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About Me

I am an Associate Professor of Computing at the Georgia Institute of Technology, Atlanta. I received a PhD in Computer Science from Carnegie Mellon University, Pittsburgh in 2012, and a BTech in Computer Science and Engineering from the Indian Institute of Technology - Bombay in 2007. Short third-person bio can be found HERE. My CV is here: PDF.

       

Research Interests

How do you forecast pandemics? How you do distribute resources to stop an outbreak as fast as possible? How do failures in power grids cascade? I am broadly interested in Data Science, Machine Learning and AI with emphasis on solving big-data problems in networks and sequences. Many of the research questions I answer deal with understanding and managing efficiently, dynamical mechanisms (like propagation) on networks, occurring across natural, social and technological systems. These include problems motivated from public health, computational epidemiology, cybersecurity, urban computing and the web. My research combines theoretical analysis of models, developing efficient algorithms and empirical studies on large scale data.

My advisor at CMU was Prof. Christos Faloutsos. Earlier at IIT Bombay, my advisor was Prof. S. Sudarshan where I worked on Query Optimization.

News

Publications: Pre-prints and Peer-reviewed

Disclaimer: All pdfs here are the author's version of the work. They are posted here by permission of ACM/IEEE/Springer for your personal use, not for re-distribution. The definitive version was published in the respective conference proceedings/journal issue.

My DBLP entry (contains a subset of my publications)

(in reverse chronological order)

Pre-prints

1. Ensemble forecasts of coronavirus disease 2019 (COVID-19) in the US [PDF]
   E. Ray et al.
2. DF2: Distribution-Free Decision-Focused Learning [PDF]
   Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang

Peer-reviewed Journals, Conferences and Workshops

3. Accurately Estimating Unreported Infections using Information Theory [PDF]
   Jiaming Cui, Arash Haddadan, A S M Ahsan Ul Haque, Bijaya Adhikari, Anil Vullikanti and B. Aditya Prakash
   in SIAM Data Mining (SDM) 2025, Alexandria.
4. Large Pre-trained time series models for cross-domain Time series analysis tasks [PDF]
   Harshavardhan Kamarthi and B. Aditya Prakash
   in NeurIPS 2024, Vancouver.
5. Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis [PDF]
   Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang and B. Aditya Prakash
   in NeurIPS 2024, Vancouver.
6. Machine learning for data-centric epidemic forecasting [PDF]
   Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre and B. Aditya Prakash
   in Nature Machine Intelligence, September, 2024.
7. Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations [PDF]
   S. Mathis et al.
   in Nature Communications, June 2024
8. Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity [PDF]
   Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk and B. Aditya Prakash
   in SIGKDD 2024, Barcelona.
9. A Review of Graph Neural Networks in Epidemic Modeling [PDF]
   Zewen Liu, Guancheng Wan, B. Aditya Prakash, Max S. Y. Lau, Wei Jin
   in SIGKDD 2024, Barcelona.
10. LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting [PDF]
    Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi and B. Aditya Prakash
    in Findings of the ACL 2024, Bangkok.
11. Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning [PDF]
    Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang and B. Aditya Prakash
    in ICML 2024, Vienna.
12. A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation [PDF]
    Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash and Wei Jin.
    in IJCAI 2024, Jeju.
13. PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks [PDF]
    Zhiyuan Zhao, Xueying Ding and B. Aditya Prakash
    in ICLR 2024, Vienna.
14. H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions. [PDF]
    Vivek Anand, Jiaming Cui, Jack Heavey, Anil Vullikanti and B. Aditya Prakash
    in SIAM Data Mining (SDM) 2024, Houston.
    Received the Best Poster Award
15. Modeling relaxed policies for discontinuation of Methicillin Resistant Staphylococcus aureus contact precautions. [PDF]
    Jiaming Cui, Jack Heavey, Leo Lin, Eili Y. Klein, Gregory R. Madden, Costi D. Sifri, Bryan Lewis, Anil Vullikanti and B. Aditya Prakash.
    in Inf. Control and Hosp. Epidemiology (ICHE) 2024.
16. Using spectral characterization to identify healthcare-associated infection (HAI) patients for clinical contact precaution. [PDF]
    Jiaming Cui, Sungjun Cho, Methun Kamruzzaman, Matthew Bielskas, Anil Vullikanti and B. Aditya Prakash.
    in Scientific Reports, 2023
17. Using Neural Networks to Calibrate Agent Based Models Enables Improved Regional Evidence for Vaccine Strategy and Policy. [PDF]
    Ayush Chopra, Alexander Rodriguez, B. Aditya Prakash, Ramesh Raskar and Thomas Kingsley.
    in Vaccine – Special Issue in ML-Driven Vaccine Development against Emerging Infections. September 2023
18. PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series. [PDF]
    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
    in SIGKDD 2023, Long Beach, CA.
19. Empirical networks for localized COVID-19 interventions using WiFi infrastructure at university campuses [PDF]
    Vedant Das Swain, Jiajia Xie, Maanit Madan, Sonia Sargolzaei, James Cai, Munmun De Choudhury, Gregory D. Abowd, Lauren N. Steimle and B. Aditya Prakash
    in Front. Digit. Health, May 2023
20. Autoregressive Diffusion Model for Graph Generation [PDF]
    Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang
    in ICML 2023, Hawaii.
21. Differentiable Agent-based Epidemiology [PDF]
    Ayush Chopra, Alexander Rodriguez, Jayakumar Subramanian, Arnau Quera-Bofarull, Balaji Krishnamurthy, B. Aditya Prakash and Ramesh Raskar
    in AAMAS 2023, London.
    Preliminary version at ICML AI4ABM 2022 received the Best Paper Award
22. Detecting Sources of Healthcare Associated Infections [PDF]
    Hankyu Jang, Andrew Fu, Jiaming Cui, Methun Kamruzzaman, B. Aditya Prakash, Anil Vullikanti, Bijaya Adhikari, Sriram Pemmaraju
    in AAAI 2023, Washington DC
23. EINNs: Epidemiologically-Informed Neural Networks [PDF]
    Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari and B. Aditya Prakash
    in AAAI 2023, Washington DC
24. End-to-end Stochastic Programming with Energy-based Model [PDF]
    Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang
    in NeurIPS 2022 (New Orleans)
25. Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US [PDF]
    E. Cramer et al.
    in Proc. of the National Academy of Sciences of U.S.A. (PNAS) 2022
26. Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future [PDF]
    Harshavardhan Kamarthi, Alexander Rodríguez and B. Aditya Prakash
    in ICLR 2022, virtual
27. CAMUL: Calibrated and Accurate Multi-view Time-Series Forecasting [PDF]
    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang and B. Aditya Prakash
    in The Web Conference (WWW) 2022, virtual.
28. Provable Sensor Sets for Epidemic Detection over Networks with Minimum Delay [PDF]
    Jack Heavey, Jiaming Cui, Chen Chen, B. Aditya Prakash, Anil Vullikanti.
    in AAAI 2022, Vancouver BC
29. Efficient Contingency Analysis in Power Systems via Network Trigger Nodes [PDF]
    Anika Tabassum, Supriya Chinthavali, Sangkeun Lee, Nils Stenvig, Bill Kay, Teja Kuruganti, and B. Aditya Prakash
    in IEEE BigData 2021 (long paper) (virtual)
30. When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting [PDF]
    Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang and B. Aditya Prakash
    in NeurIPS 2021 (virtual)
31. Actionable Insights in Multivariate Time-series for Urban Analytics [PDF]
    Anika Tabassum, Supriya Chinthavali, Varisara Tansakul and B. Aditya Prakash
    in ACM CIKM 2021 (virtual).
32. DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting [PDF]
    Alexander Rodríguez, Anika Tabassum, Jiaming Cui, Jiajia Xie, Javen Ho, Pulak Agarwal, Bijaya Adhikari and B. Aditya Prakash.
    in IAAI 2021 (virtual).
33. Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19 [PDF]
    Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan and B. Aditya Prakash.
    in AAAI 2021 (virtual).
    (Shorter version in NeurIPS 2020 Machine Learning in Public Health (MLPH) Workshop)
34. NetReAct: Interactive Learning for Network Summarization [PDF]
    Sorour E Amiri, Bijaya Adhikari, John Wenskovitch, Alexander Rodriguez, Michelle Dowling, Chris North and B. Aditya Prakash.
    in NeurIPS 2020 Human and Model in the Loop Evaluation and Training Strategies (HAMLETS) Workshop.
35. Mapping Network States using Connectivity Queries [PDF]
    Alexander Rodriguez, Bijaya Adhikari, Andres D. Gonzalez, Charles Nicholson, Anil Vullikanti, and B. Aditya Prakash.
    in IEEE BigData, Atlanta. (long paper). 2020.
    (Shorter version in NeurIPS 2020 Artificial Intelligence and Humanitarian and Disaster Relief (AI + HADR) Workshop)
36. Cut-n-Reveal: Time-Series Segmentations with Explanations [PDF]
    Liangzhe Chen, Nikhil Muralidhar, Anika Tabassum, Supriya Chinthavali, Naren Ramakrishnan and B. Aditya Prakash.
    in ACM Transactions on Intelligent Systems and Technology (TIST). 2020.
37. Incorporating Expert Guidance in Epidemic Forecasting [PDF]
    Alexander Rodriguez, Bijaya Adhikari, Naren Ramakrishnan, and B. Aditya Prakash.
    in ACM SIGKDD Epidemiology meets Data Mining and Knowledge Workshop 2020.
38. Designing Near-Optimal Temporal Interventions to Contain Epidemics [PDF]
    Prathyush Sambaturu, Bijaya Adhikari, B. Aditya Prakash, Srinivasan Venkatramanan, Anil Vullikanti.
    in AAMAS 2020, Auckland.
    Invited to JAAMAS Special Issue (AAMAS Best papers)
39. Tracking and Analyzing Dynamics of News-cycles during Global Pandemics: A Historical Perspective [PDF]
    Sorour E. Amiri, Anika Tabassum, E. Thomas Ewing and B. Aditya Prakash
    in SIGKDD Explorations. Vol 21, Issue 2. 2019.
40. Fast and Near-Optimal Monitoring for Healthcare Acquired Infection Outbreaks [PDF]
    Bijaya Adhikari, Bryan Lewis, Anil Vullikanti, Jose Mauricio Jimenez, and B. Aditya Prakash
    in PLoS Computational Biology. 2019.
41. EpiDeep: Exploiting Embeddings for Epidemic Forecasting [PDF] [CODE]
    Bijaya Adhikari, Xinfeng Xu, Naren Ramakrishnan and B. Aditya Prakash
    in SIGKDD 2019, Anchorage.
42. Urban-Net: A System to Understand and Analyze Critical Infrastructure Networks for Emergency Management [PDF] [DEMO]
    Anika Tabassum, Supriya Chinthavali, Sangkeun Lee, Liangzhe Chen and B. Aditya Prakash
    in SIGKDD 2019, Anchorage.
43. Joint Post and Link-level Influence Modeling on Social Media [PDF] [CODE]
    Liangzhe Chen and B. Aditya Prakash
    in SDM 2019, Calgary.
44. Latent Allocation Spatiotemporal Models For Indoor Human Mobility [PDF]
    Yiming Gu, Hala Mostafa, and B. Aditya Prakash
    in ACM SIGKDD Urban Computing Workshop 2018.
45. Forecasting the Flu: Designing Social Network Sensors for Epidemics [PDF]
    Huijuan Shao, K.S.M. Tozammel Hossain, Hao Wu, Maleq Khan, Anil Vullikanti, B. Aditya Prakash, Madhav Marathe and Naren Ramakrishnan
    in ACM SIGKDD Epidemiology meets Data Mining and Knowledge Workshop 2018.
46. Data Driven Efficient Network and Surveillance-based Immunization [PDF] [CODE]
    Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, and B. Aditya Prakash
    in Knowledge and Information Systems Journal, Springer. 2018.
47. NetGist: Learning to generate task-based network summaries [PDF] [CODE]
    Sorour E. Amiri, Bijaya Adhikari, Aditya Bharadwaj, and B. Aditya Prakash
    in IEEE ICDM 2018, Singapore.
48. DeepDiffuse: Predicting the 'Who' and 'When' in Cascades [PDF] [CODE]
    Mohammad R Islam, Sathappan Muthiah, Bijaya Adhikari, B. Aditya Prakash, and Naren Ramakrishnan
    in IEEE ICDM 2018, Singapore.
49. Efficiently Summarizing Attributed Diffusion Networks [PDF] [CODE]
    Sorour Amiri, Liangzhe Chen and B. Aditya Prakash.
    in ECML/PKDD 2018 (DAMI Journal Track), Dublin.
50. Sub2Vec: Feature Learning for Subgraphs [PDF] [CODE]
    Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan and B. Aditya Prakash.
    in PAKDD 2018, Melbourne. (long paper)
51. Distributed Representations of Signed Networks [PDF] [CODE]
    M. Raihanul Islam, B. Aditya Prakash and Naren Ramakrishnan.
    in PAKDD 2018, Melbourne. (long paper)
52. Mining E-Commerce Query Relations using Customer Interaction Networks [PDF]
    Bijaya Adhikari, Parikshit Sondhi, Wenke Zhang, Mohit Sharma and B. Aditya Prakash.
    in WWW 2018, Lyon.
53. Near-optimal Mapping of Network States using Probes [PDF] [CODE]
    Bijaya Adhikari, Pavan Rangudu, B. Aditya Prakash and Anil Vullikanti.
    in SDM 2018, San Diego.
54. Automatic Segmentation of Data Sequences [PDF] [CODE]
    Liangzhe Chen, Sorour Amiri, and B. Aditya Prakash.
    in AAAI 2018, New Orleans.
55. Propagation based Temporal Network Summarization [PDF] [CODE]
    Bijaya Adhikari, Yao Zhang, Sorour E. Amiri, Aditya Bharadwaj, and B. Aditya Prakash.
    in IEEE Transactions on Knowledge and Data Engineering (TKDE). 2017.
56. Automatic Segmentation of Dynamic Network Sequences with Node Labels [PDF] [CODE]
    Sorour Amiri, Liangzhe Chen and B. Aditya Prakash.
    in IEEE Transactions on Knowledge and Data Engineering (TKDE). 2017.
57. Data Driven Immunization [PDF] [CODE]
    Yao Zhang, Arvind Ramanathan, Anil Vullikanti, Laura Pullum, and B. Aditya Prakash.
    in IEEE ICDM 2017, New Orleans.
    Invited to KAIS Journal Special Issue (ICDM Best papers)
58. HotSpots: Failure Cascades on Heterogeneous Critical Infrastructure Networks [PDF] [CODE]
    Liangzhe Chen, Xinfeng Xu, Sangkeun Lee, Sisi Duan, Alfonso G. Tarditi, Supriya Chinthavali and B. Aditya Prakash.
    in ACM CIKM 2017, Singapore.
59. Distributed Representations of Subgraphs [PDF]
    Bijaya Adhikari, Yao Zhang, Naren Ramakrishnan, and B. Aditya Prakash
    in IEEE ICDM Data Mining Large Networks Workshop 2017
60. Graphs for Malware Detection: The Next Frontier [PDF]
    Abhishek Sharma and B. Aditya Prakash
    in ACM SIGKDD Mining and Learning with Graphs Workshop 2017
61. Using Partial Probes to Infer Network States [PDF]
    Venkata Pavan Rangudu, Bijaya Adhikari, B. Aditya Prakash and Anil Vullikanti
    in ACM SIGKDD Mining and Learning with Graphs Workshop 2017
62. Condensing Temporal Networks using Propagation [PDF]
    Bijaya Adhikari, Yao Zhang and B. Aditya Prakash
    in NetSci 2017.
63. URBAN-NET: A Network-based Infrastructure Monitoring and Analysis System for Emergency Management and Public Safety [PDF]
    Sangkeun Lee, Liangzhe Chen, Sisi Duan, Supriya Chinthavali, Mallikarjun Shankar, and B. Aditya Prakash
    in IEEE BigData Workshop on Big Data for Sustainable Development 2016
64. Segmenting Sequences of Node-labeled Graphs [PDF]
    Sorour Amiri, Liangzhe Chen and B. Aditya Prakash
    in IEEE ICDM Data Mining Large Networks Workshop 2016
65. MeiKe: Influence-based Communities in Networks [PDF] [CODE]
    Yao Zhang, Bijaya Adhikari, Steve Jan and B. Aditya Prakash.
    in SDM 2017, Houston.
66. Condensing Temporal Networks using Propagation [PDF] [CODE]
    Bijaya Adhikari, Yao Zhang, Aditya Bharadwaj and B. Aditya Prakash.
    in SDM 2017, Houston.
67. Detecting Large Reshare Cascades in Social Networks [PDF]
    Karthik Subbian, B. Aditya Prakash and Lada Adamic.
    in WWW 2017, Perth.
68. Non-linear Dynamics of Information Diffusion in Social Networks [PDF]
    Yasuko Matsubara, Yasushi Sakurai, B. Aditya Prakash, Lei Li and Christos Faloutsos.
    in ACM Transactions on the Web (TWEB). 2017.
69. SnapNETS: Automatic Segmentation of Network Sequences with Node Labels [PDF] [CODE]
    Sorour Amiri, Liangzhe Chen and B. Aditya Prakash.
    in AAAI 2017, San Francisco.
70. Current and Future Challenges in Mining Large Networks [PDF]
    with Larry Holder, Maleq Khan and others.
    in SIGKDD Explorations. Vol. 18, Issue 1. 2016.
71. Near-optimal Algorithms for Controlling Propagation at Group Scale on Networks [PDF] [CODE]
    Yao Zhang, Abhijin Adiga, Sudip Saha, Anil Vullikanti and B. Aditya Prakash.
    in IEEE Transactions on Knowledge and Data Engineering (TKDE). 2016.
72. Reconstructing an Epidemic over Time [PDF] [CODE]
    Polina Rozenshtein, Aristides Gionis, B. Aditya Prakash and Jilles Vreeken.
    in SIGKDD 2016, San Francisco
73. Eigen-Optimization on Large Graphs by Edge Manipulation [PDF]
    Chen Chen, Hanghang Tong, B. Aditya Prakash, Tina Eliassi-Rad, Michalis Faloutsos and Christos Faloutsos.
    in ACM Transactions on Knowledge Discovery in Data (TKDD). 2016.
74. Understanding the Relationship between Human Behavior and Susceptibility to Cyber-Attacks: A Data-Driven Approach [PDF]
    Michael Ovelgonne, Tudor Dumitras, B. Aditya Prakash, V. S. Subrahmanian and Benjamin Wang
    in ACM Transactions on Intelligent Systems and Technology (TIST). 2016.
75. Unstable Communities in Network Ensembles [PDF]
    Ahsanur Rahman, Steve Jan, Hyunju Kim, B. Aditya Prakash and T. M. Murali
    in SDM 2016, Miami.
76. Ensemble Models for Data-Driven Prediction of Malware Infections [PDF]
    Chanhyun Kang, Noseong Park, B. Aditya Prakash, Edoardo Serra, and V. S. Subrahmanian
    in ACM WSDM 2016, San Francisco.
77. Syndromic Surveillance of Flu on Twitter Using Weakly Supervised Temporal Topic Models [PDF] [CODE]
    Liangzhe Chen, K. S. M. Tozammel Hossain, Patrick Butler, Naren Ramakrishnan and B. Aditya Prakash
    in Data Mining and Knowledge Discovery Journal (DAMI), Springer. 2015.
78. Controlling Propagation at Group Scale on Networks [PDF][CODE]
    Yao Zhang, Abhijin Adiga, Anil Vullikanti and B. Aditya Prakash
    in IEEE ICDM 2015, Atlantic City.
79. Mining Unstable Communities from Network Ensembles [PDF]
    Ahsanur Rahman, Steve Jan, Hyunju Kim, B. Aditya Prakash and T. M. Murali
    in IEEE ICDM Data Mining Large Networks Workshop 2015
80. Node Immunization on Large Graphs: Theory and Algorithms [PDF]
    Chen Chen, Hanghang Tong, B. Aditya Prakash, Charalampos Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos and Polo Chau
    in IEEE Transactions on Knowledge and Data Engineering (TKDE). 2015.
81. Data-Aware Vaccine Allocation over Large Networks [PDF][CODE]
    Yao Zhang and B. Aditya Prakash
    in ACM Transactions on Knowledge Discovery in Data (TKDD). 2015.
82. Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics [PDF][CODE]
    Shashidhar Sundareisan, Jilles Vreeken and B. Aditya Prakash
    in SDM 2015, Vancouver.
83. Approximation Algorithms for Reducing the Spectral Radius to control Epidemic Spread [PDF] [CODE]
    Sudip Saha, Abhijin Adiga, B. Aditya Prakash and Anil Vullikanti
    in SDM 2015, Vancouver.
84. SharkFin: Spatio-temporal mining of software adoption and penetration [PDF]
    Evangelos E. Papalexakis, Tudor Dumitras, Duen Horng Chau, B. Aditya Prakash and Christos Faloutsos
    in Social Network Analysis and Mining Journal, Springer. 2014.
85. Flu Gone Viral: Syndromic Surveillance of Flu on Twitter using Temporal Topic Models [PDF] [CODE]
    Liangzhe Chen, K. S. M. Tozammel Hossain, Patrick Butler, Naren Ramakrishnan and B. Aditya Prakash
    in IEEE ICDM 2014, Shenzhen
86. Scalable Vaccine Distribution in Large Graphs given Uncertain Data [PDF] [CODE]
    Yao Zhang and B. Aditya Prakash
    in ACM CIKM 2014, Shanghai
87. SansText: Classifying Temporal Topic Dynamics of Twitter Cascades Without Tweet Text [PDF]
    Shashidhar Sundareisan, Abhay Rao Bhadriraju, M. Saquib Khan, Naren Ramakrishnan and B. Aditya Prakash
    in ACM/IEEE ASONAM 2014, Beijing
88. Fast Influence-based Coarsening for Large Networks [PDF] [CODE]
    Manish Purohit, B. Aditya Prakash, Chanhyun Kang, Yao Zhang and V. S. Subrahmanian
    in SIGKDD 2014, New York City
89. Modeling Mass Protest Adoption in Social Network Communities using Geometric Brownian Motion [PDF]
    Fang Jin, Rupinder Khandpur, Nathan Self, Edward Dougherty, Feng Chen, B. Aditya Prakash and Naren Ramakrishnan
    in SIGKDD 2014, New York City
90. DAVA: Distributing Vaccines over Large Networks under Prior Information [PDF] [CODE]
    Yao Zhang and B. Aditya Prakash
    in SDM 2014, Philadelphia
91. Spatio-temporal Mining of Software Adoption & Penetration [PDF]
    Evangelos E. Papalexakis, Tudor Dumitras, Duen Horng Chau, B. Aditya Prakash and Christos Faloutsos
    in ACM/IEEE ASONAM 2013, Niagara Falls
    Invited to Social Network Analysis and Mining (SNAM) journal (ASONAM Best Papers)
92. Efficiently Spotting the Starting Points of an Epidemic in a Large Graph [PDF]
    B. Aditya Prakash, Jilles Vreeken and Christos Faloutsos
    to appear in Knowledge and Information Systems Journal, Springer. 2013.
93. Fractional Immunization on Networks [PDF]
    B. Aditya Prakash, Lada Adamic, Theodore Iwashnya, Hanghang Tong and Christos Faloutsos
    in SDM 2013, Austin
94. Patterns amongst Competing Task Frequencies: Super-Linearities, and the Almond-DG model [PDF]
    Danai Koutra, Vaseilios Koutras, B. Aditya Prakash and Christos Faloutsos
    in PAKDD 2013, Gold Coast
95. Competing Memes Propagation on Networks: A Network Science Perspective [PDF]
    Xuetao Wei, Nicholas Valler, B. Aditya Prakash, Iulian Neamtiu, Michalis Faloutsos and Christos Faloutsos
    in IEEE Journal on Selected Areas in Communication (Special Issue on Network Science), 2013 (to appear)
96. Spotting Culprits in Epidemics: How many and Which ones? [PDF]
    B. Aditya Prakash, Jilles Vreeken and Christos Faloutsos
    in IEEE ICDM 2012, Brussels
    Invited to KAIS Journal Special Issue (ICDM Best papers)
97. Competing Meme Propagation on Networks: A Case Study of Composite Networks [PDF]
    Xuetao Wei, Nicholas Valler, B. Aditya Prakash, Iulian Neamtiu, Michalis Faloutsos and Christos Faloutsos
    in ACM SIGCOMM Computer Communication Review, October 2012
98. Gelling, and Melting, Large Graphs through Edge Manipulation [PDF]
    Hanghang Tong, B. Aditya Prakash, Tina Eliassi-Rad, Michalis Faloutsos and Christos Faloutsos
    in ACM CIKM 2012, Mauii
    Received the Best Paper Award (among all three DB, IR, KM tracks)
99. Rise and Fall Patterns of Information Diffusion: Model and Implications [PDF]
    Yasuko Matsubara, Yasushi Sakurai, B. Aditya Prakash, Lei Li and Christos Faloutsos
    in SIGKDD 2012, Beijing
100. Interacting Viruses on a Network: Can both survive? [PDF]
     Alex Beutel, B. Aditya Prakash, Roni Rosenfeld and Christos Faloutsos
     in SIGKDD 2012, Beijing
101. Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks [PDF]
     B. Aditya Prakash, Deepayan Chakrabarti, Michalis Faloutsos, Nicholas Valler, Christos Faloutsos
     in Knowledge and Information Systems Journal, Springer. 2012.
102. Winner-takes-all: Competing Viruses on fair-play networks [PDF]
     B. Aditya Prakash, Alex Beutel, Roni Rosenfeld, Christos Faloutsos
     in WWW 2012, Lyon
103. Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks [PDF] [extended arXiv version]
     B. Aditya Prakash, Deepayan Chakrabarti, Michalis Faloutsos, Nicholas Valler, Christos Faloutsos
     in IEEE ICDM 2011, Vancouver
     Invited to KAIS Journal Special Issue (ICDM Best papers)
104. Time Series Clustering: Complex is Simpler! [PDF] [CODE]
     Lei Li, B. Aditya Prakash
     in ICML 2011, Bellevue
105. Epidemic Spread in Mobile Ad Hoc Networks: Determining the Tipping Point [PDF]
     Nicholas Valler, B. Aditya Prakash, Hanghang Tong, Michalis Faloutsos, Christos Faloutsos
     
106. Formalizing the BGP stability problem: Patterns and a Chaotic model [PDF]
     B. Aditya Prakash, Michalis Faloutsos, Christos Faloutsos
     CMU-TR, Preliminary Version in IEEE INFOCOM NetSciCom Workshop 2011
     
in IFIP NETWORKING 2011, Valencia
107. On the Vulnerability of Large Graphs [PDF][CODE]
     Hanghang Tong, B. Aditya Prakash, Charalampos Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos, Duen Horng Chau
     in IEEE ICDM 2010, Sydney
108. Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms [PDF]
     B. Aditya Prakash, Hanghang Tong, Nicholas Valler, Michalis Faloutsos, Christos Faloutsos
     in ECML-PKDD 2010, Barcelona
109. Parsimonious Linear Fingerprinting for Time Series [PDF][CODE]
     Lei Li, B. Aditya Prakash, Christos Faloutsos
     in VLDB 2010, Singapore
110. MetricForensics: A Multi-Level Approach for Mining Volatile Graphs [PDF]
     Keith Henderson, Tina Eliassi-Rad, Christos Faloutsos, Leman Akoglu, Lei Li, Koji Maruhashi, B. Aditya Prakash, Hanghang Tong
     in SIGKDD 2010, Washington DC
     
111. EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs [PDF][CODE]
     B. Aditya Prakash, Ashwin Sridharan, Mukund Seshadri, Sridhar Machiraju, Christos Faloutsos
     in PAKDD 2010, Hyderabad
112. BGP-lens: Patterns and Anomalies in Internet Routing Updates [PDF][CODE]
     B. Aditya Prakash, Nicholas Valler, David Andersen, Michalis Faloutsos, Christos Faloutsos
     in SIGKDD 2009, Paris
113. Surprising Patterns and Scalable Community Detection in Large Graphs [PDF]
     B. Aditya Prakash, Ashwin Sridharan, Mukund Seshadri, Sridhar Machiraju, Christos Faloutsos
     in IEEE ICDM Large Scale Data Mining Workshop 2009
114. FRAPP: A framework for high-accuracy privacy-preserving mining [PDF]
     Shipra Agrawal, Jayant R. Haritsa, B. Aditya Prakash
     in Data Mining and Knowldge Discovery Journal, Springer, 2008
115. Complex Group-by Queries for XML [PDF]
     C. Gokhale, N. Gupta, P. Kumar, L. V. S. Lakshmanan, R. Ng, B. Aditya Prakash
     in ICDE 2007, Istanbul, Turkey

Book, Book Chapters and Invited Articles

Book

1. The Global Cyber-Vulnerability Report [Link to Website]
   V. S. Subrahmanian, Michael Ovelgonne, Tudor Dumitras and B. Aditya Prakash
   Springer, 2016.

Book Chapter

2. Graph Mining for Cyber Security [Link to Website]
   B. Aditya Prakash
   Book Chapter in Cyber Warfare: Building the Scientific Foundation, Springer, 2015.

Invited Articles

3. Data Mining Critical Infrastructure Systems: Models and Tools [PDF]
   Anika Tabassum, Supriya Chinthavali, Liangzhe Chen and B. Aditya Prakash
   Feature Article in IEEE Intelligent Informatics Bulletin (IIB), Dec 2018 Issue.
4. Network and Propagation Analysis [PDF]
   B. Aditya Prakash
   ‘AIs 10 to Watch: The Future of AI’ in IEEE Intelligent Systems Magazine, Jan-Feb 2018 Issue.
5. Prediction using Propagation: From Flu-Trends to Cyber Security [PDF]
   B. Aditya Prakash
   'Predictive Analytics' Column in IEEE Intelligent Systems Magazine, Jan-Feb 2016 Issue.
6. Propagation and Immunization in Large Networks [PDF]
   B. Aditya Prakash
   in Crossroads: The ACM Magazine for Students-Big Data Issue, Fall 2012 Issue.

Theses

1. Understanding and Managing Propagation on Large Networks: Theory, Algorithms and Models [PDF]
   B. Aditya Prakash
   Ph.D. Thesis, Carnegie Mellon University, 2012
2. On Query Optimization Issues in Fine-Grained Authorization
   B. Aditya Prakash
   B.Tech Thesis, IIT Bombay, 2007

Talks/Tutorials

An unsorted list HERE.

1. Data Mining Critical Infrastructure Systems---Models and Tools [LINK]
   Liangzhe Chen and B. Aditya Prakash
   Tutorial at SIAM SDM 2018, San Diego
2. Propagation for Data Mining: Models, Algorithms and Applications [LINK]
   B. Aditya Prakash and Naren Ramakrishnan
   Tutorial at SIAM SDM 2017, Houston
3. Propagation for Data Mining: Models, Algorithms and Applications [LINK]
   B. Aditya Prakash and Naren Ramakrishnan
   Tutorial at SIGKDD 2016, San Francisco
4. Understanding and Managing Cascades in Large Graphs [LINK]
   B. Aditya Prakash and Christos Faloutsos
   Tutorial at ECML/PKDD 2012, Bristol
5. Understanding and Managing Cascades in Large Graphs [LINK]
   B. Aditya Prakash and Christos Faloutsos
   Tutorial at VLDB 2012, Istanbul

Patents

1. US Patent 9,491,055. Determining User Communities in Communication Networks
   Ashwin Sridharan, Mukund Seshadri, James Schneider, B. Aditya Prakash, Christos Faloutsos, Sridhar Machiraju
   granted, November 2016
2. US Patent 8,805,839. Analysis of Computer Network Activity by Successively Removing Accepted Types of Access Events
   B. Aditya Prakash, Alice Zheng, Jack Stokes, Eric Fitzgerald, Theodore Hardy
   granted, August 2014

Funding

Thanks to the following for funding our research and teaching.

1. NSF IIS Medium (Spatio-Temporal)
2. CDC MIND
3. NSF CCF
4. NSF COVID RAPID
5. Oak Ridge National Laboratory
6. NSF IIS Medium (HAIs)
7. NSF CISE Expeditions
8. NSF CAREER
9. NEH-DFG (Bilateral Digital Humanities) HG-229283
10. Facebook Faculty Gift
11. NSF IIS-1353346
12. NSA (Science of Security)
13. Amazon AWS in Education

Service Activities

Latest: Focus Area Chair AAAI 2021 'AI for COVID-19' track, Proceedings Chair ACM SIGKDD 2020, Co-organizer epiDAMIK workshop at ACM SIGKDD 2020, Co-organizer DRSE workshop at SDM 2020.

Older: [expand]

Students

I am grateful to have had the opportunity to work with the following fantastic students:

• PhD Students
  1. Shangqing Xu, CSE PhD
  2. Haoxin Liu, CS PhD
  3. Zhiyuan Zhao, ML PhD
  4. Harshavardhan Kamarthi, ML PhD
  5. Jiaming Cui, CS PhD (From Spring 2025, Faculty at Virginia Tech)
  6. Dr. Alex Rodriguez, CS PhD (Current: Faculty at the University of Michigan, Ann Arbor)
  7. Dr. Anika Tabassum, CS PhD (Current: Oak Ridge National Laboratory)
  8. Dr. Bijaya Adhikari, CS PhD (Current: Faculty at the University of Iowa)
  9. Dr. Stacey Clifton, Sociology PhD (Current: Faculty at Radford University)
  10. Dr. Sorour Amiri, CS PhD (Current: Google)
  11. Dr. Liangzhe Chen, CS PhD (Current: Pinterest)
  12. Dr. Yao Zhang, CS PhD (Current: Linkedin)
• MS, Undergraduate and High-school Students
  1. Aditya Sasanur, BS+MS, CS
  2. Vivek Anand, MS CSE
  3. Jiajia Xie, MS CSE (co-advised with Lauren Steimle, ISyE GT)
  4. Xinfeng Xu, MS CS, Physics PhD
  5. Shashidhar Sundereisan, MS CS
  6. Benjamin Wang, MS CS
  7. Pulak Agarwal, BS CS
  8. Javen Ho, BS CS
  9. Mira Patel, BS Aerospace Engg
  10. William Edmisten, BS CS
  11. Priyanka Dangi, BS CS
  12. Pranav Aluru, High School

Teaching

Current

1. CSE 8803 EPI: Data Science for Epidemiology [Fall 2020, Fall 2021, Fall 2022, Fall 2023]
2. CSE 8803 IUC: Introduction to Urban Computing [Spring 2023]
3. CSE/ISYE/CS 6740 CDA: Computational Data Analysis [Fall 2021]

Older (2013-2019) [expand]

Contact

Office CODA S1207 Mailing Address: Georgia Institute of Technology 756 W Peachtree St NW, Suite S1207 Atlanta GA 30308 U.S.A.

Phone Call: +1-404-894-4663

Email invert(cc.gatech.edu @ badityap)

Admins Admin: Carolyn Young Financial Manager: Holly Rush