1 citations · 3 across the 18 of their papers we have counts for
21 papers
EpiNarrate: Agentic Generation of Grounded Narratives from Epidemiological Scenario Projections
Rituparna Datta, Srini Venkatramanan, Bryan L. Lewis +6
Generation of clear and accessible public health narratives is critical for communicating complex epidemiological projections to policymakers and the general public at large. Such…
Large Language Models Lack Temporal Awareness of Medical Knowledge
Zihan Guan, Qiao Jin, Guangzhi Xiong +6
The existing methods for evaluating the medical knowledge of Large Language Models (LLMs) are largely based on atemporal examination-style benchmarks, while in reality, medical kno…
Agentic Framework for Epidemiological Modeling
Rituparna Datta, Zihan Guan, Baltazar Espinoza +5
Epidemic modeling is essential for public health planning, yet traditional approaches rely on fixed model classes that require manual redesign as pathogens, policies, and scenario…
Reconstructing Network Outbreaks under Group Surveillance
Ritwick Mishra, Abhijin Adiga, Anil Vullikanti
A key public health problem during an outbreak is to reconstruct the disease cascade from a partial set of confirmed infections. This has been studied extensively under the Maximum…
Are LLMs Ready for Neural-integrated Mechanistic Modeling? A Benchmark and Agentic Framework
Zihan Guan, Rituparna Datta, Mengxuan Hu +5
Large language models (LLMs) have shown promise in constructing mechanistic models from data. However, existing evaluations largely focus on simplified settings and fail to capture…
Information Theoretic Optimal Surveillance for Epidemic Prevalence in Networks
Ritwick Mishra, Abhijin Adiga, Madhav Marathe +3
Estimating the true prevalence of an epidemic outbreak is a key public health problem. This is challenging because surveillance is usually resource intensive and biased. In the net…
Improving Hospital Risk Prediction with Knowledge-Augmented Multimodal EHR Modeling
Rituparna Datta, Jiaming Cui, Zihan Guan +5
Accurate prediction of clinical outcomes using Electronic Health Records (EHRs) is critical for early intervention, efficient resource allocation, and improved patient care. EHRs c…
Prediction of Hospital Associated Infections During Continuous Hospital Stays
Rituparna Datta, Methun Kamruzzaman, Eili Y. Klein +4
The US Centers for Disease Control and Prevention (CDC), in 2019, designated Methicillin-resistant Staphylococcus aureus (MRSA) as a serious antimicrobial resistance threat. The ri…
CALYPSO: Forecasting and Analyzing MRSA Infection Patterns with Community and Healthcare Transmission Dynamics
Rituparna Datta, Jiaming Cui, Gregory R. Madden +1
Methicillin-resistant Staphylococcus aureus (MRSA) is a critical public health threat within hospitals as well as long-term care facilities. Better understanding of MRSA risks, eva…
Improving Epidemic Analyses with Privacy-Preserving Integration of Sensitive Data
Zihan Guan, Zhiyuan Zhao, Fengwei Tian +5
Epidemic analyses increasingly rely on heterogeneous datasets, many of which are sensitive and require strong privacy protection. Although differential privacy (DP) has become a st…
Controlling the Spread of Epidemics on Networks with Differential Privacy
Dung Nguyen, Aravind Srinivasan, Renata Valieva +2
Designing effective strategies for controlling epidemic spread by vaccination is an important question in epidemiology, especially in the early stages when vaccines are limited. Th…
Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
Zihan Guan, Mengxuan Hu, Ronghang Zhu +2
Recent studies have uncovered a troubling vulnerability in the fine-tuning stage of large language models (LLMs): even fine-tuning on entirely benign datasets can lead to a signifi…
Differentially Private and Scalable Estimation of the Network Principal Component
Alireza Khayatian, Anil Vullikanti, Aritra Konar
Computing the principal component (PC) of the adjacency matrix of an undirected graph has several applications ranging from identifying key vertices for influence maximization and…
Accurately Estimating Unreported Infections using Information Theory
Jiaming Cui, Bijaya Adhikari, Arash Haddadan +4
One of the most significant challenges in combating against the spread of infectious diseases was the difficulty in estimating the true magnitude of infections. Unreported infectio…
Differentially private exact recovery for stochastic block models
Dung Nguyen, Anil Vullikanti
Stochastic block models (SBMs) are a very commonly studied network model for community detection algorithms. In the standard form of an SBM, the vertices (or nodes) of a graph…
Contrastive Explainable Clustering with Differential Privacy
Dung Nguyen, Ariel Vetzler, Sarit Kraus +1
This paper presents a novel approach to Explainable AI (XAI) that combines contrastive explanations with differential privacy for clustering algorithms. Focusing on k-median and k-…
Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks
Zirou Qiu, Abhijin Adiga, Madhav V. Marathe +4
Networked dynamical systems are widely used as formal models of real-world cascading phenomena, such as the spread of diseases and information. Prior research has addressed the pro…
UFID: A Unified Framework for Input-level Backdoor Detection on Diffusion Models
Zihan Guan, Mengxuan Hu, Sheng Li +1
Diffusion models are vulnerable to backdoor attacks, where malicious attackers inject backdoors by poisoning certain training samples during the training stage. This poses a signif…
Learning the Topology and Behavior of Discrete Dynamical Systems
Zirou Qiu, Abhijin Adiga, Madhav V. Marathe +4
Discrete dynamical systems are commonly used to model the spread of contagions on real-world networks. Under the PAC framework, existing research has studied the problem of learnin…
A Scalable Game-theoretic Approach to Urban Evacuation Routing and Scheduling
Kazi Ashik Islam, Da Qi Chen, Madhav Marathe +3
Evacuation planning is an essential part of disaster management where the goal is to relocate people under imminent danger to safety. However, finding jointly optimal evacuation ro…
Sample Complexity of Linear Regression Models for Opinion Formation in Networks
Haolin Liu, Rajmohan Rajaraman, Ravi Sundaram +3
Consider public health officials aiming to spread awareness about a new vaccine in a community interconnected by a social network. How can they distribute information with minimal…