Our team has been busy supporting the challenges of real-time epidemic science, originally pertaining to the pandemic but now so much more.
[218] Role of heterogeneity: National scale data-driven agent-based modeling for the US COVID-19 Scenario Modeling Hub. Epidemics. Sep 1;48:100779. Chen J, Bhattacharya P, Hoops S, Machi D, Adiga A, Mortveit H, Venkatramanan S, Lewis B, Marathe M (2024)
[217] Novel multi-cluster workflow system to support real-time HPC-enabled epidemic science: Investigating the impact of vaccine acceptance on COVID-19 spread. Journal of Parallel and Distributed Computing. Sep 1;191:104899. Bhattacharya P, Machi D, Chen J, Hoops S, Lewis B, Mortveit H, Venkatramanan S, Wilson ML, Marathe A, Porebski P, Klahn B (2024)
[216] Impact of waning immunity against SARS-CoV-2 severity exacerbated by vaccine hesitancy. PLoS computational biology. Aug 5;20(8):e1012211. Saad-Roy CM, Morris SE, Boots M, Baker RE, Lewis BL, Farrar J, Marathe MV, Graham AL, Levin SA, Wagner CE, Metcalf CJ (2024)
[215] Sufficient COVID-19 quarantine and testing on international travelers to forestall cross-border transmission after China's removal of the zero-COVID policy in early 2023. International Journal of Infectious Diseases. Aug 1;145:107097. Bojja D, Zuo S, Townsend JP (2024)
[214] Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations. Nature Communications. Jul 26;15(1):6289. Mathis SM, Webber AE, León TM, Murray EL, Sun M, White LA, Brooks LC, Green A, Hu AJ, Rosenfeld R, Shemetov D (2024)
[213] Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. Forty-first International Conference on Machine Learning. Jul 21. Kamarthi H, Kong L, Zhao Z, Zhang C, Prakash BA (2024)
[212] The power of an adversary in Glauber dynamics. The Thirty-Seventh Annual Conference on Learning Theory, PMLR. Jun 30 (pp. 1102-1124). Chin B, Moitra A, Mossel E, Sandon C (2024)
[211] Unlock the potential of vaccines in food-producing animals. Science. Jun 28;384(6703):1409-11. Laxminarayan R, Gleason A, Sheen J, Saad-Roy CM, Metcalf CJ, Palmer GH, Fèvre EM (2024)
[210] Stochastic Optimization and Learning for Two-Stage Supplier Problems. ACM Transactions on Probabilistic Machine Learning. Jun 17. Brubach B, Grammel N, Harris DG, Srinivasan A, Tsepenekas L, Vullikanti A (2024)
[209] Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals. ACM Transactions on Economics and Computation. Jun 10;12(2):1-28. Dickerson JP, Sankararaman K, Srinivasan A, Xu P, Xu Y (2024)
[208] A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width. Proceedings of the 56th Annual ACM Symposium on Theory of Computing. Jun 10 (pp. 503-514). Gaitonde J, Mossel E (2024)
[207] Synchronous dynamical systems on directed acyclic graphs: Complexity and algorithms. ACM Transactions on Computation Theory. Jun 10;16(2):1-34. Rosenkrantz DJ, Marathe MV, Ravi SS, Stearns RE (2024)
[206] Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections. Epidemics. Jun 1;47:100761. Porebski P, Venkatramanan S, Adiga A, Klahn B, Hurt B, Wilson ML, Chen J, Vullikanti A, Marathe M, Lewis B (2024)
[205] Predicting transcriptional outcomes of novel multigene perturbations with GEARS. Nature Biotechnology. Jun;42(6):927-35. Roohani Y, Huang K, Leskovec J (2024)
[204] Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design. Epidemics. May 24:100775. Runge MC, Shea K, Howerton E, Yan K, Hochheiser H, Rosenstrom E, Probert WJ, Borchering R, Marathe MV, Lewis B, Venkatramanan S (2024)
[203] The Impact of Risk Compensation Adaptive Behavior on the Final Epidemic Size. Available at SSRN 4825401. Espinoza B, Chen J, Orr M, Saad-Roy CM, Levin S, Marathe M (2024)
[202] Improving Risk Prediction of Methicillin-Resistant Staphylococcus aureus Using Machine Learning Methods With Network Features: Retrospective Development Study. JMIR AI. May 16;3(1):e48067. Kamruzzaman M, Heavey J, Song A, Bielskas M, Bhattacharya P, Madden G, Klein E, Deng X, Vullikanti A (2024)
[201] Barter Exchange with Shared Item Valuations. Proceedings of the ACM on Web Conference 2024. May 13 (pp. 199-210). Luque J, Duppala S, Dickerson J, Srinivasan A (2024)
[200] Distributions of 4-subtree patterns for uniform random unrooted phylogenetic trees. Journal of Theoretical Biology. May 7;584:111794. Choi KP, Kaur G, Thompson A, Wu T (2024)
[199] Network Agency: An Agent-based Model of Forced Migration from Ukraine. Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. May 6 (pp. 1372-1380). Mehrab Z, Stundal L, Swarup S, Venaktramanan S, Lewis B, Mortveit H, Barrett C, Pandey A, Wells C, Galvani A, Singer B (2024)
[198] Challenges of COVID-19 Case Forecasting in the US, 2020–2021. PLoS computational biology. May 6;20(5):e1011200. Lopez VK, Cramer EY, Pagano R, Drake JM, O’Dea EB, Adee M, Ayer T, Chhatwal J, Dalgic OO, Ladd MA, Linas BP (2024)
[197] Promoting External and Internal Equities Under Ex-Ante/Ex-Post Metrics in Online Resource Allocation. Forty-first International Conference on Machine Learning. May 1. Sankararaman KA, Srinivasan A, Xu P (2024)
[196] H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions. Proceedings of the 2024 SIAM International Conference on Data Mining (SDM) Apr: 280-288. Anand V, Cui J, Heavey J, Vullikanti A, Prakash BA (2024)
[195] Long ties accelerate noisy threshold-based contagions. Nature Human Behaviour. Apr 22:1-8. Eckles D, Mossel E, Rahimian MA, Sen S (2024)
[194] Computing epidemic metrics with edge differential privacy. International Conference on Artificial Intelligence and Statistics, PMLR. Apr 18 (pp. 4303-4311). Li GZ, Nguyen D, Vullikanti A (2024)
[193] Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the US COVID-19 Scenario Modeling Hub. Plos Medicine. Apr 17;21(4):e1004387. Jung SM, Loo SL, Howerton E, Contamin L, Smith CP, Carcelén EC, Yan K, Bents SJ, Levander J, Espino J, Lemaitre JC (2024)
[192] Citation Forecasting with Multi-Context Attention-Aided Dependency Modeling. ACM Transactions on Knowledge Discovery from Data. Apr 12;18(6):1-23. Ji T, Self N, Fu K, Chen Z, Ramakrishnan N, Lu CT (2024)
[191] A latent process approach to change-point detection of mixed-type observations. Quality Engineering. Apr 2;36(2):407-26. Chu S, Liu X, Marathe A, Deng X (2024)
[190] A Generalizable Theory-Driven Agent-Based Framework to Study Conflict-Induced Forced Migration. Proceedings of the AAAI Conference on Artificial Intelligence. Mar 24; 38(21):23027-23033. Mehrab Z, Stundal L, Venkatramanan S, Swarup S, Lewis BL, Mortveit HS, Barrett CL, Pandey A, Wells CR, Galvani AP, Singer BH (2024)
[189] Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections. Epidemics. Mar 21:100761. Porebski P, Venkatramanan S, Adiga A, Klahn B, Hurt B, Wilson ML, Chen J, Vullikanti A, Marathe M, Lewis B. (2024)
[188] Distributions of 4-subtree patterns for uniform random unrooted phylogenetic trees. Journal of Theoretical Biology. Mar 16:111794. Choi KP, Kaur G, Thompson A, Wu T (2024)
[187] Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals. ACM Transactions on Economics and Computation. Mar. Dickerson JP, Sankararaman KA, Srinivasan A, Xu P, Xu Y (2024)
[186] An agent-based framework to study forced migration: A case study of Ukraine. PNAS nexus. Mar;3(3):80. Mehrab Z, Stundal L, Venkatramanan S, Swarup S, Lewis B, Mortveit HS, Barrett CL, Pandey A, Wells CR, Galvani AP, Singer BH (2024)
[185] An uncertainty quantification framework for agent-based modeling and simulation in networked anagram games. Journal of Simulation. Mar 2:1-9. Hu Z, Liu X, Deng X, Kuhlman CJ (2024)
[184] The Planetary Child Health & Enterics Observatory (Plan-EO): A protocol for an interdisciplinary research initiative and web-based dashboard for mapping enteric infectious diseases and their risk factors and interventions in LMICs. PLOS ONE. Feb 27;19(2):e0297775. Colston JM, Fang B, Houpt EColston JM, Fang B, Houpt E, Chernyavskiy P, Swarup S, Gardner LM, Nong MK, Badr HS, Zaitchik BF, Lakshmi V, Kosek MN (2024)
[183] Modeling relaxed policies for discontinuation of methicillin-resistant Staphylococcus aureus contact precautions. Infection Control & Hospital Epidemiology. Feb 26:1-6. Cui J, Heavey J, Lin L, Klein EY, Madden GR, Sifri CD, Lewis B, Vullikanti AK, Prakash BA (2024)
[182] Citation Forecasting with Multi-Context Attention-Aided Dependency Modeling. ACM Transactions on Knowledge Discovery from Data. Feb 23. Ji T, Self N, Fu K, Chen Z, Ramakrishnan N, Lu CT (2024)
[181] Toward universal cell embeddings: integrating single-cell RNA-seq datasets across species with SATURN. Nature Methods. Feb 16:1-9. Rosen Y, Brbić M, Roohani Y, Swanson K, Li Z, Leskovec J (2024)
[180] Learning large graph property prediction via graph segment training. Advances in Neural Information Processing Systems. Feb 13;36. Cao K, Phothilimthana M, Abu-El-Haija S, Zelle D, Zhou Y, Mendis C, Leskovec J, Perozzi B (2024)
[179] PRODIGY: Enabling in-context learning over graphs. Advances in Neural Information Processing Systems. Feb 13;36. Huang Q, Ren H, Chen P, Kržmanc G, Zeng D, Liang PS, Leskovec J (2024)
[178] Uncertainty quantification over graph with conformalized graph neural networks. Advances in Neural Information Processing Systems. Feb 13;36. Huang K, Jin Y, Candes E, Leskovec J (2024)
[177] Zero-shot causal learning. Advances in Neural Information Processing Systems. Feb 13;36. Nilforoshan H, Moor M, Roohani Y, Chen Y, Šurina A, Yasunaga M, Oblak S, Leskovec J (2024)
[176] High dimensional, tabular deep learning with an auxiliary knowledge graph. Advances in Neural Information Processing Systems. Feb 13;36. Ruiz C, Ren H, Huang K, Leskovec J (2024)
[175] Faster approximate subgraph counts with privacy. Advances in Neural Information Processing Systems. Feb 13;36. Nguyen D, Halappanavar M, Srinivasan V, Vullikanti A (2024)
[174] A geometric model of opinion polarization. Mathematics of Operations Research. Feb 2;49(1):251-77. Hązła J, Jin Y, Mossel E, Ramnarayan G (2024)
[173] A simplicial epidemic model for COVID-19 spread analysis. PNAS. Jan 2; 121(1):e2313171120. Chen Y, Gel YR, Marathe MV, Poor HV (2024)
[172] Infection with alternate frequencies of SARS-CoV-2 vaccine boosting for patients undergoing antineoplastic cancer treatments. JNCI: Journal of the National Cancer Institute. Dec 1;115(12):1626-8. Townsend JP, Hassler HB, Emu B, Dornburg A (2023)
[171] Human mobility networks reveal increased segregation in large cities. Nature. Nov 29:1-7. Nilforoshan H, Looi W, Pierson E, Villanueva B, Fishman N, Chen Y, Sholar J, Redbird B, Grusky D, Leskovec J (2023)
[170] Coupled models of genomic surveillance and evolving pandemics with applications for timely public health interventions. Proceedings of the National Academy of Sciences. Nov 28;120(48):e2305227120. Espinoza B, Adiga A, Venkatramanan S, Warren AS, Chen J, Lewis BL, Vullikanti A, Swarup S, Moon S, Barrett CL, Athreya S, et al. (2023)
[169] Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty. Nature Communications. Nov 20; 14(1):7260. Howerton E, Contamin L, Mullany LC, Qin M, Reich NG, Bents S, Borchering RK, Jung SM, Loo SL, Smith CP, Levander J, et al. (2023)
[168] Seasonality of endemic COVID-19. Mbio. Nov 8:e01426-23. Townsend JP, Hassler HB, Lamb AD, Sah P, Alvarez Nishio A, Nguyen C, Tew AD, Galvani AP, Dornburg A (2023)
[167] Online matching frameworks under stochastic rewards, product ranking, and unknown patience. Operations Research. Oct 27. Brubach B, Grammel N, Ma W, Srinivasan A (2023)
[166] Improved Sample-Complexity Bounds in Stochastic Optimization. Operations Research. Oct 17. Baveja A, Chavan A, Nikiforov A, Srinivasan A, Xu P (2023)
[165] VQA-GNN: Reasoning with Multimodal Knowledge via Graph Neural Networks for Visual Question Answering. Proceedings of the IEEE/CVF International Conference on Computer Vision. Oct 2; 21582-21592. Wang Y, Yasunaga M, Ren H, Wada S, Leskovec J (2023)
[164] Using spectral characterization to identify healthcare-associated infection (HAI) patients for clinical contact precaution. Scientific Reports. Sep 27;13(1):16197. Cui J, Cho S, Kamruzzaman M, Bielskas M, Vullikanti A, Prakash BA (2023)
[163] Group fairness in set packing problems. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. Aug 19; 391-399. Duppala S, Luque J, Dickerson J, Srinivasan A (2023)
[162] Predicting transcriptional outcomes of novel multigene perturbations with gears. Nature Biotechnology. Aug 17;1-9. Roohani Y, Huang K, Leskovec J (2023)
[161] Are all underimmunized measles clusters equally critical? Royal Society Open Science. Aug 16;10(8):230873. Afroj Moon S, Marathe A, Vullikanti A (2023)
[160] A framework for modeling human behavior in large-scale agent-based epidemic simulations. Simulation. Aug 8; 99(12):1183-1211. de Mooij J, Bhattacharya P, Dell’Anna D, Dastani M, Logan B, Swarup S (2023)
[159] A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Aug 6; 4584-4594. Ma J, Chen C, Vullikanti A, Mishra R, Madden G, Borrajo D, Li J. (2023)
[158] Identifying Complicated Contagion Scenarios from Cascade Data. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Aug 6; 4135-4145. Harrison G, Alabsi Aljundi A, Chen J, Ravi SS, Vullikanti AK, Marathe MV, Adiga A (2023)
[157] Planning to fairly allocate: Probabilistic fairness in the restless bandit setting. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Aug 6; 732-740. Herlihy C, Prins A, Srinivasan A, Dickerson JP (2023)
[156] Graph and geometry generative modeling for drug discovery. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Aug 6; 5833-5834. Xu M, Liu M, Jin W, Ji S, Leskovec J, Ermon S (2023)
[155] When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. Aug 6; 1057-1072. Kamarthi H, Kong L, Rodríguez A, Zhang C, Prakash BA (2023)
[154] Deploying vaccine distribution sites for improved accessibility and equity to support pandemic response. Autonomous Agents and Multi-Agent Systems. Oct;37(2):31. Li GZ, Li A, Marathe M, Srinivasan A, Tsepenekas L, Vullikanti A. (2023)
[153] Efficient and Equitable Deployment of Mobile Vaccine Distribution Centers. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. Aug 19. Chen, Da Qi and Li, Ann and Li, George Z. and Marathe, Madhav and Srinivasan, Aravind and Tsepenekas, Leonidas and Vullikanti, Anil (2023)
[152] Adaptive group testing strategy for infectious diseases using social contact graph partitions. Scientific Reports. Jul 26;13(1):12102. Zhang J, Heath LS (2023)
[151] Role of masks in mitigating viral spread on networks. Physical Review E. Jul 24;108(1):014306. Tian Y, Sridhar A, Wu CW, Levin SA, Carley KM, Poor HV, Yağan O (2023)
[150] Geometric latent diffusion models for 3d molecule generation. Proceedings of the 40th International Conference on Machine Learning. Jul 3; 38592-38610. PMLR. Xu M, Powers AS, Dror RO, Ermon S, Leskovec J (2023)
[149] Autoregressive diffusion model for graph generation. Proceedings of the 40th International Conference on Machine Learning. Jul 3; 17391-17408. PMLR. Kong L, Cui J, Sun H, Zhuang Y, Prakash BA, Zhang C (2023)
[148] Reconstructing an epidemic outbreak using Steiner connectivity. Proceedings of the AAAI Thirty-Seventh Conference on Artificial Intelligence. Jun 26; 11613-11620. Mishra R, Heavey J, Kaur G, Adiga A, Vullikanti A (2023)
[147] Detecting Sources of Healthcare Associated Infections. Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence. Jun 26; 4347-4355. Jang H, Fu A, Cui J, Kamruzzaman M, Prakash BA, Vullikanti A, Adhikari B, Pemmaraju SV (2023)
[146] Phase-informed Bayesian ensemble models improve performance of COVID-19 forecasts. Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence. Jun 26;15647-15653. Adiga A, Kaur G, Wang L, Hurt B, Porebski P, Venkatramanan S, Lewis B, Marathe MV (2023)
[145] Rawlsian fairness in online bipartite matching: Two-sided, group, and individual. Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence. Jun 26; 5624-5632. Esmaeili S, Duppala S, Cheng D, Nanda V, Srinivasan A, Dickerson JP (2023)
[144] Einns: Epidemiologically-informed neural networks. Proceedings of the AAAI Thirty-Seventh Conference on Artificial Intelligence. Jun 26; 14453-14460. Rodríguez A, Cui J, Ramakrishnan N, Adhikari B, Prakash BA (2023)
[143] Spreading processes with mutations over multilayer networks. Proceedings of the National Academy of Sciences. Jun 13;120(24):e2302245120. Sood M, Sridhar A, Eletreby R, Wu CW, Levin SA, Yağan O, Poor HV (2023)
[142] Global incidence in hospital-associated infections resistant to antibiotics: An analysis of point prevalence surveys from 99 countries. PLoS Medicine. Jun 13;20(6):e1004178. Balasubramanian R, Van Boeckel TP, Carmeli Y, Cosgrove S, Laxminarayan R (2023)
[141] A latent process approach to change-point detection of mixed-type observations. Quality Engineering. Jun 9:1-20. Chu S, Liu X, Marathe A, Deng X (2023)
[140] Pac-learning for strategic classification. Journal of Machine Learning Research. Jun 23; 24(192):1-38. Sundaram R, Vullikanti A, Xu H, Yao F (2023)
[139] Towards Optimal and Scalable Evacuation Planning Using Data-driven Agent Based Models. Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems. Islam KA, Chen DQ, Marathe M, Mortveit H, Swarup S, Vullikanti A (2023)
[138] AI & Multi-agent Systems for Data-centric Epidemic Forecasting. Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems. May 30; 2943-2945. Rodríguez A (2023)
[137] Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses. Frontiers in Digital Health. May 16;5:1060828. Das Swain V, Xie J, Madan M, Sargolzaei S, Cai J, De Choudhury M, Abowd GD, Steimle LN, Prakash BA (2023)
[136] Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations. eLife. Apr 21;12:e81916. Sherratt K, Gruson H, Johnson H, Niehus R, Prasse B, Sandmann F, Deuschel J, Wolffram D, Abbott S, Ullrich A, Gibson G, et al . (2023)
[135] Foundation models for generalist medical artificial intelligence. Nature. Apr 13; 616(7956):259-65. Moor M, Banerjee O, Abad ZS, Krumholz HM, Leskovec J, Topol EJ, Rajpurkar P (2023)
[134] Airborne disease transmission during indoor gatherings over multiple time scales: Modeling framework and policy implications. PNAS. April 10; 120(16): e2216948120. Dixit AK, Espinoza B, Qiu Z, Vullikanti A, Marathe MV (2023)
[133] Modeling large river basins and flood plains with scarce data: Development of the large basin data portal. Hydrology. Apr 6;10(4):87. Abu-Saymeh R, Godref A, Alexander KA (2023)
[132] Bayesian Sparse Regression for Mixed Multi-Responses with Application to Runtime Metrics Prediction in Fog Manufacturing. Technometrics. Apr 3;65(2):206-19. Chen X, Kang X, Jin R, Deng X (2023)
[131] COVID-19 non-pharmaceutical interventions: data annotation for rapidly changing local policy information. Scientific Data. Mar 9;10(1):126. Hurt B, Hoque OB, Mokrzycki F, Mathew A, Xue M, Gabitsinashvili L, Mokrzycki H, Fischer R, Telesca N, Xue LA, Ritchie J, et al. (2023)
[130] Coursing hyenas and stalking lions: the potential for inter-and intraspecific interactions. Plos one. Feb 3; 18(2):e0265054. Barker NA, Joubert FG, Kasaona M, Shatumbu G, Stowbunenko V, Alexander KA, Slotow R, Getz WM (2023)
[129] A geometric model of opinion polarization. Mathematics of Operations Research. Feb 2. Hązła J, Jin Y, Mossel E, Ramnarayan G (2023)
[128] Infection by SARS‐CoV‐2 with alternate frequencies of mRNA vaccine boosting. Journal of medical virology. Feb;95(2):e28461. Townsend JP, Hassler HB, Dornburg A (2023)
[127] Impact of SARS-CoV-2 vaccination of children ages 5–11 years on COVID-19 disease burden and resilience to new variants in the United States, November 2021–March 2022: A multi-model study. The Lancet Regional Health–Americas. Jan 1; 17. Borchering RK, Mullany LC, Howerton E, Chinazzi M, Smith CP, Qin M, Reich NG, Contamin L, Levander J, Kerr J, Espino J, et al. (2023)
[126] Active sensing for epidemic state estimation using abm-guided machine learning. Proceedings of the Multi-agent-based Simulation (MABS) Workshop. Saliba S, Dadgostari F, Hoops S, Mortveit HS, Swarup S (2023)
[125] Improved bi-point rounding algorithms and a golden barrier for k-median. Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms (SODA). 987–1011. SIAM. Gowda KN, Pensyl T, Srinivasan A, Trinh K (2023)
[124] Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support. The International Journal of High Performance Computing Applications. Jan; 37(1):4–27. Bhattacharya P, Chen J, Hoops S, Machi D, Lewis B, Venkatramanan S, Wilson ML, Klahn B, Adiga A, Hurt B, et al. (2023)
[123] End-to-end stochastic optimization with energy-based model. NeurIPS 2022. Kong L, Cui J, Yuchen, Zhuang Y, Feng R, Prakash BA, Zhang C (2022)
[122] Greaselm: Graph reasoning enhanced language models. International conference on learning representations. Zhang X, Bosselut A, Yasunaga M, Ren H, Liang P, Manning CD, Leskovec J (2022)
[121] Deep bidirectional language-knowledge graph pretraining. Advances in Neural Information Processing Systems. Dec 6; 35:37309–37323. Yasunaga M, Bosselut A, Ren H, Zhang X, Manning CD, Liang PS, Leskovec J (2022)
[120] Modeling and active learning for experiments with quantitative-sequence factors. Journal of the American Statistical Association. Oct 27; 1–15. Xiao Q, Wang Y, Mandal A, Deng X. (2022)
[119] Learning to accelerate partial differential equations via latent global evolution. NeurIPS 2022. Wu T, Maruyama T, Leskovec J (2022)
[118] Scalable and memory-efficient algorithms for controlling networked epidemic processes using multiplicative weights update method. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. Jan; 5164–5170. Sambaturu P, Minutoli M, Halappanavar M, Kalyanaraman A, Vullikanti A (2022)
[117] CAMul: Calibrated and accurate multi-view time-series forecasting. Proceedings of the ACM Web Conference 2022. Apr 25; 3174–3185. Kamarthi H, Kong L, Rodríguez A, Zhang C, Prakash BA (2022)
[116] Artificial intelligence foundation for therapeutic science. Nature Chemical Biology. Oct; 18(10):1033–1036. Huang K, Fu T, Gao W, Zhao Y, Roohani Y, Leskovec J, Coley CW,Xiao C, Sun J, Zitnik M (2022)
[115] Universal healthcare as pandemic preparedness: The lives and costs that could have been saved during the covid-19 pandemic. Proceedings of the National Academy of Sciences. Jun 21; 119(25):e2200536119. Galvani AP, Parpia AS, Pandey A, Sah P, Colón K, Friedman G, Campbell T, Kahn JG, Singer BH, Fitzpatrick MC (2022)
[114] Identifying correlates of emergent behaviors in agent-based simulation models using inverse reinforcement learning. 2022 Winter Simulation Conference (WSC). IEEE. Dadgostari F, Swarup S, Adams S, Beling P, Mortveit HS (2022)
[113] The United States COVID-19 Forecast Hub dataset. Scientific Data. Aug 1; 9(1):1–15. Cramer EY, Huang Y, Wang Y, Ray EL, Cornell M, Bracher J, Brennen A, Rivadeneira AJC, Gerding A, House K, et al. (2022)
[112] Differentiable agent-based epidemiological modeling for end-to-end learning. ICML 2022 Workshop AI for Agent-Based Modelling. Chopra A, Rodríguez A, Subramanian J, Krishnamurthy B, Prakash BA, Raskar R (2022)
[111] Effective social network-based allocation of covid-19 vaccines. Proceedings of the KDD Health Day. Aug 14. J, Hoops S, Marathe A, Mortveit H, Lewis B, Venkatramanan S, Haddadan A, Bhattacharya P, Adiga A, Vullikanti A, Srinivasan A, Wilson ML, Ehrlich G, Fenster M, Eubank S, Barrett C, Marathe M (2022)
[110] A new notion of individually fair clustering: α-equitable k-center. International Conference on Artificial Intelligence and Statistics. May 3; 6387–6408. PMLR. Chakrabarti D, Dickerson JP, Esmaeili SA, Srinivasan A, Tsepenekas L (2022)
[109] Exacerbation of covid-19 mortality by the fragmented united states healthcare system: A retrospective observational study. The Lancet Regional Health-Americas. Aug 1; 12:100264. Campbell T, Galvani AP, Friedman G, Fitzpatrick MC (2022)
[108] Microbiome analysis for wastewater surveillance during covid-19. Mbio, Aug 30; 13(4):e00591–22. Brumfield KD, Leddy M, Usmani M, Cotruvo JA, Tien CT, Dorsey S, Graubics K, Fanelli B, Zhou I, Registe N, Dadlani M, Wimalarante M, Jinasena D, Abayagunawardena R, Withanachchi C, Huq A, Jutla A, Colwell R (2022)
[107 ] Controlling epidemic spread using probabilistic diffusion models on networks. International Conference on Artificial Intelligence and Statistics, May 3; 11641–11654. PMLR. Babay AE, Dinitz M, Srinivasan A, Tsepenekas L, Vullikanti A (2022)
[106 ] Modelling healthcare associated infections with hypergraphs. epiDAMIK 5.0: The 5th International workshop on Epidemiology meets Data Mining and Knowledge discovery at KDD 2022, Anand V, Prakash BA (2022)
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[66] BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments. arXiv:2405.17631. May 27. Roohani Y, Vora J, Huang Q, Steinhart Z, Marson A, Liang P, Leskovec J (2024)
[65] STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases. arXiv:2404.13207. Apr 19. Wu S, Zhao S, Yasunaga M, Huang K, Cao K, Huang Q, Ioannidis VN, Subbian K, Zou J, Leskovec J (2024)
[64] Wastewater-based Epidemiology for COVID-19 Surveillance: A Survey. arXiv:2403.15291. Mar 22. Chen C, Kaur G, Adiga A, Espinoza B, Venkatramanan S, Warren A, Lewis B, Crow J, Singh R, Lorentz A, Toney D (2024)
[63] Predicting drug outcome of population via clinical knowledge graph. medRxiv. Mar 8. Brbic M, Yasunaga M, Agarwal P, Leskovec J (2024)
[62] Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting. arXiv:2402.18697. Feb 28. Chang S, Koehler F, Qu Z, Leskovec J, Ugander J (2024)
[61] LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. arXiv:2402.16132. Feb 25. Liu H, Zhao Z, Wang J, Kamarthi H, Prakash BA (2024)
[60] Towards Improved Uncertainty Quantification of Stochastic Epidemic Models Using Sequential Monte Carlo. arXiv:2402.15619. Feb 23. Fadikar A, Stevens A, Collier N, Toh KB, Morozova O, Hotton A, Clark J, Higdon D, Ozik J (2024)
[59] Sample-Efficient Linear Regression with Self-Selection Bias. arXiv:2402.14229. Feb 22. Gaitonde J, Mossel E (2024)
[58] Uncertainty Quantification for Forward and Inverse Problems of PDEs via Latent Global Evolution. arXiv:2402.08383. Feb 13. Wu T, Neiswanger W, Zheng H, Ermon S, Leskovec J (2024)
[57] Evaluation of FluSight influenza forecasting in the 2021-22 and 2022-23 seasons with a new target laboratory-confirmed influenza hospitalizations. medRxiv. Dec 11. Mathis SM, Webber AE, Basu A, Drake JM, White LA, Murray EL, Sun M, Leon TM, Hu AJ, Shemetov D, Brooks LC (2023)
[56] Relational Deep Learning: Graph Representation Learning on Relational Databases. arXiv:2312.04615. Dec 7. Fey M, Hu W, Huang K, Lenssen JE, Ranjan R, Robinson J, Ying R, You J, Leskovec J (2023)
[54] Universal Cell Embeddings: A Foundation Model for Cell Biology. bioRxiv. doi: 10.1101/2023.11.28.568918 Nov 29. Rosen Y, Roohani Y, Agrawal A, Samotorcan L, Consortium TS, Quake SR, Leskovec J (2023)
[53] Potential impact of annual vaccination with reformulated COVID-19 vaccines: lessons from the US COVID-19 Scenario Modeling Hub. medRxiv. Nov 11. Jung SM, Loo SL, Howerton E, Contamin L, Smith CP, Carcelén EC, Yan K, Bents SJ, Levander J, Espino J, Lemaitre JC, et al. (2023)
[52] A Unified Approach to Learning Ising Models: Beyond Independence and Bounded Width. arXiv:2311.09197. Nov 15. Gaitonde J, Mossel E (2023)
[51] Sufficient COVID-19 quarantine and testing on international travelers from China. medRxiv. Nov 4. Bojja D, Zuo S, Townsend JP (2023)
[50] Scenario Design for Infectious Disease Projections: Integrating Concepts from Decision Analysis and Experimental Design. medRxiv. Oct 12. Runge MC, Shea K, Howerton E, Yan K, Hochheiser H, Rosenstrom E, Probert WJ, Borchering R, Marathe MV, Lewis B, Venkatramanan S, et al. (2023)
[49] Combinative Cumulative Knowledge Processes. arXiv:2309.05638. Sep 11. Brandenberger A, Marcussen C, Mossel E, Sudan M (2023)
[48] Influence Maximization in Ising Models. arXiv:2309.05206. Sep 11. Chen Z, Mossel E (2023)
[47] Simulation-assisted optimization for large-scale evacuation planning with congestion-dependent delays. arXiv:2209.01535. Aug 19. Islam KA, Da Qi Chen MM, Mortveit H, Swarup S, Vullikanti A (2023)
[46] Communication-Free Distributed GNN Training with Vertex Cut. arXiv:2308.03209. Aug 6. Cao K, Deng R, Wu S, Huang EW, Subbian K, Leskovec J (2023)
[45] Informing pandemic response in the face of uncertainty. An evaluation of the US COVID-19 Scenario Modeling Hub. medRxiv. Jul 3. Howerton E, Contamin L, Mullany LC, Qin M, Reich NG, Bents S, Borchering RK, Jung SM, Loo SL, Smith CP, Levander J, et al. (2023)
[44] Infection by SARS-CoV-2 with alternate frequencies of mRNA vaccine boosting for patients undergoing antineoplastic treatment for cancer. medRxiv. May 30. Townsend JP, Hassler H, Emu B, Dornburg A (2023)
[43] Uncertainty quantification over graph with conformalized graph neural networks. arXiv:2305.14535. May 23. Huang K, Jin Y, Candes E, Leskovec J (2023)
[42] Learning Large Graph Property Prediction via Graph Segment Training. arXiv:2305.12322. May 21. Cao K, Phothilimthana PM, Abu-El-Haija S, Zelle D, Zhou Y, Mendis C, Leskovec J, Perozzi B (2023)
[41] Spatial-Temporal Networks for Antibiogram Pattern Prediction. arXiv:2305.01761. May 2. Fu X, Chen C, Dong Y, Vullikanti A, Klein E, Madden G, Li J (2023)
[40] Learning Controllable Adaptive Simulation for Multi-resolution Physics. arXiv:2305.01122. May 1. Wu T, Maruyama T, Zhao Q, Wetzstein G, Leskovec J (2023)
[39] The Planetary Child Health and Enterics Observatory (Plan-EO): a Protocol for an Interdisciplinary Research Initiative and Web-Based Dashboard for Climate-Informed Mapping of Enteric Infectious Diseases and their Risk Factors and Interventions in Low- and Middle-Income Countries. Research Square. Apr 18. Colston JM, Chernyavskiy P, Gardner L, Fang B, Houpt E, Swarup S, Badr H, Zaitchik B, Lakshmi V, Kosek M (2023)
[38] AutoTransfer: AutoML with Knowledge Transfer--An Application to Graph Neural Networks. arXiv:2303.07669. Mar 14. Cao K, You J, Liu J, Leskovec J (2023)
[37] Relational multi-task learning: Modeling relations between data and tasks. arXiv:2303.07666. Mar 14. Cao K, You J, Leskovec J (2023)
[36] Medium-term scenarios of COVID-19 as a function of immune uncertainties and chronic disease. medRxiv. Mar 10. Saad-Roy CM, Morris SE, Baker RE, Farrar J, Graham AL, Levin SA, Wagner CE, Metcalf CJE, Grenfell BM (2023)
[35] The Power of an Adversary in Glauber Dynamics. arXiv:2302.10841. Feb 21. Chin B, Moitra A, Mossel E, Sandon C (2023)
[34] Towards Universal Cell Embeddings: Integrating Single-cell RNA-seq Datasets across Species with SATURN. bioRxiv doi: 10.1101/2023.02.03.526939. Feb 3. Rosen Y, Brbić M, Roohani Y, Swanson K, Li Z, Leskovec J (2023)
[33] Zero-shot causal learning. arXiv:2301.12292. Jan 28. Nilforoshan H, Moor M, Roohani Y, Chen Y, Šurina A, Yasunaga M, Oblak S, Leskovec J (2023)
[32] Online Dependent Rounding Schemes. arXiv:2301.08680. Jan 20. Srinivasan A, Wajc D (2023)
[31] Einns: Epidemiologically-informed neural networks. arXiv:2202.10446. Feb 21. Rodríguez A, Cui J, Ramakrishnan N, Adhikari B, Prakash BA (2022)
[30] Data-driven real-time strategic placement of mobile vaccine distribution. medRxiv. Jun 28. Mehrab Z, Wilson ML, Chang S, Harrison G, Lewis B, Telionis A, Crow J, Kim D, Spillmann S, Peters K, Leskovec J, Marathe MV (2022)
[29] Interpreting county level covid-19 infection and feature sensitivity using deep learning time series models. arXiv:2210.03258. Islam MK, Zhu D, Liu Y, Erkelens A, Daniello N, Fox J (2022)
[28] Back2future: Leveraging backfill dynamics for improving real-time predictions in future. arXiv:2106.04420. Kamarthi H, Rodríguez A, Prakash BA (2021)
[27] Is this correct? Let's check! arXiv:2211.12301. Nov 22. Ben-Eliezer O, Mikulincer D, Mossel E, Sudan M (2022)
[26] Deploying Vaccine Distribution Sites for Improved Accessibility and Equity to Support Pandemic Response. arXiv:2202.04705. To appear in Proceedings of the AAMAS 2022. Feb 9. Li G, Li A, Marathe M, Srinivasan A, Tsepenekas L, Vullikanti A (2022) Best Student Paper Award.
[25] Impact of weeknight and weekend curfews using mobility data: a case study of Bengaluru urban. medRxiv. Jan 28. Adiga A, Athreya S, Marathe M, Midthala J, Rathod N, Sundaresan R, Venkataramanan S, Yasodharan S (2022)
[24] Projecting the seasonality of endemic COVID-19. medRxiv. Jan 28. Townsend J, Lamb A, Hassler H, Sah P, Alvarez-Nishio A, Nguyen C, Galvani A, Dornburg A (2022)
[23] SARS-CoV-2 Testing Strategies for Outbreak Mitigation in Vaccinated Populations. medRxiv. Jan 1. Kumar C, Balasubramanian R, Ongarello S, Carmona S, Laxminarayan R (2022) [Also published in PLOS ONE. 17(7): e0271103. July 13 (2022).]
[22] A Markov Decision Process Framework for Efficient and Implementable Contact Tracing and Isolation. arXiv:2112.15547. Dec 31. Li G, Haddadan A, Li A, Marathe M, Srinivasan A, Vullikanti A, Zhao Z (2021)
[21] Earthquake Nowcasting with Deep Learning. arXiv:2201.01869. Dec 18. Fox G, Rundle J, Donnellan A, Feng B (2021)
[20] Vaccine breakthrough and the invasion dynamics of SARS-CoV-2 variants. medRxiv. Dec 14. Saad-Roy CM, Levin SA, Gog JR, Farrar J, Wagner CE, Metcalf CJE, Grenfell BT (2021)
[19] SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs. arXiv:2110.14890. Oct 28. Ren H, Dai H, Dai B, Chen X, Zhou D, Leskovec J, Schuurmans D (2021)
[18] Phase transitions and the theory of early warning indicators for critical transitions. arXiv:2110.12287. Oct 23. Hagstrom G, Levin S (2021)
[17] Informing University COVID-19 Decisions Using Simple Compartmental Models. medRxiv. July 6. Hurt B, Adiga A, Marathe M, Barrett C (2021)
[16] Evaluating the Utility of High-Resolution Proximity Metrics in Predicting the Spread of COVID-19. medRxiv. Jun 10. Mehrab Z, Adiga A, Marathe M, Venkatramanan S, Swarup S (2021). [Also published in ACM Trans. Spatial Algorithms Syst. 8(4): 26. Nov (2022).]
[15] Strategies to Mitigate COVID-19 Resurgence Assuming Immunity Waning: A Study for Karnataka, India. medRxiv. May 29. Adiga A, Athreya S, Lewis B, Marathe M, Rathod N, Sundaresan R, Swarup S, Venkatramanan S, Yasodharan S (2021)
[14] Quantifying the potential for dominant spread of SARS-CoV-2 variant B. 1.351 in the United States. medRxiv. May 12. Sah P, Vilches T, Shoukat A, Pandey A, Fitzpatrick M, Moghadas S, Galvani A (2021)
[13] Timing is everything: the relationship between COVID outcomes and the date at which mask mandates are relaxed. medRxiv. Apr 6. Shoukat A, Galvani A, Fitzpatrick M (2021)
[12] WiFi mobility models for COVID-19 enable less burdensome and more localized interventions for university campuses. medRxiv. Mar 24. Swain V, Xie J, Madan M, Sargolzaei S, Cai J, De Choudhury M, Abowd G, Steimle L, Prakash BA.
[11] Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness. medRxiv. Feb 15. Chen J, Hoops S, Marathe A, Mortveit H, Lewis B, Venkatramanan S, Haddadan A, Bhattacharya P, Adiga A, Vullikanti A, Srinivasan A, Wilson M, Ehrlich G, Fenster M, Eubank S, Barrett C, Marathe M (2021)
[10] Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. medRxiv. Feb 5. Cramer EY, et al (2021)
[9] Using Mobility Data to Understand and Forecast COVID19 Dynamics. medRxiv. Dec 15. Wang L, Ben X, Adiga A, Sadilek A, Tendulkar A, Venkatramanan S, Vullikanti A, Aggarwal G, Talekar A, Chen J, Lewis B, Swarup S, Kapoor A, Tambe M, Marathe M (2020)
[8] High resolution proximity statistics as early warning for US universities reopening during COVID-19. medRxiv. Mehrab Z, Ranga A, Sarkar D, Venkatramanan S, Baek Y, Swarup S, Marathe M (2020)
[7] Broadcasting on two-dimensional regular grids. arXiv:2010.01390. Oct 3. Makur A, Mossel E, Polyanskiy Y (2020)
[6] Distance Encoding--Design Provably More Powerful GNNs for Structural Representation Learning. arXiv:2009.00142. Aug 31. Li P, Wang Y, Wang H, Leskovec J (2020)
[5] Interplay of global multi-scale human mobility, social distancing, government interventions, and COVID-19 dynamics. medRxiv. Aug 24. Adiga A, Wang L, Sadilek A, Tendulkar A, Venkatramanan S, Vullikanti A, Aggarwal G, Talekar A, Ben X, Chen J, Lewis B, Swarup S, Tambe M, Marathe M (2020)
[4] Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the US. medRxiv. Aug 22. Ray E, et al (2020)
[3] Approximation Algorithms for Radius-Based, Two-Stage Stochastic Clustering Problems with Budget Constraints. arXiv:2008.03325. Aug 7. Brubach B, Grammel N, Harris D, Srinivasan A, Tsepenekas L, Vullikanti A (2020)
[2] Staggered Release Policies for COVID-19 Control: Costs and Benefits of Sequentially Relaxing Restrictions by Age. arXiv. May 12. Zhao H, Feng Z, Castillo-Chavez C, Levin S (2020)
[1] Explaining the "bomb-like" dynamics of COVID-19 with modeling and implications for policy. medRxiv. Lin G, Strauss A, Pinz M, Martinez D, Tseng K, Schueller E, Gatalo O, Yang Y, Levin S, Klein E (2020)
The Interplay between Genomic Surveillance and Public Health Interventions. 2024 SIAM Annual Meeting. Espinoza B (Jul 2024)
Program Design: Mobile Clinic Placement, Testing Strategies, and Demand Planning. 2024 CSTE Annual Conference-Applications of Forecasting Workshop. Lewis B (Jun 2024)
Synthetic Social Habitats for Policy and Decision Making. Summer at Census Seminars 2024. Swarup S and Marathe M (May 2024)
The Interplay between Genomic Surveillance and Public Health Interventions. 2024 AMS Spring Eastern Sectional Meeting. Espinoza B (Apr 2024)
Integrating Topics from Computational Epidemiology Undergraduate Courses. ACM SIGCSE 2024. Espinoza B (Mar 2024)
Learning from Dynamics. 2024 EnCORE Workshop on Computational vs Statistical Gaps in Learning and Optimization. Moitra A (Feb 2024)
Optimizing epidemic surveillance with limited screening resources. CeZAP SPARK Spring 2024. Vullikanti A (Feb 2024)
National Landscape Analysis of Pathogen Genomics. OAMD Leads Meeting. Warren A (Feb 2024)
Predicting Pandemics: What Cholera Has Taught Us About COVID-19. European Space Agency E04Health User Forum 2024. Colwell R (Jan 2024)
Modeling Social Complexity in Epidemiology: Risk Perception and Adaptive Human Behavior. BEER 2023. Espinoza B (Nov 2023)
Synthetic Information and Digital Twins for Pandemic Science: Challenges and Opportunities. Fifth IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications. Marathe M (Nov 2023)
Relational Deep Learning. Learning on Graphs Conference 2023. Leskovec J (Nov 2023)
Understanding of Drug Resistance as a Problem of Managing a Shared Global Resource. 4th Antimicrobial Resistance (AMR) Course - A One Health Challenge. Laxminarayan R (Nov 2023)
Privacy for Network Science and Public Health. ORNL Core Universities AI Workshop 2023. Vullikanti A (Oct 2023)
Responding to the COVID-19 Pandemic: The Central Role of Computing and AI. 2023 INFORMS Annual Meeting. Madhav M (Oct 2023)
Synthetic Information of Socio-Technical Networks. Cross-cutting Research Needs for Digital Twins. Marathe M (Oct 2023)
Interactive Simulacra of Human Behavior. Michigan AI Symposium 2023. Bernstein M (Oct 2023)
Ecosystems and the Biosphere as Complex Adaptive Systems: Scaling, Collective Phenomena and Governance. 2023-34 McGill Seminar Series in Quantitative Life Sciences and Medicine. Levin S (Oct 2023)
State of the World's Antibiotics in 2023. 2023 McGill AMR Centre Annual Symposium. Laxminarayan R (Oct 2023)
The Potential of Synthetic Surveillance: Embracing Multiple Realities. AMD Days 2023. Warren A (Sep 2023)
Learning from Dynamics. 2023 Harvard Big Data Conference. Moitra A (Aug 2023)
Maintaining Order in the Sequence Tsunami: Sequence Data Management. ASM Training in NGS for Infectious Disease Applications. Warren A (Jul 2023)
The Metropolis Algorithm for the Planted Clique Problem. Oxford Discrete Maths and Probability Seminar Series. Mossel E (Jun 2023)
Interactive Simulacra of Human Opinions and Behavior. Stanford Cyber Policy Center Spring Seminar Series. Bernstein M (May 2023)
Some Modern Perspectives on the Kesten-Stigum Bound for Reconstruction on Trees. Harvard Center of Mathematical Sciences and Applications's Workshop on GRAMSIA: Graphical Models, Statistical Inference, and Algorithms. Mossel E (May 2023)
Designing Artificial Intelligence to Navigate Societal Disagreement. Nokia Bell Labs Responsible AI Seminar Series. Bernstein M (Feb 2023)
Can We Tackle Vaccine Hesitancy and Global Warming with a Similar Playbook? Researchers Think So. Princeton Pulse. Levin S (Jan 2023)
Epidemiology of COVID-19 in India. IIT Madras Symposium on Epidemic Modelling. Laxminarayan R (Dec 2022)
Designing artificial intelligence to navigate societal disagreement. Schwartz Reisman Institute for Technology and Society Seminar Series. Bernstein M (Oct 2022)
Situational Awareness and Course-of-Action Analysis in Complex Systems: The Role of High-Fidelity, High-Resolution Modeling and Simulation. Jefferson Science Fellowship Distinguished Lecture. Eubank S (Oct 2022)
Deep Learning with Knowledge Graphs. The Knowledge Graph Conference 2022. Leskovec J. (Jul 2022)
Combinatorial Statistics and the Sciences. ICM 2022. Mossel E (Jul 2022)
Probabilistic Methods in Computer Science, Data Science, and Public Health. Boeing Distinguished Colloquium. Srinivasan A (Apr 2022)
Climate and Health: Conquering Water-Borne Diseases in the 21st Century. ONWARD Webinar Series on Water-Related Diseases, Their Links To Environmental Conditions, Water Quality, Monitoring Methods, and Solutions, AIR Centre. Colwell R (Mar 2022)
Just Because You Are A Pawn You Don't Have To Lose The Game. UMD CMNS DEI Lecture. Colwell R (Mar 2022)
Optimal COVID-19 Quarantine and Testing Strategies. Pasteur Institute. Townsend J (Oct 2021)
Rethinking Robustness: From Classification to Contextual Bandits. USC Department of Mathematics Probability and Statistics Seminar. Moitra A (Oct 2021)
HySec-Flow: Privacy-Preserving Genomic Computing with SGX-Based Big-Data Analytics Framework. 2021 IEEE 14th International Conference on Cloud Computing (CLOUD). Fox J (Aug 2021)
Real-time contagion science in the 21st century: The role of data and computing. Science Gallery Bengaluru: Contagion. Marathe M (Jun 2021)
AI/ML for Pandemic Response. PathCheck Global Health Innovators Talk Series. Prakash BA and Rodriguez A (Jun 2021)
The durability of immunity following infection by SARS-CoV-2. COVID-19 Research Webinar, Northeast Big Data Innovation Hub, Columbia University Data Science Initiative. Townsend J (Jun 2021)
Mobility Networks for Modeling the Spread of COVID-19. Penn State Center for Socially Responsible AI: AI for Social Impact Seminar Series. Leskovec J (Jun 2021)
Data Assimilation for Pandemic Modeling. Alan Turing Institute Workshop on Towards Real-Time Numerical Simulations of Human-Evironment Systems: Data Assimilation & Agent-Based Modelling. Swarup S (May 2021)
Vaccine prioritization: The role of AI and computing in pandemic planning and response. Chalmers AI Research Centre Talks. Marathe M (Mar 2021)
Fairness in AI and in Algorithms. University of Maryland Fairness in AI Seminar Series. Srinivasan A (Mar 2021)
COVID-19 in the US. COVID-19: Policymaking in the Throes of a Global Crisis Seminar Series, Columbia SIPA. Galvani A (Nov 2020)
Mobility and Behavior Modeling for COVID-19. 3rd ACM SIGSPATIAL Workshop on Geospatial Simulation. Swarup S (Nov 2020)
Real-time pandemic planning and response: Experiences from the COVID-19 pandemic. Harvard CRCS's AI for Social Impact Seminar Series. Marathe M (Oct 2020)
Predicting and Analyzing Pandemics. Technology, Culture, and Society in the Age of COVID-19 Continuing Studies Course, Rice University. Marathe M (Oct 2020)
A Lab of One's Own: One Woman's Personal Journey Through Sexism in Science. Harvard Science Book Talk. Colwell R (Sep 2020)
Real-Time Computational Science for COVID-19 Pandemic Planning and Response. ACM BCB 2020. Marathe M (Sep 2020)
Projecting hospital utilization and assessing implications of silent transmission during the COVID-19 outbreak in the United States. COVID-19 Consortium Colloquium Speaker Series, UT Austin. Galvani A and Pandey A (Sep 2020)
Graph Structure of Neural Networks: Good Neural Networks Are Alike. MLG20. Leskovec J (Aug 2020)
Towards real-time computational epidemiology. Workshop on Knowledge Guided Machine Learning (KGML). Marathe M (Aug 2020)
Graph Neural Networks for Reasoning over Multimodal Content. ML4MD at ICML2020. Leskovec J (Jul 2020)
Representation Learning for Logical Reasoning in Knowledge Graphs. Automated Knowledge Base Construction. Leskovec J (Jun 2020)
Robustness meets Algorithms. Trustworthy and Robust AI Collaboration (TRAC) Workshop. Moitra A (Jun 2020)
Using Machine Learning to Respond to Covid-19. Machine Learning Center at Georgia Tech. Kumar S, Prakash BA, De Choudhury M, Serban N, and Miller K (Jun 2020)
Uncertainty & Precision in Math Modeling to Mitigate the Threat of COVID-19. Mathematical Models on Epidemiology in Connection with COVID-19, Dept of Mathematics, Vellore Institute of Technology, TN, India. Mubayi A (Jun 2020)
Underreporting, Preparedness, and Silent Typhoid Marys: A Cautionary Tale of Modeling COVID Dynamics. COVID-19 Modeling Webinar Series, Indian Institute of Public Health, Gandhinagar, India. Mubayi A (Jun 2020)
Lessons from Evolution for Anticipating and Coping with Extreme Events. "Don’t Waste the Covid-19 Crisis: Reflections on Resilience and the Commons Revealed by Covid-19" Webinar Series, Center for Behavior, Institutions and the Environment (CBIE), the International Association for Study of the Commons (IASC), and the Resilience Alliance. Levin S (May 2020)
Responding to the COVID-19 Pandemic: Role of Computing and Data Science. IIT Madras Leadership Lecture Series. Marathe M (May 2020)
Tackling the COVID-19 Crisis. UVA Research virtual panel. Marathe M (May 2020)
Computational and Statistical Tools to Control a Pandemic. Theoretically Speaking Series, Simons Institute for the Theory of Computing. Team members on the virtual panel: Moitra A, Marathe M, Vullikanti A (May 2020)
Computational Science for Real-time COVID-19 Response. ACM India Industry Webinar. Marathe M (Apr 2020)
Recommendations for Improving Science During Crisis. AAAS Annual Meeting. Colwell R (Feb 2020)
Chen J, Lewis B, and Venkatramanan S. 2022 UVA Provost's Office Award for Collaborative Excellence in Public Service. For their service to the University, the Commonwealth of Virginia, and federal authorities during the pandemic, which continues today. (2022)
Levin SA. 2022 AMS Fellow. For contributions to the mathematics of ecology, evolution, and epidemiology. (2022)
Li G, Li A, Marathe M, Srinivasan A, Tsepenekas L and Vullikanti AK. AAMAS 2022. Best Student Paper. Deploying Vaccine Distribution Sites for Improved Accessibility and Equity to Support Pandemic Response. May (2022)
Bhattacharya P, Chen J, Hoops S, Machi D, Lewis B, Venkatramanan S, Wilson ML, Klahn B, Adiga A, Hurt B, Outten J, Adiga A, Warren A, Baek H, Porebski P, Marathe A, Xie D, Swarup S, Vullikanti A, Mortveit H, Eubank S, Barrett CL and Marathe M. 2021 ACM Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research Finalist. Data-Driven Scalable Pipeline Using National Agent-Based Models for Real-Time Pandemic Response and Decision Support. Nov (2021)
Marathe M, Athreya S, Barrett C, Eubank S, Levin S, Ollivere B, Poor HV, Reidys C, Sunaresan R, Valdez A, Waterman M. 2021 Trinity Challenge Finalist. For better protecting the world against health emergencies using data-driven research and analytics. Jun (2021)
Levin SA. 14th Edition BBVA Frontiers of Knowledge Award in Ecology and Conservation Biology. For leading the development of the theoretical and mathematical basis for spatial ecology, making it possible to understand the mechanisms that maintain biodiversity by taking into account the complex interactions between individuals and the environment. And applying this theory to the design of nature preserves and more sustainable cities. (2021)
Mossel E. 2021 ACM Fellow. For contributions to theoretical computer science and inference. (2021)
Bernstein M. 2021 Patrick J. McGovern Tech for Humanity Changemaker. For contributions to reducing bias in technology by developing a jury-based approach to artificial intelligence and machine learning that considers diverse perspectives. (2021)
Vullikanti A. 2020 ACM Distinguished Members for Contributions that Propel the Digital Age. For Outstanding Scientific Contributions to Computing. (2020)
Team members have played a key role in supporting local, state, and national public health policymakers. While the operational effort is funded by multiple agencies (including the CDC, DTRA, and VDH), the Expeditions project has focused largely on technology development. While we had planned for such participation as part of our project, COVID-19 provided us with an unprecedented opportunity. Multiple tools and web apps have been developed for COVID-19 surveillance. The UVA team continued to serve as the lead analytical group supporting the Virginia Department of Health (VDH), the Virginia Department of Emergency Management, various local and state hospitals, including the University of Virginia School of Medicine and Virginia Commonwealth University, as well as the DoD and CDC. This work has resulted in over 92 slide decks and weekly briefs, numerous updates to stakeholders, over 1.3 million views to the main projection dashboard, and citations in over 360 local media reports. These analyses assist local health officials, school administrators, businesses, and individuals in risk assessment and various kinds of policy decisions. In particular,
- VDH: During the outbreak response phase, we generated knowledge in the form of forecasts of case counts that were communicated to VDH and other operational agencies through weekly briefings.
- CDC: The COVID Forecast Hub has had a central role in CDC’s messaging about the pandemic. The Expeditions team also developed the Scenario Modeling Hub, which was influential in CDC’s authorization of the initial vaccination use for children, as well as the early rollout of boosters (after Labor Day instead of mid-October). Team members also developed dashboards and decision-support tools as a collaboration between UVA and Stanford. Policy-shaping examples also include the decision to not establish field hospitals, the use of the work done by Jure Leskovec et al. on evaluating social interventions, and coverage of the work by Alison Galvani and her team on boosters 1, 2, 3.
- International policy: The team’s work was influential in increasing the rate of COVID-19 testing at the Tokyo Olympics by 10-fold over planned levels (up to 31,000 per day) as a direct result of the work by Ramanan Laxminarayan et al.. Policy-shaping examples also include international support of COVID-19 responses in Botswana and India, Rita Colwell’s work on Cholera risk in different countries, and the assessment of the health impacts of Russia’s invasion of Ukraine.
- Key Insights: (a) durability of vaccine-mediated immunity by Townsend et al., (b) identification of the social interactions important for transmission by Leskovec et al., and (c) impact of COVID-19 vaccine boosters by Galvani et al. 1, 2, 3
