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ORCIDB. Aditya Prakash
Person information
- affiliation: Georgia Institute of Technology, USA
- affiliation (PhD 2012): Carnegie Mellon University, Pittsburgh, USA
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Books and Theses
- 2015
[b1]V. S. Subrahmanian, Michael Ovelgönne, Tudor Dumitras, B. Aditya Prakash:
The Global Cyber-Vulnerability Report. Terrorism, Security, and Computation, Springer 2015, ISBN 978-3-319-25758-7, pp. 1-291
Journal Articles
- 2025
- [j28]Jiaming Cui, Jack Heavey, Eili Y. Klein, Gregory Madden, Costi D. Sifri, Anil Vullikanti
, B. Aditya Prakash:
Identifying and forecasting importation and asymptomatic spreaders of multi-drug resistant organisms in hospital settings. npj Digit. Medicine 8(1) (2025) - 2024
- [j27]Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash:
Machine learning for data-centric epidemic forecasting. Nat. Mac. Intell. 6(10): 1122-1131 (2024) - 2023
- [j26]Vedant Das Swain, Jiajia Xie, Maanit Madan, Sonia Sargolzaei, James Cai, Munmun De Choudhury, Gregory D. Abowd, Lauren N. Steimle, B. Aditya Prakash:
Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses. Frontiers Digit. Health 5 (2023) - 2020
- [j25]Nikhil Muralidhar, Anika Tabassum, Liangzhe Chen, Supriya Chinthavali, Naren Ramakrishnan, B. Aditya Prakash:
Cut-n-Reveal: Time Series Segmentations with Explanations. ACM Trans. Intell. Syst. Technol. 11(5): 53:1-53:26 (2020) - 2019
- [j24]Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, B. Aditya Prakash:
Data-driven efficient network and surveillance-based immunization. Knowl. Inf. Syst. 61(3): 1667-1693 (2019) - [j23]Bijaya Adhikari, Bryan L. Lewis, Anil Vullikanti, José M. Jiménez, B. Aditya Prakash:
Fast and near-optimal monitoring for healthcare acquired infection outbreaks. PLoS Comput. Biol. 15(9) (2019) - [j22]Sorour E. Amiri, Anika Tabassum, E. Thomas Ewing, B. Aditya Prakash:
Tracking and analyzing dynamics of news-cycles during global pandemics: a historical perspective. SIGKDD Explor. 21(2): 91-100 (2019) - 2018
- [j21]Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash:
Efficiently summarizing attributed diffusion networks. Data Min. Knowl. Discov. 32(5): 1251-1274 (2018) - [j20]Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash:
Automatic Segmentation of Dynamic Network Sequences with Node Labels. IEEE Trans. Knowl. Data Eng. 30(3): 407-420 (2018) - [j19]Bijaya Adhikari, Yao Zhang, Sorour E. Amiri, Aditya Bharadwaj, B. Aditya Prakash:
Propagation-Based Temporal Network Summarization. IEEE Trans. Knowl. Data Eng. 30(4): 729-742 (2018) - 2017
- [j18]Michael Ovelgönne, Tudor Dumitras, B. Aditya Prakash, V. S. Subrahmanian, Benjamin Wang:
Understanding the Relationship between Human Behavior and Susceptibility to Cyber Attacks: A Data-Driven Approach. ACM Trans. Intell. Syst. Technol. 8(4): 51:1-51:25 (2017) - [j17]Yasuko Matsubara, Yasushi Sakurai, B. Aditya Prakash, Lei Li, Christos Faloutsos:
Nonlinear Dynamics of Information Diffusion in Social Networks. ACM Trans. Web 11(2): 11:1-11:40 (2017) - 2016
- [j16]Liangzhe Chen, K. S. M. Tozammel Hossain, Patrick Butler, Naren Ramakrishnan, B. Aditya Prakash:
Syndromic surveillance of Flu on Twitter using weakly supervised temporal topic models. Data Min. Knowl. Discov. 30(3): 681-710 (2016) - [j15]B. Aditya Prakash:
Prediction Using Propagation: From Flu Trends to Cybersecurity. IEEE Intell. Syst. 31(1): 84-88 (2016) - [j14]Lawrence B. Holder, Rajmonda Sulo Caceres, David F. Gleich, E. Jason Riedy, Maleq Khan, Nitesh V. Chawla, Ravi Kumar, Yinghui Wu, Christine Klymko, Tina Eliassi-Rad, B. Aditya Prakash:
Current and Future Challenges in Mining Large Networks: Report on the Second SDM Workshop on Mining Networks and Graphs. SIGKDD Explor. 18(1): 39-45 (2016) - [j13]Chen Chen, Hanghang Tong, B. Aditya Prakash, Tina Eliassi-Rad, Michalis Faloutsos, Christos Faloutsos:
Eigen-Optimization on Large Graphs by Edge Manipulation. ACM Trans. Knowl. Discov. Data 10(4): 49:1-49:30 (2016) - [j12]Chen Chen, Hanghang Tong, B. Aditya Prakash, Charalampos E. Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos, Duen Horng Chau:
Node Immunization on Large Graphs: Theory and Algorithms. IEEE Trans. Knowl. Data Eng. 28(1): 113-126 (2016) - [j11]Yao Zhang, Abhijin Adiga, Sudip Saha, Anil Vullikanti, B. Aditya Prakash:
Near-Optimal Algorithms for Controlling Propagation at Group Scale on Networks. IEEE Trans. Knowl. Data Eng. 28(12): 3339-3352 (2016) - 2015
- [j10]Yao Zhang, B. Aditya Prakash:
Data-Aware Vaccine Allocation Over Large Networks. ACM Trans. Knowl. Discov. Data 10(2): 20:1-20:32 (2015) - 2014
- [j9]B. Aditya Prakash, Jilles Vreeken, Christos Faloutsos:
Efficiently spotting the starting points of an epidemic in a large graph. Knowl. Inf. Syst. 38(1): 35-59 (2014) - [j8]Evangelos E. Papalexakis, Tudor Dumitras, Duen Horng Chau, B. Aditya Prakash, Christos Faloutsos:
SharkFin: Spatio-temporal mining of software adoption and penetration. Soc. Netw. Anal. Min. 4(1): 240 (2014) - 2013
- [j7]Xuetao Wei, Nicholas Valler, B. Aditya Prakash, Iulian Neamtiu, Michalis Faloutsos, Christos Faloutsos:
Competing Memes Propagation on Networks: A Network Science Perspective. IEEE J. Sel. Areas Commun. 31(6): 1049-1060 (2013) - 2012
- [j6]Xuetao Wei, Nicholas Valler, B. Aditya Prakash, Iulian Neamtiu, Michalis Faloutsos, Christos Faloutsos:
Competing memes propagation on networks: a case study of composite networks. Comput. Commun. Rev. 42(5): 5-12 (2012) - [j5]B. Aditya Prakash:
Propagation and immunization in large networks. XRDS 19(1): 56-59 (2012) - [j4]B. Aditya Prakash, Deepayan Chakrabarti, Nicholas Valler, Michalis Faloutsos, Christos Faloutsos:
Threshold conditions for arbitrary cascade models on arbitrary networks. Knowl. Inf. Syst. 33(3): 549-575 (2012) - [j3]B. Aditya Prakash, Christos Faloutsos:
Understanding and Managing Cascades on Large Graphs. Proc. VLDB Endow. 5(12): 2024-2025 (2012) - 2010
- [j2]Lei Li, B. Aditya Prakash, Christos Faloutsos:
Parsimonious Linear Fingerprinting for Time Series. Proc. VLDB Endow. 3(1): 385-396 (2010) - 2009
- [j1]Shipra Agrawal, Jayant R. Haritsa, B. Aditya Prakash:
FRAPP: a framework for high-accuracy privacy-preserving mining. Data Min. Knowl. Discov. 18(1): 101-139 (2009)
Conference and Workshop Papers
- 2025
- [c85]Haoxin Liu, Chenghao Liu, B. Aditya Prakash:
A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization. NAACL (Long Papers) 2025: 7486-7518 - [c84]Jiaming Cui, Bijaya Adhikari, Arash Haddadan, A. S. M. Ahsan-Ul-Haque, Jilles Vreeken, Anil Vullikanti, B. Aditya Prakash:
Accurately Estimating Unreported Infections using Information Theory. SDM 2025: 457-466 - [c83]Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang:
DF2: Distribution-Free Decision-Focused Learning. UAI 2025: 2269-2290 - 2024
- [c82]Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash:
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. ACL (Findings) 2024: 7832-7840 - [c81]Leo Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash:
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks. ICLR 2024 - [c80]Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash:
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. ICML 2024 - [c79]Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin:
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. IJCAI 2024: 8058-8066 - [c78]Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash:
Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity. KDD 2024: 5230-5239 - [c77]Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin:
A Review of Graph Neural Networks in Epidemic Modeling. KDD 2024: 6577-6587 - [c76]Alexander Rodríguez, Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Marie-Laure Charpignon, Kai Wang, Serina Chang, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 2024: The 7th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2024: 6735-6736 - [c75]Harshavardhan Kamarthi, B. Aditya Prakash:
Large Pre-trained time series models for cross-domain Time series analysis tasks. NeurIPS 2024 - [c74]Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash:
Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis. NeurIPS 2024 - [c73]Vivek Anand, Jiaming Cui, Jack Heavey, Anil Vullikanti, B. Aditya Prakash:
H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions. SDM 2024: 280-288 - 2023
- [c72]Hankyu Jang, Andrew Fu, Jiaming Cui, Methun Kamruzzaman, B. Aditya Prakash, Anil Vullikanti, Bijaya Adhikari, Sriram V. Pemmaraju:
Detecting Sources of Healthcare Associated Infections. AAAI 2023: 4347-4355 - [c71]Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash:
EINNs: Epidemiologically-Informed Neural Networks. AAAI 2023: 14453-14460 - [c70]Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar:
Differentiable Agent-based Epidemiology. AAMAS 2023: 1848-1857 - [c69]Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang:
Autoregressive Diffusion Model for Graph Generation. ICML 2023: 17391-17408 - [c68]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. KDD 2023: 1057-1072 - [c67]Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang:
Uncertainty Quantification in Deep Learning. KDD 2023: 5809-5810 - [c66]Bijaya Adhikari, Alexander Rodríguez, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2023: 5847-5848 - 2022
- [c65]Jack Heavey, Jiaming Cui, Chen Chen, B. Aditya Prakash, Anil Vullikanti:
Provable Sensor Sets for Epidemic Detection over Networks with Minimum Delay. AAAI 2022: 10202-10209 - [c64]Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash:
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. ICLR 2022 - [c63]Alexander Rodríguez, Harshavardhan Kamarthi, B. Aditya Prakash:
Epidemic Forecasting with a Data-Centric Lens. KDD 2022: 4822-4823 - [c62]Bijaya Adhikari, Amulya Yadav, Sen Pei, Ajitesh Srivastava, Sarah Kefayati, Alexander Rodríguez, Marie-Laure Charpignon, Anil Vullikanti, B. Aditya Prakash:
epiDAMIK 5.0: The 5th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery. KDD 2022: 4850-4851 - [c61]Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang:
End-to-end Stochastic Optimization with Energy-based Model. NeurIPS 2022 - [c60]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. WWW 2022: 3174-3185 - 2021
- [c59]Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash:
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. AAAI 2021: 4855-4863 - [c58]Alexander Rodríguez, Anika Tabassum, Jiaming Cui, Jiajia Xie, Javen Ho, Pulak Agarwal, Bijaya Adhikari, B. Aditya Prakash:
DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting. AAAI 2021: 15393-15400 - [c57]Anika Tabassum, Supriya Chinthavali, Sangkeun Lee, Nils M. Stenvig, Bill Kay, P. Teja Kuruganti, B. Aditya Prakash:
Efficient Contingency Analysis in Power Systems via Network Trigger Nodes. IEEE BigData 2021: 1964-1973 - [c56]Anika Tabassum, Supriya Chinthavali, Varisara Tansakul, B. Aditya Prakash:
Actionable Insights in Urban Multivariate Time-series. CIKM 2021: 1774-1783 - [c55]Bijaya Adhikari, Ajitesh Srivastava, Sen Pei, Sarah Kefayati, Rose Yu, Amulya Yadav, Alexander Rodríguez, Arvind Ramanathan, Anil Vullikanti, B. Aditya Prakash:
The 4th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery (epiDAMIK 4.0 @ KDD2021). KDD 2021: 4104-4105 - [c54]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. NeurIPS 2021: 19796-19807 - 2020
- [c53]Prathyush Sambaturu, Bijaya Adhikari, B. Aditya Prakash, Srinivasan Venkatramanan, Anil Vullikanti:
Designing Effective and Practical Interventions to Contain Epidemics. AAMAS 2020: 1187-1195 - [c52]Alexander Rodríguez, Bijaya Adhikari, Andrés D. González, Charles D. Nicholson, Anil Vullikanti, B. Aditya Prakash:
Mapping Network States using Connectivity Queries. IEEE BigData 2020: 778-787 - 2019
- [c51]Bijaya Adhikari, Xinfeng Xu, Naren Ramakrishnan, B. Aditya Prakash:
EpiDeep: Exploiting Embeddings for Epidemic Forecasting. KDD 2019: 577-586 - [c50]Liangzhe Chen, B. Aditya Prakash:
Joint Post and Link-level Influence Modeling on Social Media. SDM 2019: 262-270 - 2018
- [c49]Liangzhe Chen, Sorour E. Amiri, B. Aditya Prakash:
Automatic Segmentation of Data Sequences. AAAI 2018: 2844-2851 - [c48]Sorour E. Amiri, Bijaya Adhikari, Aditya Bharadwaj, B. Aditya Prakash:
NetGist: Learning to Generate Task-Based Network Summaries. ICDM 2018: 857-862 - [c47]Mohammad Raihanul Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, Naren Ramakrishnan:
DeepDiffuse: Predicting the 'Who' and 'When' in Cascades. ICDM 2018: 1055-1060 - [c46]Mohammad Raihanul Islam, B. Aditya Prakash, Naren Ramakrishnan:
SIGNet: Scalable Embeddings for Signed Networks. PAKDD (2) 2018: 157-169 - [c45]Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash:
Sub2Vec: Feature Learning for Subgraphs. PAKDD (2) 2018: 170-182 - [c44]Bijaya Adhikari, Pavan Rangudu, B. Aditya Prakash, Anil Vullikanti:
Near-Optimal Mapping of Network States using Probes. SDM 2018: 108-116 - [c43]Bijaya Adhikari, Parikshit Sondhi, Wenke Zhang, Mohit Sharma, B. Aditya Prakash:
Mining E-Commerce Query Relations using Customer Interaction Networks. WWW 2018: 1805-1814 - 2017
- [c42]Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash:
SnapNETS: Automatic Segmentation of Network Sequences with Node Labels. AAAI 2017: 3-9 - [c41]Liangzhe Chen, Xinfeng Xu, Sangkeun Lee, Sisi Duan, Alfonso G. Tarditi, Supriya Chinthavali, B. Aditya Prakash:
HotSpots: Failure Cascades on Heterogeneous Critical Infrastructure Networks. CIKM 2017: 1599-1607 - [c40]Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash:
Distributed Representations of Subgraphs. ICDM Workshops 2017: 111-117 - [c39]Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura L. Pullum, B. Aditya Prakash:
Data-Driven Immunization. ICDM 2017: 615-624 - [c38]Yao Zhang, Bijaya Adhikari, Steve T. K. Jan, B. Aditya Prakash:
MeiKe: Influence-based Communities in Networks. SDM 2017: 318-326 - [c37]Bijaya Adhikari, Yao Zhang, Aditya Bharadwaj, B. Aditya Prakash:
Condensing Temporal Networks using Propagation. SDM 2017: 417-425 - [c36]Karthik Subbian, B. Aditya Prakash, Lada A. Adamic:
Detecting Large Reshare Cascades in Social Networks. WWW 2017: 597-605 - 2016
- [c35]Sangkeun Lee, Liangzhe Chen, Sisi Duan, Supriya Chinthavali, Mallikarjun Shankar, B. Aditya Prakash:
URBAN-NET: A network-based infrastructure monitoring and analysis system for emergency management and public safety. IEEE BigData 2016: 2600-2609 - [c34]Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash:
Segmenting Sequences of Node-Labeled Graphs. ICDM Workshops 2016: 61-68 - [c33]Polina Rozenshtein, Aristides Gionis, B. Aditya Prakash, Jilles Vreeken:
Reconstructing an Epidemic Over Time. KDD 2016: 1835-1844 - [c32]B. Aditya Prakash, Naren Ramakrishnan:
Leveraging Propagation for Data Mining: Models, Algorithms and Applications. KDD 2016: 2133-2134 - [c31]Ahsanur Rahman, Steve T. K. Jan, Hyunju Kim, B. Aditya Prakash, T. M. Murali:
Unstable Communities in Network Ensembles. SDM 2016: 504-512 - [c30]Chanhyun Kang, Noseong Park, B. Aditya Prakash, Edoardo Serra, V. S. Subrahmanian:
Ensemble Models for Data-driven Prediction of Malware Infections. WSDM 2016: 583-592 - 2015
- [c29]Ahsanur Rahman, Steve T. K. Jan, Hyunju Kim, B. Aditya Prakash, T. M. Murali:
Mining Unstable Communities from Network Ensembles. ICDM Workshops 2015: 508-515 - [c28]Yao Zhang, Abhijin Adiga, Anil Vullikanti, B. Aditya Prakash:
Controlling Propagation at Group Scale on Networks. ICDM 2015: 619-628 - [c27]Shashidhar Sundareisan, Jilles Vreeken, B. Aditya Prakash:
Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics. SDM 2015: 415-423 - [c26]Sudip Saha, Abhijin Adiga, B. Aditya Prakash, Anil Kumar S. Vullikanti:
Approximation Algorithms for Reducing the Spectral Radius to Control Epidemic Spread. SDM 2015: 568-576 - 2014
- [c25]Shashidhar Sundereisan, Abhay Bhadriraju, M. Saquib Khan, Naren Ramakrishnan, B. Aditya Prakash:
SansText: Classifying temporal topic dynamics of Twitter cascades without tweet text. ASONAM 2014: 649-656 - [c24]Yao Zhang, B. Aditya Prakash:
Scalable Vaccine Distribution in Large Graphs given Uncertain Data. CIKM 2014: 1719-1728 - [c23]Liangzhe Chen, K. S. M. Tozammel Hossain, Patrick Butler, Naren Ramakrishnan, B. Aditya Prakash:
Flu Gone Viral: Syndromic Surveillance of Flu on Twitter Using Temporal Topic Models. ICDM 2014: 755-760 - [c22]Manish Purohit, B. Aditya Prakash, Chanhyun Kang, Yao Zhang, V. S. Subrahmanian:
Fast influence-based coarsening for large networks. KDD 2014: 1296-1305 - [c21]Fang Jin, Rupinder Paul Khandpur, Nathan Self, Edward R. Dougherty, Sheng Guo, Feng Chen, B. Aditya Prakash, Naren Ramakrishnan:
Modeling mass protest adoption in social network communities using geometric brownian motion. KDD 2014: 1660-1669 - [c20]Yao Zhang, B. Aditya Prakash:
DAVA: Distributing Vaccines over Networks under Prior Information. SDM 2014: 46-54 - 2013
- [c19]Evangelos E. Papalexakis, Tudor Dumitras, Duen Horng (Polo) Chau, B. Aditya Prakash, Christos Faloutsos:
Spatio-temporal mining of software adoption & penetration. ASONAM 2013: 878-885 - [c18]Xuetao Wei, Nicholas Valler, Michalis Faloutsos, Iulian Neamtiu, B. Aditya Prakash, Christos Faloutsos:
Smartphone viruses propagation on heterogeneous composite networks. NSW 2013: 106-109 - [c17]Danai Koutra, Vasileios Koutras, B. Aditya Prakash, Christos Faloutsos:
Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG Model. PAKDD (1) 2013: 201-212 - [c16]Lada A. Adamic, Christos Faloutsos, Theodore J. Iwashyna, B. Aditya Prakash, Hanghang Tong:
Fractional Immunization in Networks. SDM 2013: 659-667 - 2012
- [c15]Hanghang Tong, B. Aditya Prakash, Tina Eliassi-Rad, Michalis Faloutsos, Christos Faloutsos:
Gelling, and melting, large graphs by edge manipulation. CIKM 2012: 245-254 - [c14]B. Aditya Prakash, Jilles Vreeken, Christos Faloutsos:
Spotting Culprits in Epidemics: How Many and Which Ones? ICDM 2012: 11-20 - [c13]Yasuko Matsubara, Yasushi Sakurai, B. Aditya Prakash, Lei Li, Christos Faloutsos:
Rise and fall patterns of information diffusion: model and implications. KDD 2012: 6-14 - [c12]Alex Beutel, B. Aditya Prakash, Roni Rosenfeld, Christos Faloutsos:
Interacting viruses in networks: can both survive? KDD 2012: 426-434 - [c11]B. Aditya Prakash, Alex Beutel, Roni Rosenfeld, Christos Faloutsos:
Winner takes all: competing viruses or ideas on fair-play networks. WWW 2012: 1037-1046 - 2011
- [c10]B. Aditya Prakash, Deepayan Chakrabarti, Michalis Faloutsos, Nicholas Valler, Christos Faloutsos:
Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks. ICDM 2011: 537-546 - [c9]Lei Li, B. Aditya Prakash:
Time Series Clustering: Complex is Simpler! ICML 2011: 185-192 - [c8]Nicholas Valler, B. Aditya Prakash, Hanghang Tong, Michalis Faloutsos, Christos Faloutsos:
Epidemic Spread in Mobile Ad Hoc Networks: Determining the Tipping Point. Networking (1) 2011: 266-280 - 2010
- [c7]Hanghang Tong, B. Aditya Prakash, Charalampos E. Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos, Duen Horng Chau:
On the Vulnerability of Large Graphs. ICDM 2010: 1091-1096 - [c6]Keith Henderson, Tina Eliassi-Rad, Christos Faloutsos, Leman Akoglu, Lei Li, Koji Maruhashi, B. Aditya Prakash, Hanghang Tong:
Metric forensics: a multi-level approach for mining volatile graphs. KDD 2010: 163-172 - [c5]B. Aditya Prakash, Ashwin Sridharan, Mukund Seshadri, Sridhar Machiraju, Christos Faloutsos:
EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs. PAKDD (2) 2010: 435-448 - [c4]B. Aditya Prakash, Hanghang Tong, Nicholas Valler, Michalis Faloutsos, Christos Faloutsos:
Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms. ECML/PKDD (3) 2010: 99-114 - 2009
- [c3]B. Aditya Prakash, Mukund Seshadri, Ashwin Sridharan, Sridhar Machiraju, Christos Faloutsos:
EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs. ICDM Workshops 2009: 290-295 - [c2]B. Aditya Prakash, Nicholas Valler, David G. Andersen, Michalis Faloutsos, Christos Faloutsos:
BGP-lens: patterns and anomalies in internet routing updates. KDD 2009: 1315-1324 - 2007
- [c1]Chaitanya Gokhale, Nitin Gupta, Pranav Kumar, Laks V. S. Lakshmanan, Raymond T. Ng, B. Aditya Prakash:
Complex Group-By Queries for XML. ICDE 2007: 646-655
Parts in Books or Collections
- 2015
- [p1]B. Aditya Prakash:
Graph Mining for Cyber Security. Cyber Warfare 2015: 287-306
Editorship
- 2023
- [e2]B. Aditya Prakash, Dong Wang, Tim Weninger:
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2023, Kusadasi, Turkey, November 6-9, 2023. ACM 2023 [contents] - 2020
- [e1]Rajesh Gupta, Yan Liu, Jiliang Tang, B. Aditya Prakash:
KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020. ACM 2020, ISBN 978-1-4503-7998-4 [contents]
Informal and Other Publications
- 2025
- [i38]Jiaming Cui, Bijaya Adhikari, Arash Haddadan, A. S. M. Ahsan-Ul-Haque, Jilles Vreeken, Anil Vullikanti, B. Aditya Prakash:
Accurately Estimating Unreported Infections using Information Theory. CoRR abs/2502.00039 (2025) - [i37]Haoxin Liu, Zhiyuan Zhao, Shiduo Li, B. Aditya Prakash:
Evaluating System 1 vs. 2 Reasoning Approaches for Zero-Shot Time Series Forecasting: A Benchmark and Insights. CoRR abs/2503.01895 (2025) - [i36]Haoxin Liu, Harshavardhan Kamarthi, Zhiyuan Zhao, Shangqing Xu, Shiyu Wang, Qingsong Wen, Tom Hartvigsen, Fei Wang, B. Aditya Prakash:
How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlook. CoRR abs/2503.11835 (2025) - [i35]Zhiyuan Zhao, Juntong Ni, Shangqing Xu, Haoxin Liu, Wei Jin, B. Aditya Prakash:
TimeRecipe: A Time-Series Forecasting Recipe via Benchmarking Module Level Effectiveness. CoRR abs/2506.06482 (2025) - [i34]Zihan Guan, Zhiyuan Zhao, Fengwei Tian, Dung Nguyen, Payel Bhattacharjee, Ravi Tandon, B. Aditya Prakash, Anil Vullikanti:
A Framework for Multi-source Privacy Preserving Epidemic Analysis. CoRR abs/2506.22342 (2025) - [i33]Zhiyuan Zhao, Sitan Yang, Kin G. Olivares, Boris N. Oreshkin, Stan Vitebsky, Michael W. Mahoney, B. Aditya Prakash, Dmitry Efimov:
TAT: Temporal-Aligned Transformer for Multi-Horizon Peak Demand Forecasting. CoRR abs/2507.10349 (2025) - [i32]Guancheng Wan, Lucheng Fu, Haoxin Liu, Yiqiao Jin, Hui Yi Leong, Eric Hanchen Jiang, Hejia Geng, Jinhe Bi, Yunpu Ma, Xiangru Tang, B. Aditya Prakash, Yizhou Sun, Wei Wang:
Beyond Magic Words: Sharpness-Aware Prompt Evolving for Robust Large Language Models with TARE. CoRR abs/2509.24130 (2025) - 2024
- [i31]Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin:
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. CoRR abs/2402.03358 (2024) - [i30]Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash:
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. CoRR abs/2402.16132 (2024) - [i29]Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin:
A Review of Graph Neural Networks in Epidemic Modeling. CoRR abs/2403.19852 (2024) - [i28]Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash:
Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis. CoRR abs/2406.08627 (2024) - [i27]Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash:
Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. CoRR abs/2406.09130 (2024) - [i26]Wenjie Du, Jun Wang, Linglong Qian, Yiyuan Yang, Fanxing Liu, Zepu Wang, Zina M. Ibrahim, Haoxin Liu, Zhiyuan Zhao, Yingjie Zhou, Wenjia Wang, Kaize Ding, Yuxuan Liang, B. Aditya Prakash, Qingsong Wen:
TSI-Bench: Benchmarking Time Series Imputation. CoRR abs/2406.12747 (2024) - [i25]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting. CoRR abs/2407.02641 (2024) - [i24]Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash:
Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity. CoRR abs/2407.02657 (2024) - [i23]Guancheng Wan, Zewen Liu, Max S. Y. Lau, B. Aditya Prakash, Wei Jin:
Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph. CoRR abs/2410.00049 (2024) - [i22]Haoxin Liu, Chenghao Liu, B. Aditya Prakash:
A Picture is Worth A Thousand Numbers: Enabling LLMs Reason about Time Series via Visualization. CoRR abs/2411.06018 (2024) - 2023
- [i21]Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang:
Autoregressive Diffusion Model for Graph Generation. CoRR abs/2307.08849 (2023) - [i20]Leo Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash:
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks. CoRR abs/2307.11833 (2023) - [i19]Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang:
DF2: Distribution-Free Decision-Focused Learning. CoRR abs/2308.05889 (2023) - [i18]Zhiyuan Zhao, Alexander Rodríguez, B. Aditya Prakash:
Performative Time-Series Forecasting. CoRR abs/2310.06077 (2023) - [i17]Harshavardhan Kamarthi, B. Aditya Prakash:
PEMS: Pre-trained Epidemic Time-series Models. CoRR abs/2311.07841 (2023) - [i16]Harshavardhan Kamarthi, B. Aditya Prakash:
Large Pre-trained time series models for cross-domain Time series analysis tasks. CoRR abs/2311.11413 (2023) - 2022
- [i15]Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash:
EINNs: Epidemiologically-Informed Neural Networks. CoRR abs/2202.10446 (2022) - [i14]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series. CoRR abs/2206.07940 (2022) - [i13]Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash:
Data-Centric Epidemic Forecasting: A Survey. CoRR abs/2207.09370 (2022) - [i12]Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar:
Differentiable Agent-based Epidemiology. CoRR abs/2207.09714 (2022) - [i11]Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang:
End-to-End Stochastic Optimization with Energy-Based Model. CoRR abs/2211.13837 (2022) - 2021
- [i10]Alexander Rodríguez, Bijaya Adhikari, Naren Ramakrishnan, B. Aditya Prakash:
Incorporating Expert Guidance in Epidemic Forecasting. CoRR abs/2101.10247 (2021) - [i9]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. CoRR abs/2106.03904 (2021) - [i8]Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash:
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. CoRR abs/2106.04420 (2021) - [i7]Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash:
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. CoRR abs/2109.07438 (2021) - 2020
- [i6]Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash:
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. CoRR abs/2009.11407 (2020) - [i5]Alexander Rodríguez, Bijaya Adhikari, Andrés D. González, Charles D. Nicholson, Anil Vullikanti, B. Aditya Prakash:
Mapping Network States Using Connectivity Queries. CoRR abs/2012.03413 (2020) - [i4]Sorour E. Amiri, Bijaya Adhikari, John E. Wenskovitch, Alexander Rodríguez, Michelle Dowling, Chris North, B. Aditya Prakash:
NetReAct: Interactive Learning for Network Summarization. CoRR abs/2012.11821 (2020) - 2017
- [i3]Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash:
Distributed Representation of Subgraphs. CoRR abs/1702.06921 (2017) - 2016
- [i2]Huijuan Shao, K. S. M. Tozammel Hossain, Hao Wu, Maleq Khan, Anil Vullikanti, B. Aditya Prakash, Madhav V. Marathe, Naren Ramakrishnan:
Forecasting the Flu: Designing Social Network Sensors for Epidemics. CoRR abs/1602.06866 (2016) - 2015
- [i1]Sudip Saha, Abhijin Adiga, B. Aditya Prakash, Anil Kumar S. Vullikanti:
Approximation Algorithms for Reducing the Spectral Radius to Control Epidemic Spread. CoRR abs/1501.06614 (2015)
Coauthor Index
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