B. Aditya Prakash

ORCID

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 93

Top Venues

Publications

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 (2024)
Vivek Anand, Jiaming Cui, Jack Heavey, Anil Vullikanti, B. Aditya Prakash
ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions. SDM (2024)
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 (2024)
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 (2024)
Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
A Review of Graph Neural Networks in Epidemic Modeling. CoRR (2024)
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)
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)
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)
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 (2024)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting. CoRR (2024)
Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
A Review of Graph Neural Networks in Epidemic Modeling. KDD (2024)
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 (2024)
Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation. CoRR (2024)
Leo Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks. ICLR (2024)
Leo Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash
PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks. CoRR (2023)
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)
Zhiyuan Zhao, Alexander Rodríguez, B. Aditya Prakash
Performative Time-Series Forecasting. CoRR (2023)
Harshavardhan Kamarthi, B. Aditya Prakash
PEMS: Pre-trained Epidemic Time-series Models. CoRR (2023)
Harshavardhan Kamarthi, B. Aditya Prakash
Large Pre-trained time series models for cross-domain Time series analysis tasks. CoRR (2023)
Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang
DF2: Distribution-Free Decision-Focused Learning. CoRR (2023)
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)
Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash
EINNs: Epidemiologically-Informed Neural Networks. AAAI (2023)
Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang
Autoregressive Diffusion Model for Graph Generation. CoRR (2023)
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)
Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang
Uncertainty Quantification in Deep Learning. KDD (2023)
Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar
Differentiable Agent-based Epidemiology. AAMAS (2023)
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)
Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang
Autoregressive Diffusion Model for Graph Generation. ICML (2023)
Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash
EINNs: Epidemiologically-Informed Neural Networks. CoRR (2022)
Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang
End-to-end Stochastic Optimization with Energy-based Model. NeurIPS (2022)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. WWW (2022)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series. CoRR (2022)
Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar
Differentiable Agent-based Epidemiology. CoRR (2022)
Jack Heavey, Jiaming Cui, Chen Chen, B. Aditya Prakash, Anil Vullikanti
Provable Sensor Sets for Epidemic Detection over Networks with Minimum Delay. AAAI (2022)
Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. ICLR (2022)
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)
Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash
Data-Centric Epidemic Forecasting: A Survey. CoRR (2022)
Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang
End-to-End Stochastic Optimization with Energy-Based Model. CoRR (2022)
Alexander Rodríguez, Harshavardhan Kamarthi, B. Aditya Prakash
Epidemic Forecasting with a Data-Centric Lens. KDD (2022)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. CoRR (2021)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. CoRR (2021)
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)
Anika Tabassum, Supriya Chinthavali, Varisara Tansakul, B. Aditya Prakash
Actionable Insights in Urban Multivariate Time-series. CIKM (2021)
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)
Alexander Rodríguez, Bijaya Adhikari, Naren Ramakrishnan, B. Aditya Prakash
Incorporating Expert Guidance in Epidemic Forecasting. CoRR (2021)
Anika Tabassum, Supriya Chinthavali, Sangkeun Lee, Nils Stenvig, Bill Kay, P. Teja Kuruganti, B. Aditya Prakash
Efficient Contingency Analysis in Power Systems via Network Trigger Nodes. IEEE BigData (2021)
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)
Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. CoRR (2021)
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. NeurIPS (2021)
Alexander Rodríguez, Bijaya Adhikari, Andrés D. González, Charles D. Nicholson, Anil Vullikanti, B. Aditya Prakash
Mapping Network States Using Connectivity Queries. CoRR (2020)
Alexander Rodríguez, Bijaya Adhikari, Andrés D. González, Charles D. Nicholson, Anil Vullikanti, B. Aditya Prakash
Mapping Network States using Connectivity Queries. IEEE BigData (2020)
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) (2020)
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 (2020)
Sorour E. Amiri, Bijaya Adhikari, John E. Wenskovitch, Alexander Rodríguez, Michelle Dowling, Chris North, B. Aditya Prakash
NetReAct: Interactive Learning for Network Summarization. CoRR (2020)
Prathyush Sambaturu, Bijaya Adhikari, B. Aditya Prakash, Srinivasan Venkatramanan, Anil Vullikanti
Designing Effective and Practical Interventions to Contain Epidemics. AAMAS (2020)
Bijaya Adhikari, Xinfeng Xu, Naren Ramakrishnan, B. Aditya Prakash
EpiDeep: Exploiting Embeddings for Epidemic Forecasting. KDD (2019)
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)
Liangzhe Chen, B. Aditya Prakash
Joint Post and Link-level Influence Modeling on Social Media. SDM (2019)
Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, B. Aditya Prakash
Data-driven efficient network and surveillance-based immunization. Knowl. Inf. Syst. 61 (3) (2019)
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) (2019)
Bijaya Adhikari, Yao Zhang, Sorour E. Amiri, Aditya Bharadwaj, B. Aditya Prakash
Propagation-Based Temporal Network Summarization. IEEE Trans. Knowl. Data Eng. 30 (4) (2018)
Bijaya Adhikari, Parikshit Sondhi, Wenke Zhang, Mohit Sharma, B. Aditya Prakash
Mining E-Commerce Query Relations using Customer Interaction Networks. WWW (2018)
Mohammad Raihanul Islam, B. Aditya Prakash, Naren Ramakrishnan
SIGNet: Scalable Embeddings for Signed Networks. PAKDD (2) (2018)
Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash
Automatic Segmentation of Dynamic Network Sequences with Node Labels. IEEE Trans. Knowl. Data Eng. 30 (3) (2018)
Sorour E. Amiri, Bijaya Adhikari, Aditya Bharadwaj, B. Aditya Prakash
NetGist: Learning to Generate Task-Based Network Summaries. ICDM (2018)
Liangzhe Chen, Sorour E. Amiri, B. Aditya Prakash
Automatic Segmentation of Data Sequences. AAAI (2018)
Mohammad Raihanul Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, Naren Ramakrishnan
DeepDiffuse: Predicting the 'Who' and 'When' in Cascades. ICDM (2018)
Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash
Sub2Vec: Feature Learning for Subgraphs. PAKDD (2) (2018)
Bijaya Adhikari, Pavan Rangudu, B. Aditya Prakash, Anil Vullikanti
Near-Optimal Mapping of Network States using Probes. SDM (2018)
Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash
Efficiently summarizing attributed diffusion networks. Data Min. Knowl. Discov. 32 (5) (2018)
Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash
SnapNETS: Automatic Segmentation of Network Sequences with Node Labels. AAAI (2017)
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) (2017)
Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash
Distributed Representations of Subgraphs. ICDM Workshops (2017)
Yasuko Matsubara, Yasushi Sakurai, B. Aditya Prakash, Lei Li, Christos Faloutsos
Nonlinear Dynamics of Information Diffusion in Social Networks. ACM Trans. Web 11 (2) (2017)
Karthik Subbian, B. Aditya Prakash, Lada A. Adamic
Detecting Large Reshare Cascades in Social Networks. WWW (2017)
Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura L. Pullum, B. Aditya Prakash
Data-Driven Immunization. ICDM (2017)
Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, B. Aditya Prakash
Distributed Representation of Subgraphs. CoRR (2017)
Bijaya Adhikari, Yao Zhang, Aditya Bharadwaj, B. Aditya Prakash
Condensing Temporal Networks using Propagation. SDM (2017)
Yao Zhang, Bijaya Adhikari, Steve T. K. Jan, B. Aditya Prakash
MeiKe: Influence-based Communities in Networks. SDM (2017)
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)
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) (2016)
Polina Rozenshtein, Aristides Gionis, B. Aditya Prakash, Jilles Vreeken
Reconstructing an Epidemic Over Time. KDD (2016)
Ahsanur Rahman, Steve T. K. Jan, Hyunju Kim, B. Aditya Prakash, T. M. Murali
Unstable Communities in Network Ensembles. SDM (2016)
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) (2016)
B. Aditya Prakash, Naren Ramakrishnan
Leveraging Propagation for Data Mining: Models, Algorithms and Applications. KDD (2016)
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) (2016)
Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash
Segmenting Sequences of Node-Labeled Graphs. ICDM Workshops (2016)
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)
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) (2016)
B. Aditya Prakash
Prediction Using Propagation: From Flu Trends to Cybersecurity. IEEE Intell. Syst. 31 (1) (2016)
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) (2016)
Chanhyun Kang, Noseong Park, B. Aditya Prakash, Edoardo Serra, V. S. Subrahmanian
Ensemble Models for Data-driven Prediction of Malware Infections. WSDM (2016)
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 (2016)
Ahsanur Rahman, Steve T. K. Jan, Hyunju Kim, B. Aditya Prakash, T. M. Murali
Mining Unstable Communities from Network Ensembles. ICDM Workshops (2015)
Shashidhar Sundareisan, Jilles Vreeken, B. Aditya Prakash
Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics. SDM (2015)
Sudip Saha, Abhijin Adiga, B. Aditya Prakash, Anil Kumar S. Vullikanti
Approximation Algorithms for Reducing the Spectral Radius to Control Epidemic Spread. SDM (2015)
Yao Zhang, B. Aditya Prakash
Data-Aware Vaccine Allocation Over Large Networks. ACM Trans. Knowl. Discov. Data 10 (2) (2015)
Sudip Saha, Abhijin Adiga, B. Aditya Prakash, Anil Kumar S. Vullikanti
Approximation Algorithms for Reducing the Spectral Radius to Control Epidemic Spread. CoRR (2015)
Yao Zhang, Abhijin Adiga, Anil Vullikanti, B. Aditya Prakash
Controlling Propagation at Group Scale on Networks. ICDM (2015)
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)

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Publication Activity (10 Years)

Top Topics

Top Venues

B. Aditya Prakash