35 citations · 66 across the 33 of their papers we have counts for
8 papers · 1 filter
Neural Residual Modeling for Scientific Data Compression under Guaranteed Error Bounds
Surya Majumder, Liangji Zhu, Sanjay Ranka +1
Lossy compression of scientific simulation data increasingly relies on learned, latent-space architectures such as Residual Vector Quantization (RVQ), which iteratively quantize a…
Multivariate Scientific Data Compression with Learned Cross-Variable Latent Decorrelation and Autoregressive Entropy Modeling
Liangji Zhu, Anand Rangarajan, Sanjay Ranka
Scientific simulations generate collections of physical fields with heterogeneous statistics and dependencies, yet learned compressors often encode those fields independently or re…
QoI-Aware Provisional Rollout and Retrospective Reconciliation for Reduced-State Scientific Twins
Liangji Zhu, Scott Klasky, Jaemoon Lee +3
Scientific twins may need to continue operating when updates from an authoritative primary system are temporarily unavailable. Once synchronization resumes, the new boundary can al…
PhaseShift: Topology-Aware Data Harmonization and Model Consolidation Across Signalized Intersections
Yash Ranjan, Artur Kumik, Rahul Sengupta +2
Learned traffic-behavior models are commonly trained separately for each intersection, creating model portfolios that cannot share evidence across sites. We present PhaseShift, a t…
A Generative Model for Closed-Loop Microsimulation of Signalized Intersections
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic microsimulators rely on hand-crafted behavior models that reproduce aggregate flow but miss the heterogeneous interactions between vehicles at signalized intersections. Lea…
Residual Modeling for High-Fidelity Learned Compression of Scientific Data
Liangji Zhu, Sanjay Ranka, Anand Rangarajan
Lossy compression is essential for massive spatiotemporal data from scientific simulations. Learned compressors can achieve high compression ratios at moderate accuracy targets, bu…
Enactor: From Traffic Simulators to Surrogate World Models
Yash Ranjan, Rahul Sengupta, Anand Rangarajan +1
Traffic microsimulators are widely used to evaluate road network performance under various ``what-if" conditions. However, the behavior models controlling the actions of the actors…
BigSUMO: A Scalable Framework for Big Data Traffic Analytics and Parallel Simulation
Rahul Sengupta, Nooshin Yousefzadeh, Manav Sanghvi +7
With growing urbanization worldwide, efficient management of traffic infrastructure is critical for transportation agencies and city planners. It is essential to have tools that he…