- Research Assistant Professor (Sep 2021 – present)
- Research Scientist (Oct 2018 – Sep 2021)
- Biocomplexity Institute & Initiative, University of Virginia
- Biocomplexity Institute & Initiative, University of Virginia
- Computational Health Data Scientist (Dec 2017 – Oct 2018)
- Postdoctoral Associate (Feb 2015 – Nov 2017)
- Biocomplexity Institute, Virginia Tech
- Biocomplexity Institute, Virginia Tech
- Research Assistant (May – Nov 2014)
- Dept. of Information Engineering, Chinese University of Hong Kong
- Mentor: Prof. Dah Ming Chiu
- Student Intern (May – Aug 2007) , Bell Labs Research India
- Ph.D. (Aug. 2008 – Apr 2014) – Influence Dynamics on Social Networks
- Dept. of ECE, Indian Institute of Science
- Advisor: Prof. Anurag Kumar
- B.E. (Aug 2004- Jun 2008) – Dept. of ECE, College of Engg. Guindy
- Final Year Project: Relay Selection for Cooperative Diversity in Wireless Networks
- Computational modeling & simulation
- Data analytics
- Network science
- Stochastic processes
- Network Epidemiology
- Infectious disease forecasting
- Human mobility modeling
- Invasive species
- SV, A. Sadilek, A. Fadikar, C. L. Barrett, M. Biggerstaff, J. Chen, X. Dotiwalla, P. Eastham, B. Gipson, D. Higdon, O. Kucuktunc, A. Lieber, B. L. Lewis, Z. Reynolds, A. Vullikanti, L. Wang, M. Marathe, “Forecasting influenza activity using machine-learned mobility map“, accepted to appear in Nature Communications (2020)
- A.S. Poudel, B.B. Shrestha, M.D. Joshi, R. Muniappan, A. Adiga, SV, and P.K. Jha, “Predicting the current and future potential distribution of an invasive weed Ageratina adenophora in Chitwan-Annapurna Landscape, Nepal“, Mountain Research and Development, 2020
- A. Adiga, D. Dubhashi, B. Lewis, M. Marathe, SV, A. Vullikanti, “Mathematical Models for COVID-19 Pandemic: A Comparative Analysis“, Journal of the Indian Institute of Science 100, 793-807 (2020)
- A. Adiga, J. Chen, M. Marathe, H. Mortveit, SV, A. Vullikanti, “Data-Driven Modeling for Different Stages of Pandemic Response“, Journal of the Indian Institute of Science 100, 901-915 (2020)
- J. Chen, A. Vullikanti, S. Hoops, H. Mortveit, B. Lewis, SV, W. You, S. Eubank, M. Marathe, C. Barrett, and A. Marathe, “Medical Costs of Keeping the US Economy Open During COVID-19“, Scientific reports 10.1 (2020): 1-10
- P. Sambaturu, P. Bhattacharya, J. Chen, B. Lewis, M. Marathe, SV, and A. Vullikanti, “An automated approach for finding spatio-temporal patterns in disease spread“, JMIR Public Health Surveill 2020;6(3):e12842
- S. Eubank, I. Eckstrand, B. Lewis, SV, M. Marathe, and C. Barrett, “Commentary on Ferguson, et al., Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand“, Bulletin of Mathematical Biology 82.4 (2020): 1-7
- P. Telionis, SV, P. Corbett, and B. Lewis, “Methods for Rapid Mobility Estimation to Support Outbreak Response“, Health security 18.1 (2020): 1-15
- SV, J. Chen, A. Fadikar, S. Gupta, D. Higdon, B. Lewis, M. Marathe, H. Mortveit, A. Vullikanti, Optimizing spatial allocation of seasonal influenza vaccine under temporal constraints, PLOS Computational Biology (2019).
- SV, S. Wu, B. Shi, A. Marathe, M. Marathe, S. Eubank, L. Sah, A.P. Giri, L. Colavito, Nitin S, Sridhar V, Asokan R, R. Muniappan, G. Norton, and A. Adiga, Modeling commodity flow in the context of invasive species spread: Study of Tuta absoluta in Nepal., Elsevier Journal of Crop Protection (2019).
- A. Fadikar, D. Higdon, J. Chen, B. Lewis, SV, and M. Marathe, Calibrating a Stochastic Agent based model using Quantile-based Emulation, SIAM Journal of Uncertainty Quantification
- Q. F. Ying, D. M. Chiu, SV, and X. Zhang, User Modeling and Usage Profiling Based on Temporal Posting Behavior in OSNs, accepted to appear in Elsevier Online Social Networks and Media
- W. Yan, SV, and D. M. Chiu, A Population Model for Academia: Case Study of the Computer Science Community using DBLP Bibliography 1960-2016, accepted to appear in IEEE Transactions on Emerging Topics in Computing.
- SV, B. Lewis, J. Chen, D. Higdon, A. Vullikanti, M. Marathe, Using data-driven agent-based models for forecasting emerging infectious diseases, accepted to appear in Elsevier Epidemics, 2017.
- F. S. Tabataba, P. Chakraborty, N. Ramakrishnan, SV, J. Chen, B. Lewis, and M. Marathe, A Framework for Evaluating Epidemic Forecasts, accepted to appear in BMC Infectious Diseases, 2017.
- W. Yan, SV, and D. M. Chiu, Research collaboration and topic trends in Computer Science based on top active authors, PeerJ Computer Science 2:e41, 2016.
- SV and A. Kumar, Co-Evolution of Content Spread and Popularity in Mobile Opportunistic Networks, IEEE Transactions on Mobile Computing 13(11): 2498-2509, February 2014
L. Wang, A. Adiga, SV, J. Chen, B. Lewis, and M. Marathe, “Examining Deep Learning Models with Multiple Data Sources for COVID-19 Forecasting“, IEEE BigData Workshop on Data Science in Medicine and Healthcare (DSMH), 2020
A. S. Peddireddy, D. Xie, P. Patil, M. Wilson, D. Machi, SV, B. Klahn, P. Porebski, P. Bhattacharya, S. Dumbre, E. Raymond, and M. Marathe, “From 5Vs to 6Cs: Operationalizing Epidemic Data Management with COVID-19 Surveillance“, IEEE International Conference on Big Data (Big Data), 2020
A. Adiga, S. Singh, E. Choo, SV, M. Marathe, P. Jha, S. Dhakal, K. Poudel, B. B. Shreshta, R. Muniappan, S. Mahajan, A. Devkota, A. Adiga, “A Deep Learning Framework for Invasive Species Mapping using High-Resolution Satellite Imagery“, ASPRS Annual Conference, 2020
P. Sambaturu, B. Adhikari, B. A. Prakash, SV, and A. Vullikanti, “Designing Near-Optimal Temporal Interventions to Contain Epidemics“, International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2020
A. Adiga, SV, S. Wu, M. Marathe, S. Eubank, L. P. Sah, A. P. Giri, L. Colavito, R. Muniappan, “Understanding the Role of Seasonal Food Trade Networks in Invasive Species Spread“, SIAM Workshop of Network Science, 2019
M. Nath, SV, B. Kaperick, S. Eubank, M. Marathe, A. Marathe, and A. Adiga, Using Network Reliability to Understand International Food Trade Dynamics, COMPLEX NETWORKS 2018.
Q. F. Ying, D. M. Chiu, SV, and X. Zhang, Profiling OSN Users Based on Temporal Posting Patterns , ACM OSNeD 2018 (Online Social Networks and Media: Network Properties and Dynamics), co-held with The Web Conference (WWW) 2018.
SV, S. Wu, B. Shi, A. Marathe, M. Marathe, S. Eubank, L. P. Sah, A. P. Giri, L. Colavito, Nitin S, Sridhar V, Asokan R, R. Muniappan, G. Norton, and A. Adiga, Towards Robust Models of Food Flows and Their Role in Invasive Species Spread , IEEE International Conference on Big Data (IEEE Big Data), 2017. [Slides]
F. S. Tabataba, M. Hosseinipour, B. Lewis, F. S. Tabataba, SV, D. Higdon, J. Chen, and M. Marathe, Epidemic Forecasting by Combining Agent-Based Models and Smart Beam-Particle Filtering Framework, IEEE International Conference on Data Mining (ICDM) short paper, 2017.
SV, J. Chen, S. Gupta, B. Lewis, M. Marathe, H. Mortveit, and A. Vullikanti, Spatio-temporal optimization of seasonal vaccination using a metapopulation model of influenza, IEEE International Conference on Healthcare Informatics (ICHI) 2017.
SV, A. Marathe, S. Eubank, M. Marathe, A. Adiga Towards an Integrated Network-based Approach to Modeling the Dynamics of Invasive Plant Pests, to be presented at KDD 2016 Workshop on Data Science for Food, Energy and Water, San Francisco, August 2016 [Paper]
W. Yan, SV, and D. M. Chiu, Get To the Top and Stay There: A Study of Citation Rank Dynamics in Academia, Proceedings of the 25th International Conference Companion on World Wide Web (BigScholar), 2016.
A. Adiga, SV, and A. Vullikanti, To delay or not: temporal vaccination games on networks, IEEE INFOCOM 2016.
W. Yan, SV, and D. M. Chiu, Research Collaboration and Topic Trends in Computer Science – An Analysis Based on UCP Authors, SAVE- SD (WWW’15 Companion), Florence, Italy
Q. F. Ying, SV, and D. M. Chiu, Modeling and Analysis of Scholar Mobility on Scientific Landscape, BigScholar (WWW’15 Companion), Florence, Italy
SV and A. Kumar, Competition for Content Spread over Multiple Social Networks, presented at SCINSE, co-held with COMSNETS’14, Bangalore, India. (Best presentation award) [Slides]
SV and A. Kumar, Co-evolution of Content Popularity and Delivery in Mobile P2P Networks, INFOCOM’12, Orlando,FL. pdf, [Slides]
- SV and A. Kumar, Information Dissemination in Socially Aware Networks Under the Linear Threshold Model, NCC’11, Bangalore, India. [Slides]
J. Chen, A. Vullikanti, J. Santos, SV, S. Hoops, H. Mortveit, B. Lewis, W. You, S. Eubank, M. Marathe, C. Barrett, and A. Marathe, “Epidemiological and Economic Impact of COVID-19 in the US“, medRxiv, 2020
Z. Mehrab, A. G. Ranga, D. Sarkar, SV, Y. Chungbaek, S. Swarup, and M. Marathe “High resolution proximity statistics as early warning for US universities reopening during COVID-19“, medRxiv, 2020
N. Wu, X. Ben, B. Green, K. Rough, SV, M. Marathe, P. Eastham, A. Sadilek, and S. O’Banion, “Predicting Onset of COVID-19 with Mobility-Augmented SEIR model“, medRxiv, 2020.
A. Adiga, L. Wang, A. Sadilek, A. Tendulkar, SV, A. Vullikanti, G. Aggarwal, A. Talekar, X. Ben, J. Chen, B. Lewis, S. Swarup, M. Tambe, and M. Marathe, “Interplay of global multi-scale human mobility, social distancing, government interventions, and COVID-19 dynamics“, medRxiv, 2020.
A. Adiga, SV, J. Schlitt, …, C. Barrett, “Evaluating the impact of international airline suspensions on the early global spread of COVID-19“, medRxiv, 2020
E. A. Heinrichs, J. Sidhu, R. Muniappan, A. Fayad, A. Adiga, A. Marathe, J. Mcnitt, SV, Pest Risk Assessment of the Fall Armyworm, Spodoptera frugiperda in Egypt, report published by Feed the Future Innovation Lab for Integrated Pest Management, December 2017
SV and A. Kumar, Influence Spread in Social Networks: A Study via a Fluid Limit of the Linear Threshold Model, arXiv:1405.7096
- SV and A. Kumar, New Insights from an Analysis of Social Influence Networks under the Linear Threshold model, arXiv:1002.1335
“Computational Modeling and Data Strategies for Predicting and Responding to Pandemics”, Intelligent Health Inspired Summit, May 2020
“Estimating Global direct importation risk for COVID-19”, Pandemic Prediction and Forecasting Science & Technology workgroup, Feb 2020
P. Corbett, SV, B. Lewis, “CDC Aedes Forecasting Challenge: Historical Average and Ecological Niche Modeling”, Vector-borne disease forecasting workshop, Feb 2020
SV, L. Wang, A. Fadikar, B. Lewis, J. Chen, H. Carscadden, P. Sambaturu, A. Vullikanti, and M. Marathe, “Multi-model Multi-target Approaches for Forecasting Seasonal Influenza in the United States”, CSTE/CDC Seasonal Influenza Forecasting Workshop, Aug 2019
- Computing for Health: In silico approaches for health sciences, invited talk at the Indian Institute of Science, Bangalore, Jan 2019.
- Team 4Sight – CDC FluSight 2017-18, presentation at the CSTE/CDC Seasonal Influenza Forecasting Workshop, Atlanta, GA, Aug 2018.
Exploring optimal vaccine allocation using a national model of influenza, poster presented at UNC Going Viral Symposium, Chapel Hill, NC, Apr 2018 (Best Poster Award)
iFlu, e-Flu: where from and where to?, invited talk at Schiffert Health Center, Virginia Tech, Mar 2018.
- Resource optimization problems using a mathematical model of influenza, presented at the 6th Annual MIDAS Outreach Conference, Harvard T.H. Chan School of Public Health, November 2017
Hybrid models for ecological and anthropogenic drivers of pest invasion: Case study of Tuta Absoluta in Nepal, presented at International Conference on Biodiversity, Climate Change Assessment and Impacts on Livelihood, Kathmandu, Nepal, January 2017
- Modeling in the Time of Ebola: Using HPC Simulations to Understand Infectious Disease Dynamics, talk given at IISc. Bangalore and IIT Madras, February 2016
- Ebola Forecasting Challenge: Team Virginia Tech, talk given at NIH/RAPIDD Ebola Forecasting Challenge workshop, Bethesda, February 2016
- Calibration and Forecasting Framework for Infectious Diseases, poster presented at International Symposium for Next Generation Infrastructure (ISNGI), Washington D.C., September 2015
- Influence Dynamics on Social Networks , Thesis Colloquium, Apr. 2014 video
- Delay-Cost Optimal Coupon Delivery in Mobile Opportunistic Networks ,
- Indo-US Workshop on Machine Learning, Game theory and Optimization, IISc., 2014
- High Dimensional Network Analytics Workshop, Department of CSA, IISc., 2013
- Spread of Content and Interest in Mobile Opportunistic Networks,
- Intl. Conference on Networks in Biology, Social Sciences and Engg, IISc. 2012
- Department Student Colloquium, ECE, IISc, Dec. 2012
- Information Dissemination in Social Networks under the LT model, Workshop on Recent Trends in Social Networks: Algorithms, Models and Learning, held at TIFR, Mumbai, Jan. 2011
- Influence Spread in Social Networks, poster presented at Techvista organized by Microsoft Research, Bangalore, Jan. 2010.
- How to Give a Technical Talk?, NDSSL Seminar Series, Aug. 2016
- Evolution of Cooperation – Winners Don’t Punish, Game Theory course presentation, IISc, Spring 2010.
- Why SNA? A Network Engineer’s Perspective , survey talk given at the ECE Department, IISc Bangalore, Jan. 2010.
Co-PI: RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks, National Science Foundation, ($173,640), National Science Foundation (NSF), 2020-2021
Co-PI: RAPID: Collaborative: Transfer Learning Techniques for Better Response to COVID-19 in the US, National Science Foundation (NSF), ($25,000), 2020-2021
- Co-PI: Smart Targeting and Optimization for the Mitigation and Prevention of Influenza (STOMP-Flu). Center for Disease Control and Prevention (CDC) ($454,427, 2019-2020)
- Co-PI: Network-based Mobility Modeling for Complex Humanitarian Emergencies. Global Infectious Diseases Institute, University of Virginia ($98,750, 2019-2020)
- Co-PI: AccuWeather License to Use, Market and Resell 4-Week Influenza Forecast. AccuWeather ($55,000, 2018-2019)
- Co-PI: Assessment of Invasive Alien Species Distribution in the Chitwan-Annapurna-Landscape (CHAL) Region, Nepal. United States Agency for International Development (USAID) ($135,458, 2018-2019)
- Postdoc/key personnel: A High-resolution Interaction Based Approach to Modeling the Spread of Agricultural Invasive Species. United States Agency for International Development (USAID) ($1,000,000, 2015-2019)
COVID-19 Modeling Support for Virginia Department of Health, Biocomplexity COVID-19 Response Team, https://www.vdh.virginia.gov/coronavirus/covid-19-data-insights/
“Flattening the Curve”, Mini Med School Special Podcast: COVID-19 Charlottesville, 24 Jun 2020
Panel member on “Rural Populations and Infectious Disease Transmission: Implications for COVID-19”, George Mason University, 9 Jun 2020
J. Chen, S. Levin, S. Eubank, H. Mortveit, SV, A. Vullikanti, and M. Marathe “Networked Epidemiology for COVID-19”, SIAM News, 1 Jun 2020
Governor Northam, University of Virginia Biocomplexity Institute, RAND Corporation Present Infectious Disease Modeling on Impact of COVID-19 Mitigations in Virginia”, Office of the Governor, 14 Apr 2020
Modeling the Spread of Epidemics”, The Pragati Podcast, 25 Mar 2020
Panel member on “Batten Hour: Multidisciplinary perspectives on the coronavirus”, UVA Batten School of Leadership & Public Policy, 24 Feb 2020
“To predict Flu’s spread, modelers turn to weather forecasts”, UVA Today, 18 Feb 2020
“Using weather forecasts to predict flu activity”, AccuWeather Press, 28 Jan 2020
“Researchers utilize holistic approach to predict severity of influenza season”, Cavalier Daily, 16 Jan 2020
UVA Researchers Harnessing Big Data’s Power to Fight the Flu, UVA Today, October 25th, 2019.
- Modelling epidemics: the maths behind disease outbreaks, Elsevier, February 2019
- Researchers at Virginia Tech’s Biocomplexity Institute work to forecast flu-like weather, Collegiate Times, February 19th, 2018
- Virginia Tech Flu Forecasting Technology to be used by Accuweather , WSLS, Dec 6th 2017
- Virginia Tech researchers develop computer model to predict Zika movement, WSET, June 21st 2016
Editorial Board: Frontiers Big Data – Data Analytics for Social Impact
Co-organizer: epiDAMIK 3.0: The 3rd International workshop on Epidemiology meets Data Mining and Knowledge discovery, coheld with SIGKDD 2020
Delphi panel member for Epidemic Forecasting Reporting Guidelines (EPI-FORGE)
TPC Member: COMSNETS (2015, 2016), IJCAI (2020, 2021), AAMAS 2021, AAAI 2021
Conference Reviewer: SPCOM 2016, INFOCOM 2019
Journal Reviewer: IEEE Transactions on Mobile Computing, IEEE Transactions on Information Theory, Elsevier Theoretical Computer Science, PLOS Currents: Outbreaks, Springer Articial Intelligence Review, Epidemiology & Infection, Health Security, Elsevier Ecological Informatics, Elsevier Ecological Modeling, Simulation Modeling Practice & Theory, PLOS One, Health Aairs, PNAS, Americal Journal of Tropical Medicine & Hygiene, BMJ Open, F1000, PLOS Computational Biology, Journal of Theoretical Biology, Frontiers, Nature Scientic Reports, Journal of the Indian Institute of Science, PLOS One, Applied Soft Computing, Vaccine
Local Organizing Committee, ICTS School and Workshop on Network Science in EECS, IISc., 2012
- Akhil Peddireddy – Masters GRA (2019-20)
- Project: Real-time database for multi-modal spatiotemporal inuenza surveillance
- Andrew Murphy – Undergrad intern (Summer 2019)
- Project: Hierarchical seasonal autoregressive models for influenza forecasting
- Patrick Corbett – Undergrad intern (Spring 2019)
- Project: Forecasting Aedes mosquito abundance in United States
- Ethan Ludwick – Undergrad intern (Summer 2018)
- Project: Using machine learning and satellite imagery data to map C. odorata in Nepal
- Kingsley Nwosu – Undergrad intern (Summer 2017)
- Asia Taylor – Undergrad intern (Summer 2017)