A5019703184- Advanced Graph Theory Research
- Complex Network Analysis Techniques
- COVID-19 epidemiological studies
- Graph Labeling and Dimension Problems
- Opinion Dynamics and Social Influence
- Complexity and Algorithms in Graphs
- Computational Geometry and Mesh Generation
- Stochastic processes and statistical mechanics
- DNA and Biological Computing
- Gene Regulatory Network Analysis
- Interconnection Networks and Systems
- Plant and animal studies
- Game Theory and Voting Systems
- Optimization and Search Problems
- Insect-Plant Interactions and Control
- Distributed systems and fault tolerance
- Graph theory and applications
- Limits and Structures in Graph Theory
- Data-Driven Disease Surveillance
- Bayesian Modeling and Causal Inference
- Game Theory and Applications
- Opportunistic and Delay-Tolerant Networks
- Mobile Agent-Based Network Management
- Cold Atom Physics and Bose-Einstein Condensates
- Cooperative Communication and Network Coding
University of Virginia
2018-2025
Biocom
2016-2025
Warwick Hospital
2024
Weatherford College
2021
Flint Institute Of Arts
2021
Virginia Tech
2008-2018
Indian Institute of Science Bangalore
2008-2014
Manipal Academy of Higher Education
2012
Kasturba Medical College, Manipal
2012
Abstract We study allocation of COVID-19 vaccines to individuals based on the structural properties their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 24 months vaccinate citizens. These time and emergence new viral strains urge us find quick effective ways allocate contain pandemic. While current approaches use combinations age-based occupation-based prioritizations, our strategy marks a departure from such largely aggregate...
The largest eigenvalue of the adjacency matrix a network (referred to as spectral radius) is an important metric in its own right. Further, for several models epidemic spread on networks (e.g., ‘flu-like’ SIS model), it has been shown that dies out quickly if radius graph below certain threshold depends model parameters. This motivates strategy control by reducing underlying network.In this paper, we develop suite provable approximation algorithms removing minimum cost set edges (modeling...
The convergence of HPC and data intensive methodologies provide a promising approach to major performance improvements. This paper provides general description the interaction between traditional ML approaches motivates "Learning Everywhere" paradigm for HPC. We introduce concept "effective performance" that one can achieve by combining learning with simulation based approaches, distinguish as measured benchmark scores. To support promise integrating methods, this examines specific examples...
Objectives This research studies the role of slums in spread and control infectious diseases National Capital Territory India, Delhi, using detailed social contact networks its residents. Methods We use an agent-based model to study influenza Delhi through person-to-person contact. Two different are used: one which slum non-slum regions treated same, other 298 zones identified. In second network, slum-specific demographics activities assigned individuals whose homes reside inside these...
Given a network with groups, such as contact-network grouped by ages, which are the best groups to immunize control epidemic? Equivalently, how choose communities in social media like Facebook stop rumors from spreading? Immunization is an important problem multiple different domains epidemiology, public health, cyber security, and media. Additionally, clearly immunization at group scale (like schools communities) more realistic due constraints implementations compliance (e.g., it hard...
Considering the difficulty of interpreting generative model output, there is significant current research focused on determining meaningful evaluation metrics. Several recent approaches utilize "precision" and "recall," borrowed from classification domain, to individually quantify output fidelity (realism) diversity (representation real data variation), respectively. With increase in metric proposals, a need for unifying perspective, allowing easier comparison clearer explanation their...
Healthcare decision-making is largely reliant on evidence-based medicine; building skills in scientific reasoning and thinking among medical students becomes an important part of education. Medical India have no formal path to becoming physicians, scientists or academicians.This study examines students' perceptions regarding research improvement after participating the Mentored Student Project programme at Melaka Manipal College, Campus, India. Additionally, this paper describes initiatives...
Let G be a simple, undirected, finite graph with vertex set $V(G)$ and edge $E(G)$. A k-dimensional box is Cartesian product of closed intervals $[a_1,b_1]\times [a_2,b_2]\times\cdots\times [a_k,b_k]$. The boxicity G, box$(G)$, the minimum integer k such that can represented as intersection boxes; i.e., each mapped to two vertices are adjacent in if only their corresponding boxes intersect. $\mathcal{P}=(S,P)$ poset, where S ground P reflexive, antisymmetric transitive binary relation on S....
Given a network with groups, such as contact-network grouped by ages, which are the best groups to immunize control epidemic? Equivalently, how choose communities in social networks like Facebook stop rumors from spreading? Immunization is an important problem multiple different domains epidemiology, public health, cyber security and media. Additionally, clearly immunization at group scale (like schools communities) more realistic due constraints implementations compliance (e.g., it hard...
We study allocation of COVID-19 vaccines to individuals based on the structural properties their underlying social contact network. Using a realistic representation network for Commonwealth Virginia, we how limited number vaccine doses can be strategically distributed reduce overall burden pandemic. show that individuals' degree (number contacts) and total proximity time is significantly more effective than usually used age-based strategy in reducing infections, hospitalizations deaths. The...
Modern food systems facilitate rapid dispersal of pests and pathogens through multiple pathways. The complexity spread dynamics data inadequacy make it challenging to model the phenomenon also prepare for emerging invasions. We present a generic framework study spatio-temporal invasive species as multi-scale propagation process over time-varying network accounting climate, biology, seasonal production, trade demographic information. Machine learning techniques are used in novel manner...
This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning response. The consists of ( i) automatic semantic-aware scheduling method that coordinates jobs across two separate high performance computing systems; ii) a data collect, integrate organize county-level disaggregated for initialization post-simulation analysis; iii) digital twin social contact networks made up 288 Million individuals...
UVA-EpiHiper is a national scale agent-based model to support the US COVID-19 Scenario Modeling Hub (SMH). uses detailed representation of underlying social contact network along with data measured during course pandemic initialize and calibrate model. In this paper, we study role heterogeneity on complexity resulting epidemic dynamics using UVA-EpiHiper. We discuss various sources that encounter in use modeling analysis under scenarios. also how affects computational corresponding...
The spread of epidemics and malware is commonly modeled by diffusion processes on networks. Protective interventions such as vaccinations or installing anti-virus software are used to contain their spread. Typically, each node in the network has decide its own strategy securing itself, benefit depends which other nodes secure, making this a natural game-theoretic setting. There been lot work security game models, but most focus either simplified epidemic models homogeneous structure. We...
With increasing globalization, trade, and human movement, the rate of alien species introduction has increased all around globe. In addition, climate change is thought to exacerbate situation by allowing range expansion invasive into new areas. Predicting distribution under conditions important for identifying susceptible areas invasion developing strategies limiting their expansion. We used Maxent modeling predict one world's most aggressive weeds, Ageratina adenophora (Sprengel) R. King H....
Abduction is an inference approach that uses data and observations to identify plausible (and preferably, best) explanations for phenomena. Applications of abduction (e.g., robotics, genetics, image understanding) have largely been devoid human behavior. Here, we devise execute iterative abductive analysis process driven by the social sciences: behaviors interactions among groups subjects. One goal understand intra-group cooperation its effect on fostering collective identity. We build...