific implementation of greedy strategies; under alternative strategies, market fragmentation actually reduces execution time and improves trader welfare. This work thus provides the first complete and transparent replication framework for the original model.

0 citationsRead paper

Recent publications

Latest Papers

Abstractions for Network Intelligence: A Reference Architecture for AI at the Wireless Edge

Aug 10, 2026

Current Internet architectures struggle to effectively support the sharing of sensing information between networks and AI applications, limiting the joint optimization of resource utilization and performance. This work proposes AI-EDGE, a reference architecture that introduces, for the first time, a network intelligence abstraction framework tailored for wireless edge AI. By incorporating an “information waist” layer, AI-EDGE enables efficient co-design and collaboration between intelligent networks and intelligent applications. The architecture is compatible with mainstream platforms such as O-RAN and Multi-access Edge Computing (MEC), supporting sensing data sharing, application portability, and rapid prototyping. Validation through diverse representative use cases in O-RAN cellular networks and 3GPP/ETSI edge computing environments demonstrates significant advantages across all these dimensions.

0 citationsRead paper

DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion

Aug 07, 2026

This work addresses the challenge of efficiently generating novel crystalline materials that satisfy crystallographic symmetry, elemental composition, and geometric continuity constraints within a vast compositional and structural space. It proposes a coupled symbolic diffusion framework that dynamically evolves space groups, Wyckoff positions, and elemental assignments, guided by crystallographic group–subgroup relationships to enable structured space-group transitions. A pretrained symmetry codebook is introduced to jointly constrain both the decoder and the geometric model. This approach achieves, for the first time, joint generation of space groups and crystal structures, demonstrating state-of-the-art performance across two independent relaxation evaluation engines. It enables efficient generation of highly stable, novel, and unique crystals, excelling particularly in preserving nontrivial post-relaxation symmetries, while supporting rapid sampling.

0 citationsRead paper

An Actuarial Cost and Revenue Model for Helicopter Emergency Medical Services: Estimating Population-Based Coverage and Sustainability Thresholds

Jun 11, 2026

This study addresses the financial sustainability challenges of Helicopter Emergency Medical Services (HEMS) by developing a transparent, replicable two-stage evaluation framework that integrates actuarial methodologies with real-world insurance reimbursement data. The framework comprises a cost-accounting module and a revenue-prediction model, enhanced through Monte Carlo simulation (10,000 iterations) and multi-scenario sensitivity analyses. Under a baseline scenario assuming 50% commercial insurance reimbursement of billed charges and 24/7 staffing, the model identifies a breakeven threshold of 184 annual transports. However, this requirement surges to over 1,000 missions if reimbursement is limited to Medicare rates or if personnel costs double. For the first time, the model quantifies the minimum population coverage threshold necessary for HEMS viability, offering policymakers and healthcare planners an evidence-based tool for strategic decision-making and resource allocation.

0 citationsRead paper

Identifier-Free Code Embedding Models for Scalable Search

May 05, 2026

Existing approaches struggle to achieve efficient and accurate bidirectional function matching between source code and decompiled code under standard preprocessing conditions that strip identifiers. This work proposes an embedding model based on Qwen3-Embedding, fine-tuned via contrastive learning to construct a semantically aligned embedding space without relying on symbolic information. For the first time, it enables bidirectional cross-representation code matching in fully de-identified settings. The method significantly outperforms current state-of-the-art techniques across multiple function-matching benchmarks, substantially improving both matching accuracy and scalability. Notably, it also demonstrates strong generalization capabilities on constant-algorithm matching tasks, despite not being explicitly trained for them.

0 citationsRead paper

Testing replication for an agent-based model of market fragmentation and latency arbitrage

Apr 21, 2026

This study addresses the reproducibility challenges of the multi-market fragmentation and delayed arbitrage agent-based model proposed by Wah and Wellman (2016), which stemmed from insufficient implementation details and limited quantitative reporting. Leveraging the authors’ subsequently released code, we formalize the modeling process using the ODD protocol and enhance statistical robustness by increasing simulation runs and applying bootstrapping to construct confidence intervals. Our replication achieves relational equivalence across most metrics but rejects quantitative alignment under non-zero delay conditions. Notably, we uncover that conclusions regarding fragmentation effects are highly sensitive to the specific implementation of greedy strategies; under alternative strategies, market fragmentation actually reduces execution time and improves trader welfare. This work thus provides the first complete and transparent replication framework for the original model.

0 citationsRead paper