Journal Papers

1. A. Augello, Ashish Gupta, G. L. Re and S. K. Das, "FairRFL: Fair and Robust Federated Learning in the Presence of Selfish Clients", IEEE Transactions on Emerging Topics in Computing, vol. 14, no. 1, pp. 316-331, 2026. [Pdf][IF 4.8]

2. P. Ranjan, Ashish Gupta, Federico Corò, and S.K. Das , "FedDOT: Defending Federated Learning Against Overwhelming Targeted Attacks ", IEEE Transactions on Artificial Intelligence, pp 1-14, 2026. [Pdf][Scopus]

3. V. K. Tanwar, Ashish Gupta, S. Madria and S. K. Das, "Bit-ViP: Leveraging Bit-planes to Preserve Visual Privacy in Images through Obfuscation", IEEE Transactions on Emerging Topics in Computing, pp 1-14, 2026. [Pdf][IF 4.8]

4. Aakar Mathur, Ashish Gupta, and S.K. Das, "When Federated Learning Meets Quantum Computing:  A Survey and Research Opportunities", IEEE Communications Surveys and Tutorials, vol. 28, pp. 1351-1380, 2025. [Pdf][IF 50.6]

5. P. V. Pravija Raj, P. M. Pawar, R. Muthalagu and Ashish Gupta , "BIELM: Integrating Incremental Extreme Learning Machine and Blockchain for Secure Data Gathering in IoT-based WSNs ", IEEE Sensors Journal, vol. 26, no. 3, pp. 5204-5212, 2025. [Pdf][IF 4.5]

6. Ashish Gupta, V. K. Tanwar, Amit N. Jha, and S.K. Das, ”Analyzing Real-time Insect Detection in Smart Connected Farms”, IEEE Computer , vol. 57, no. 12, pp. 38-46, Dec. 2024 . [Pdf] [IF 2.8]

7. Rahul Mishra, Ashish Gupta, and H.P. Gupta, “Locomotion Mode Recognition using Sensory Data with Noisy Labels: A Deep Learning Approach", IEEE Transactions on Mobile Computing,  2021. [Pdf] [IF 7.9]

8. Ashish Gupta and H.P. Gupta, “YogaHelp: Leveraging Motion Sensors for Learning Correct Execution of Yoga with Feedback”, IEEE Transactions on Artificial Intelligence, vol. 2, no. 4, pp. 362-371, 2021. [Pdf] [Scopus] 

9. Ashish Gupta, H.P. Gupta, B. Biswas, and T. Dutta, “An Unseen Fault Classification Approach for Smart Appliances using Ongoing Multivariate Time Series”, IEEE Transactions on Industrial Informatics, vol. 17, no. 6, pp. 3731-3738, 2020.   [Pdf]   [IF 12.3]

10. Ashish Gupta, H.P. Gupta, B. Biswas, and T. Dutta, “A Fault-Tolerant Early Classification Approach for Human Activities using Multivariate Time Series”, IEEE Transactions on Mobile Computing, vol. 20, no. 5, pp. 1747-1760, 2020.   [Pdf]  [IF 7.9] 

11. Ashish Gupta, H. P. Gupta, B. Biswas, and T. Dutta, “An Early Classification Approach for Multivariate Time Series of On-vehicle Sensors in Transportation”, IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 12, pp. 5316-5327, 2020.   [Pdf]  [IF 8.5] 

12. Ashish Gupta, H. P. Gupta, B. Biswas, and T. Dutta, “A Divide-and-Conquer Based Early Classification Approach for Multivariate Time Series with Different Sampling Rate Components in IoT ”, ACM Transactions on Internet of Things,  vol. 1, no. 2, pp. 1-21, 2020.   [Pdf] [IF 2.7]  

13. Ashish Gupta, H. P. Gupta, B. Biswas, and T. Dutta, “Approaches and Applications of Early Classification of Time Series: A Review ”, IEEE Transactions on Artificial Intelligence,  vol. 1, no. 1, pp. 47-61, 2020.   [Pdf] [Scopus]  

14. R. Mishra, Ashish Gupta, H. P. Gupta and T. Dutta, “A Sensors based Deep Learning Model for Unseen Locomotion Mode Identification using Multiple Semantic Matrices ”, IEEE Transactions on Mobile Computing,  vol. 21, no. 3, pp. 799-810, 2020.   [Pdf]  [IF 7.9] 

15. S. Saraswat, Ashish Gupta, H. P. Gupta, and T. Dutta, “An Incremental Learning based Gesture Recognition System for Consumer Devices using Edge-Fog Computing”, IEEE Transactions on Consumer Electronics,  vol. 66, no. 1, pp. 51-60, 2019.   [Pdf]  [IF 4.3] 

16. S. Saraswat, V. Agarwal, H. P. Gupta, R. Mishra, Ashish Gupta, and T. Dutta, "Challenges and solutions in Software Defined Networking: A survey", Journal of Network and Computer Applications, vol. 141, pp. 23-58, 2019.   [Pdf]  [IF 8.7] 

17. S. Patil, Ashish Gupta, and M. Zaveri, "Recovery of lost target using target tracking in event driven clustered wireless sensor network", Journal of Computer Networks and Communications, vol. 2014, pp. 1-15, 2014.   [Pdf]  [IF 2.0]

Conference Papers

1. A. Mathur, R. Mohammed, Ashish Gupta, F. Coro, G. Lo Re, Sajal K. Das, “Can Quantum Federated Learning Withstand Circuit-Level Backdoors?", in Proc. the 35th International Joint Conference on Artificial Intelligence (IJCAI-ECAI), Bremen, Germany, 2026, pp. 1-9. [Core A*](Slides)

2. A. Augello, P. Ranjan, Ashish Gupta, F. Coro, G. Lo Re, Sajal K. Das, “BatteryFL: Battery-Aware Federated Learning", in Proc. of IEEE Global Communications Conference (GlobeCom), Taipei, Taiwan, 2025, pp. 1938-1943. [Core B][pdf](Slides)

3. K. Soltani, V. K. Tanwar, Ashish Gupta, Sajal K. Das, “Energy-Efficient Split Learning for Resource-Constrained Environments: A Smart Farming Solution", in Proc. of 22nd IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS), Chicago, USA, 2025, pp. 1-9. [Core B] [pdf]

4. P. Ranjan, Ashish Gupta, Sajal K Das, “Securing federated learning from distributed backdoor attacks via maximal clique and dynamic reputation system", in Proc. of IEEE International Conference on Smart Computing (SMARTCOMP), Cork, Ireland, 2025, pp. 130-137 [pdf]

5. Andrea Augello, Ashish Gupta, Giuseppe Lo Re, and S. K. Das, “Tackling Selfish Clients in Federated Learning”, in Proc. of 27th European Conference on Artificial Intelligence (ECAI), Santiago de Compostela, 2024, pp. 1888-1895. [Core A] [pdf]

6. Ashish Gupta,  George Markowsky, and Sajal K. Das, "Is Performance Fairness Achievable in Presence of Attackers Under Federated Learning?", In proceedings of 26th European Conference on Artificial Intelligence (ECAI), Kraków, Poland, 2023, pp. 948 - 955. [Core A] [pdf] 

7. Ashish Gupta, H.P. Gupta, and Sajal K. Das, "FedAR+: A Federated Learning Approach to Appliance Recognition with Mislabeled Data in Residential Environments", In proceedings of 14th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS),  San Antonio, Texas, USA, 2023, pp. 78-87. [pdf] 

8. P. Ranjan, Ashish Gupta, F. Corò, and Sajal K. Das, "Robust Federated Learning against Backdoor Attackers",In proceedings of 41th IEEE International Conference on Computer Communications Workshops (INFOCOM),  New York, USA, 2023, pp. 1-6. [Core A*]

9. P. Ranjan, Ashish Gupta, F. Corò, and Sajal K. Das, "Securing Federated Learning against Overwhelming Collusive Attackers", In proceedings of IEEE Global Communications Conference (GLOBECOM),  Rio de Janeiro, Brazil, 2022, pp. 1448-1453. [Core B] [pdf]

10. Ashish Gupta, Tony T. Luo, Mao V. Ngo, and Sajal K. Das, "Long-Short History of Gradients is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning", In proceedings of 27th European Symposium on Research in Computer Security (ESORICS), Copenhagen, Denmark, 2022, pp 445–465. [Core A] [pdf] [slides] [video] [code]

11. P. Ranjan, F. Corò, Ashish Gupta, and Sajal K. Das, "Leveraging Spanning Tree to Detect Colluding Attackers in Federated Learning", In proceedings of 41th IEEE International Conference on Computer Communications Workshops (INFOCOM),  Virtual, 2022, pp. 1-2 [Core A*] [pdf]

12. Ashish Gupta, H. P. Gupta, and T. Dutta, "Towards Identifying Internet Applications Using Early Classification of Traffic Flow", In proceedings of 20th Annual IFIP Networking Conference, Espoo and Helsinki, Finland , 2021, pp. 1-9.   [Core A]   [pdf] [slides]

13. Ashish Gupta, H. P. Gupta, and T. Dutta, "A Deep Learning based Traffic Flow Classification with Just a Few Packets", In proceedings of 40th IEEE International Conference on Computer Communications Workshops (INFOCOM), Vancouver, BC, Canada, 2021, pp. 1-2.  [Core A*]  [pdf] [slides]

14. Ashish Gupta, H. P. Gupta, and B. Biswas, "Early Classification Approaches for Sensors Generated Multivariate Time Series with Different Challenges", In proceedings of 22nd International Conference on Distributed Computing and Networking (ICDCN), Nara, Japan, 2021, pp. 241-242. [Doctoral Symposium]  [pdf]

15. Ashish Gupta, H. P. Gupta, T. Dutta, and S. K. Das, "Poster Abstract: Towards Identifying Alien Appliances using Semantic Information", In proceedings of 7th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys), Yokohama, Japan, 2020, pp. 328-329.  [Core A]  [pdf] [slides]

16. Ashish Gupta, R. Pal, R. Mishra, H. P. Gupta, T. Dutta, and P. Hirani, "Game Theory based Early Classification of Rivers using Time Series Data", In proceedings of IEEE World Forum on Internet of Things (WF-IoT), Limerick, Ireland, 2019, pp. 686-691. [pdf] [slides]

17. Ashish Gupta, H. P. Gupta, and T. Dutta, "Early Classification Approach for Multivariate Time Series using Sensors of Different Sampling Rate", In proceedings of 16th IEEE International Conference on Sensing, Communication, and Networking (SECON), Boston, Massachusetts, USA, 2019, pp. 1-2. [Poster] [pdf]

18. Ashish Gupta, H. P. Gupta, P. Kumari, R. Mishra, S. Saraswat, and T. Dutta, "A Real-time Precision Agriculture Monitoring System using Mobile Sink in WSNs", In proceedings of 12th IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Indore, India, 2018, pp. 1-5. [pdf]

19. M. Agrawal, K. Manchanda, A. Agarwal, S. Saraswat, Ashish Gupta, H. P. Gupta, and T. Dutta, "A Supervised Approach-based Job Scheduling Technique for Distributed Real-Time Systems", In proc. of 12th IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Indore, India, 2018, pp. 1-6. [pdf]

20. Ashish Gupta, S. Patil, and M. Zaveri,"Lost target recovery in wireless sensor network using tracking", In proceedings of IEEE International Conference on Communication Systems and Network Technologies, Rajkot, India, 2012, pp. 352-356. [pdf]

21. S. Patil, Ashish Gupta, and M. Zaveri, "Efficient target recovery in wireless sensor network", In Proceedings of International Conference on Advances in Computing and Information Technology, Chennai, India, 2012, pp. 385-394  [pdf]

Book Chapters

• P. Ranjan, Ashish Gupta, and Sajal K. Das, “Robust Federated Learning against Targeted Attackers using Model Updates Correlation”, Handbook of Trustworthy Federated Learning, Springer, 2024, pp. 109–147, eBook ISBN: 978-3-031-58923-2. [pdf]

• Pravija Raj P V, Ashish Gupta, and Sajal K Das, “Investigating the Resilience of Federated Learning: Perspectives on Attacks and Defenses”, Federated Learning: Foundations and Applications, Elsevier, USA , 2025, pp. 171--191. [pdf]

• Andrea Augello, Priyesh Ranjan, Ashish Gupta, Federico Corò, Sajal K Das, and Giusseppe Lo Re, “Federated Learning Framework with Battery-Aware Clients”, Federated Learning: Foundations and Applications, Elsevier, USA , 2025, pp. 63--80. [pdf]

Open Dataset

• Ashish Gupta, Hari Prabhat Gupta, Tanima Dutta, Rahul Mishra, Ramakant Kumar,  “Accelerometer, Gyroscope, and Magnetometer Sensors based Data for Recognizing Handwritten Digits”, IEEE Dataport, 2020   [Link]