Other profiles: Scholar DBLP Twitter
Work
- 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
Education
- 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
Research Areas
- Computational modeling & simulation
- Data analytics
- Network science
- Stochastic processes
- Optimization
Research Domains
- Network Epidemiology
- Infectious disease forecasting
- Human mobility modeling
- Invasive species
Journals
- 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
Peer-reviewed Conferences/Workshops
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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
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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
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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
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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
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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
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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.
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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.
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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]
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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.
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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.
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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]
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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.
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A. Adiga, SV, and A. Vullikanti, To delay or not: temporal vaccination games on networks, IEEE INFOCOM 2016.
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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
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Q. F. Ying, SV, and D. M. Chiu, Modeling and Analysis of Scholar Mobility on Scientific Landscape, BigScholar (WWW’15 Companion), Florence, Italy
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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]
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E. Altman, P. Kumar, SV, and A. Kumar, Competition over Timeline in Social Networks, SNAA, co-held with ASONAM’13, Niagara Falls, Canada. [Slides]
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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]
Technical Reports
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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
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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
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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.
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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.
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A. Adiga, SV, J. Schlitt, …, C. Barrett, “Evaluating the impact of international airline suspensions on the early global spread of COVID-19“, medRxiv, 2020
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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
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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
Research Talks/Posters
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“Computational Modeling and Data Strategies for Predicting and Responding to Pandemics”, Intelligent Health Inspired Summit, May 2020
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“Estimating Global direct importation risk for COVID-19”, Pandemic Prediction and Forecasting Science & Technology workgroup, Feb 2020
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P. Corbett, SV, B. Lewis, “CDC Aedes Forecasting Challenge: Historical Average and Ecological Niche Modeling”, Vector-borne disease forecasting workshop, Feb 2020
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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.
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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)
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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
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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.
Other Talks
- 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.
Funding
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Co-PI: RAPID: COVID-19 Response Support: Building Synthetic Multi-scale Networks, National Science Foundation, ($173,640), National Science Foundation (NSF), 2020-2021
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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)
Press Coverage
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COVID-19 Modeling Support for Virginia Department of Health, Biocomplexity COVID-19 Response Team, https://www.vdh.virginia.gov/coronavirus/covid-19-data-insights/
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“Flattening the Curve”, Mini Med School Special Podcast: COVID-19 Charlottesville, 24 Jun 2020
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Panel member on “Rural Populations and Infectious Disease Transmission: Implications for COVID-19”, George Mason University, 9 Jun 2020
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J. Chen, S. Levin, S. Eubank, H. Mortveit, SV, A. Vullikanti, and M. Marathe “Networked Epidemiology for COVID-19”, SIAM News, 1 Jun 2020
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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
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Modeling the Spread of Epidemics”, The Pragati Podcast, 25 Mar 2020
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Panel member on “Batten Hour: Multidisciplinary perspectives on the coronavirus”, UVA Batten School of Leadership & Public Policy, 24 Feb 2020
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“To predict Flu’s spread, modelers turn to weather forecasts”, UVA Today, 18 Feb 2020
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“Using weather forecasts to predict flu activity”, AccuWeather Press, 28 Jan 2020
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“Researchers utilize holistic approach to predict severity of influenza season”, Cavalier Daily, 16 Jan 2020
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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
Responsibilities
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Editorial Board: Frontiers Big Data – Data Analytics for Social Impact
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Co-organizer: epiDAMIK 3.0: The 3rd International workshop on Epidemiology meets Data Mining and Knowledge discovery, coheld with SIGKDD 2020
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Delphi panel member for Epidemic Forecasting Reporting Guidelines (EPI-FORGE)
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TPC Member: COMSNETS (2015, 2016), IJCAI (2020, 2021), AAMAS 2021, AAAI 2021
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Conference Reviewer: SPCOM 2016, INFOCOM 2019
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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
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Local Organizing Committee, ICTS School and Workshop on Network Science in EECS, IISc., 2012
Mentoring
- 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)