Publications
Prof. Balasubramanian Raman
For complete list of publications: click here

Refereed International Journal Papers: Q1 (JCR 2021)

1. Puneet Kumar and Balasubramanian Raman, A BERT Based Dual-Channel Explainable Text Emotion Recognition System, Neural Networks (Elsevier), Vol. 150, pp. 392-407, 2022

2. M. Tanveer, A.H. Rashid, Rahul Kumar and Balasubramanian Raman, Parkinson’s Disease Diagnosis with Deep and Shallow Neural Networks: Survey and Comprehensive Evaluation, Information Processing and Management (Elsevier), Vol. 59, No. 3, pp. 1-50, 102909, 2022

3. Nidhi Saxena and Balasubramanian Raman, Pansharpening scheme using bi-dimensional empirical mode decomposition and neural network, ACM Transactions on Multimedia Computing, Communications and Applications, Vol. 18, No. 4, pp. 1-22, 108, 2022

4. Himanshu Buckchase and Balasubramanian Raman, GraSP: Local Grassmannian Spatio - Temporal Patterns for Unsupervised Pose Sequence Recognition, ACM Transactions on Multimedia Computing, Communications and Applications, Vol. 18, No. 3, pp. 1-23, 79, 2022

5. Javed Imran and Balasubramanian Raman, Three-stream spatio-temporal attention network for first-person action and interaction recognition, Journal of Ambient Intelligence and Humanized Computing (Springer), Vol. 13, pp. 1137-1152, 2022

6. Ankur Gupta, Rahul Kumar, Harkirat Singh Arora and Balasubramanian Raman, C-CADZ: Computational Intelligence System for Coronary Artery Disease Detection Using Z-Alizadeh Sani Dataset, Applied Intelligence (Springer), Vol. 52, No. 3, pp. 2436-2464, 2022

7. Rahul Kumar, Ankur Gupta, Harkirat Singh Arora and Balasubramanian Raman, IBRDM: An Intelligent Framework for Brain Tumor Classification Using Radiomics-and DWT Based Fusion, ACM Transactions on Internet Technology, Vol. 22, No. 1, pp. 1-30, 9, 2022

8. Amitesh Singh Rajput and Balasubramanian Raman, Privacy-preserving distribution and access control of personalized healthcare data, IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2021.3138993, 2021

9. Himanshu Buckchase and Balasubramanian Raman, Towards Zero Shot Learning of Geometry of Motion Streams and Its Application to Anomaly Recognition, Expert Systems With Applications (Elsevier), Vol. 177, pp. 1-12, 114916, 2021

10. Amitesh Singh Rajput, Vishesh Kumar Tanwar and Balasubramanian Raman, Z-score based secure biomedical model for effective skin lesion segmentation over eHealth cloud, ACM Transactions on Multimedia Computing, Communications and Applications, Vol. 17, No. 2s, Article 65, 2021

11. Rahul Kumar, Balasubramanian Raman and Brajesh Kumar Kaushik, Efficient Method and Architecture for Real-Time Video Defogging, IEEE Transactions on Intelligent Transportation Systems, Vol. 22, No.10, pp. 6536-6546, 2021

12. Sahil Garg, Song Guo, Vincenzo Piuri, Kim-Kwang Raymond Choo and Balasubramanian Raman, Edge-Cloud Interplay Based on SDN and NFV for Next-Generation IoT Applications, IEEE Internet of Things Journal, Vol. 7, No. 7, pp. 5690-5694, 2020

13. Amitesh Rajput, Balasubramanian Raman and Javed Imran, Privacy-preserving human action recognition as a remote cloud service using RGB-D sensors and deep CNN, Expert Systems with Applications (Elsevier), Vol. 152, 113349, 2020

14. Vishesh Tanwar, Balasubramanian Raman, Amitesh Rajput and Rama Bhargava, CryptoLesion: A Privacy-preserving Model for Lesion Segmentation using Whale Optimization over Cloud, ACM Transactions on Multimedia Computing Communications and Applications, Vol. 16, No. 2, Article No.: 50, pp 1-23, 2020

15. Debanjan Sadhya, Kanjar De, Balasubramanian Raman and Partha Pratim Roy, Efficient Extraction of Consistent Bit Locations from Binarized Iris Features, Expert Systems with Applications (Elsevier), Vol. 140, 112884, 2020

Refereed International Conference Papers appear in Proceedings:

1. Anshul Pundhir, Saurabh Dadhich, Ananya Agarwal and Balasubramanian Raman, Towards Improved Skin Lesion Classification using Metadata Supervision, Accepted for publication in The 26th International Conference on Pattern Recognition (ICPR 2022), August 21-25, 2022, Montral Qubec, CANADA

2. Sarthak Malik, Puneet Kumar and Balasubramanian Raman, Towards Interpretable Facial Emotion Recognition, Proceedings of The 12th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP 2021), Article No.: 14, pp. 1-9, https://doi.org/10.1145/3490035.3490271, December 19-22, 2021, Jodhpur, INDIA

3. Rishabh Mamgain, Balasubramanian Raman and Ridhi Arora, Re-calibrated Attention-based Deep Learning Technique for Dermoscopic Lesion Segmentation, Accepted for publication in 9th International Conference on Pattern Recognition and Machine Intelligence (PReMI 2021), December 15 - 18, 2021, Kolkata, INDIA

4. Puneet Kumar, Vishesh Kaushik and Balasubramanian Raman, Towards the explainability of Multimodal Speech Emotion Recognition, Proceedings of Annual Conference of the International Speech Communication Association (Interspeech 2021), pp. 1748-1752, 30 August- 3 September 2021, Brno, CZECH REPUBLIC

5. Puneet Kumar, Vedanti Khokher, Yukti Gupta and Balasubramanian Raman, Hybrid Fusion Based Approach for Multimodal Emotion Recognition with Insufficient Labelled Data, Proceedings of the 28th IEEE International Conference on Image Processing (ICIP 2021), pp. 314-318, September 2021, Anchorage, Alaska, USA

6. Ridhi Arora and Balasubramanian Raman, A Deep Neural CNN Model with CRF for Breast Mass Segmentation in Mammograms, Proceedings of the 29th European Signal Processing Conference (EUSIPCO 2021), pp. 1311-1315, May 2021, Dublin, Ireland

7. Ankur Gupta, Harkirat Singh Arora, Rahul Kumar and Balasubramanian Raman, DMHZ : A Decision Support System based on Machine Computational Design for Heart Disease Diagnosis Using Z-Alizadeh Sani Dataset, Proceedings of the 35th International Conference on Information Networking (ICOIN 2021), pp. 818-823, 13-16, January 2021, Jeju Island, SOUTH KOREA

8. Rahul Kumar, Ankur Gupta, Harkirat Singh Arora and Balasubramanian Raman, GRGE: Detection of Gliomas Using Radiomics, GA Features and Extremely Randomized Trees, Proceedings of the 35th International Conference on Information Networking (ICOIN 2021), pp. 379-384, 13-16, January 2021, Jeju Island, SOUTH KOREA

9. Puneet Kumar, Sidharth Jain, Balasubramanian Raman, Partha Pratim Roy and Masakazu Iwamura, End-to-end Triplet Loss based Emotion Embedding System for Speech Emotion Recognition, Proceedings of the 25th International Conference on Pattern Recognition (ICPR 2020), pp. 8766-8773, 10-15, January 2021, Milan, ITALY

10. Himanshu Buckchash and Balasubramanian Raman, DuTriNet: Dual-Stream Triplet Siamese Network for Self-Supervised Action Recognition by Modeling Temporal Correlations, Proceedings of 32nd International Conference on Tools with Artificial Intelligence (ICTAI 2020), pp. 488-495, 9-11, November 2020, Virtual Conference

11. Himanshu Buckchash and Balasubramanian Raman, Human Motion Generation by Stochastic Conditioning of Deep Recurrent Networks on Pose Manifolds, Proceedings of International Conference on Image Processing (ICIP 2020), pp. 2406-2410, October 25-28, 2020, UAE

12. Javed Imran, Balasubramanian Raman and Amitesh Rajput, Robust, Efficient and PrivacyPreserving Violent Activity Recognition in Videos, Proceedings of The 35th ACM/ SIGAPP Symposium on Applied Computing (SAC 2020), pp. 2081-2088, March 30 - April 03, 2020, Brno, CZECH REPUBLIC

13. Nidhi Saxena, N. Kishore Babu and Balasubramanian Raman, Semantic Segmentation of Multispectral Images using Res-Seg-net Model, Proceedings of 14th IEEE International Conference on Semantic Computing (IEEE ICSC), pp. 154-157, February 3-5, 2020, San Diego, California, USA

14. Himanshu Buckchash and Balasubramanian Raman, Sustained Self-Supervised Pretraining for Temporal Order Verification, Proceedings of 8th International Conference on Pattern Recognition and Machine Intelligence (PReMI 2019), pp. 140-149, December 17-20, 2019, Tezpur, INDIA

15. Sanyam Rajpal, Debanjan Sadhya, Kanjar De, Partha Pratim Roy and Balasubramanian Raman, EAI-NET: Effective and Accurate Iris Segmentation Network, Proceedings of 8th International Conference on Pattern Recognition and Machine Intelligence (PReMI 2019), pp. 442-451, December 17-20, 2019, Tezpur, INDIA
Prof. Debiprasanna Sahoo
Publications (Journals):

1. Formal Modeling and Verification of a Victim DRAM Cache
ACM Transactions on Design Automation of Electronic Systems (TODAES), Vol-24(2), 2019
https://dl.acm.org/citation.cfm?id=3306491
Debiprasanna Sahoo, Swaraj Sha, Manoranjan Satpathy, Madhu Mutyam, S. Ramesh,Partha Roop

2. ReDRAM: A Reconfigurable DRAM Cache for GPGPUs
IEEE Computer Architecture Letter (CAL), vol-17, issue-2, 2018
https://ieeexplore.ieee.org/document/8437148/
Debiprasanna Sahoo, Swaraj Sha, Manoranjan Satpathy, Madhu Mutyam

3. Formal Modeling and Verification of Controllers for a Family of DRAM Caches
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol-37, issue-11, 2018 (It also appeared in CODES+ISSS, ESWEEK, 2018)
https://ieeexplore.ieee.org/document/8493587
Debiprasanna Sahoo, Swaraj Sha, Manoranjan Satpathy, Madhu Mutyam, S. Ramesh, Partha Roop.

Publications (Conference):

1. Post-Model Validation of Victim DRAM Caches
37th, International Conference on Computer Design (ICCD), IEEE, 2019
https://ieeexplore.ieee.org/document/8988756/
Debiprasanna Sahoo, Shivani Tripathy, Manoranjan Satpathy, Madhu Mutyam

2. CAMO: A Novel Cache Management Organization for GPGPUs
23rd, Asia and South Pacific Design Automation Conference (ASP-DAC), ACM, 2018
https://dl.acm.org/citation.cfm?id=3201652
Debiprasanna Sahoo, Swaraj Sha, Manoranjan Satpathy, Madhu Mutyam, Laxmi Narayan Bhuyan

3. An Experimental Study on Dynamic Bank Partitioning of DRAM in Chip Multiprocessors
30th, International Conference on VLSI Design (VLSID), IEEE, 2017
http://ieeexplore.ieee.org/document/7884754/
Debiprasanna Sahoo, Manoranjan Satpathy, Madhu Mutyam

4. MSimDRAM: Formal Model Driven Development of DRAM Simulator
29th, International Conference on VLSI Design (VLSID), IEEE, 2016
http://ieeexplore.ieee.org/document/7435034/
Debiprasanna Sahoo, Manoranjan Satpathy

Publications (Co-Authored):

1. Slumber: Static Power Management for GPGPU Register Files
25th, International Symposium on Low Power Electronics and Design, ACM, 2020
https://dl.acm.org/doi/abs/10.1145/3370748.3406577
Devashree Tripathy, H.Z. Sabzi, Debiprasanna Sahoo, Manoranjan Satpathy, Laxmi Narayan Bhuyan

2. Fuzzy Fairness Controller for NVMe SSDs
34th, International Conference on Supercomputing (ICS), IEEE, 2020
https://dl.acm.org/doi/abs/10.1145/3392717.3392766
Shivani Tripathy, Debiprasanna Sahoo, Manoranjan Satpathy, Madhu Mutyam

3. Formal Modeling and Verification of of NAND Flash Memory
37th, International Conference on Computer Design (ICCD), IEEE, 2019
https://ieeexplore.ieee.org/iel7/8970097/8988587/08988731.pdf
Shivani Tripathy, Debiprasanna Sahoo, Manoranjan Satpathy, Srinivas Pinisetty

4. Multidimensional Grid Aware Address Prediction for GPGPU
32nd, International Conference on VLSI Design (VLSID), IEEE, 2019
https://ieeexplore.ieee.org/document/8711244
Shivani Tripathy, Debiprasanna Sahoo, Manoranjan Satpathy

5. Locking Lines in Tag Cache to Improve Access Optimization for DRAM Caches
International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (CASES), ESWEEK, IEEE, 2018
https://dl.acm.org/citation.cfm?id=3283564
Shivani Tripathy, Debiprasanna Sahoo, Manoranjan Satpathy
Prof. Durga Toshniwal
Papers:

1. Shalini Jangra and Durga Toshniwal. "Efficient algorithms for victim item selection in privacy-preserving utility mining." Future Generation Computer Systems 128 (2022): 219-234.

2. Narayan Chaturvedi, Durga Toshniwal, and Manoranjan Parida. "Combinatorial Approach of Feature Generation for Traffic Event Detection using Social Media Data: CFGA." (2021).

3. Shivani Sharma and Durga Toshniwal. "MR-OVnTSA: a heuristics based sensitive pattern hiding approach for big data." Applied Intelligence 50, no. 12 (2020): 4241-4260.

4. Jatin Bedi and Durga Toshniwal. "Data Decomposition Based Learning for Load Time-Series Forecasting." In Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 62-74. Springer, Cham, 2020.

5. Shalini Jangra and Durga Toshniwal. "VIDPSO: victim item deletion based PSO inspired sensitive pattern hiding algorithm for dense datasets." Information Processing & Management 57, no. 5 (2020): 102255
Prof. Manoj Misra
Publications (Journals)

1. Varshney G., Misra M., and Atrey P., 2018. Secure authentication scheme to thwart RT MITM, CR MITM and malicious browser extension based phishing attacks. Journal of Information Security and Applications, 42, pp. 1-17.

2. Varshney G., Misra M., and Atrey P.K., 2016. A phish detector using lightweight search features. Computers & Security, 62, pp.213-228.

3. Gupta G.P., Misra M. and Garg K., 2017. Towards scalable and load-balanced mobile agents-based data aggregation for wireless sensor networks. Computer & Electrical Engineering, 64, pp.262-276.



Publications (Conferences):

1. A.K. Yadav, M. Misra, M. Liyanage and G. Varshney, "Secure and User Efficient EAP based Authentication Protocol for IEEE 802.11 Wireless LANs," 2020 IEEE 17th International Conference on Mobile Ad Hoc and Sensor Systems (MASS), 2020, pp. 576-584, doi:10.1109/MASS50613.2020.00076. (Rank: Core-B).

2. Yadav A.K., Misra M., Pandey P.K., Kaur K., Garg S. and Liyanage M., LEMAP: A Lightweight EAP based Mutual Authentication Protocol for IEEE 802.11 WLAN. In 2022, IEEE International Conference on Communication (ICC) (Rank: Qualis-A2)

3. Shukla S., Misra M., and Varshney G., 2020, November. Identification of spoofed emails by applying email forensics and memory forensics. In 2020 the 10th international Conference on Communication and Network Security (pp. 109-114).

4. Arora V. and Misra M., 2020 September. A Novel Machine Learning Methodology for Detecting Phishing Attacks in Real Time. In International Workshop on Security and Trust Management (pp. 39-54). Springer, Cham.

5. Varshney G., Iyer P., Atrey P. and Misra M., 2021, January. Evading DoH via Live Memory Forensics for Phishing Detection and Content Filtering. In 2021 International Conference on COMmunication Systems & NETworkS (COMSNETS) (pp. 1-4). IEEE.
Prof. Neetesh Kumar
Publications (Journals)

1. Rajni Jindal, Neetesh Kumar and and Sanjay Patidar, "IoT Streamed Data Handling Model using Delta Encoding", in International Journal of Communication Systems, Wiley, In press, Accepted May 2022.

2. Dinesh Soni, Neetesh Kumar, "Machine Learning Techniques in Emerging Cloud Computing Integrated Paradigms: A Survey and Taxonomy", in Journal of Network and Computer Applications, Elsevier, In press, Accepted May 2022.

3. Neetesh Kumar , Rashmi Chaudhry, O.P. katwariya , N. Kumar, “ChaseMe: A Heuristic Scheme for Electric Vehicles Mobility Management on Charging Stations in a Smart City Scenario”, in IEEE Transactions on Intelligent Transportation System, In press, Accepted Feb 2022.

4. Pooja Mishra, Neetesh Kumar, and W. W. Wilfred Godfrey, An Evolutionary Computing based Energy-efficient Solution for IoT-enabled Software-Defined Sensor Network Architecture”, in International Journal of Communication Systems, Wiley, Jan, 2022. DOI : 10.1002/dac.5111.

5. Rashmi Chaudhry, Neetesh Kumar “ A Multi-objective Meta-heuristic Solution for Green Computing in Software-Defined Wireless Sensor Networks ", IEEE Transactions on Green Communications and Networking. DOI : 10.1109/TGCN.2021.3122078

6. Neetesh Kumar , Sarthak Mittal, Vaibhav Garg, Neeraj Kumar, “ Deep Reinforcement Learning-Based Traffic Light Scheduling Framework for SDN-Enabled Smart Transportation System ", IEEE Transactions on Intelligent Transportation System. DOI : 10.1109/TITS.2021.3095161.

7. Neetesh Kumar , Deo Prakash Vidyarthi, “ A novel energy-efficient scheduling model for multi-core systems " Cluster Computing. DOI : 10.1007/s10586-020-03143-w.

8. Neetesh Kumar , Deo Prakash Vidyarthi, Rajkumar Buyya “ Fog-Integrated Cloud Architecture enabled multi-attribute combinatorial reverse auctioning framework " Simulation Modelling Practice and Theory DOI: 10.1016/j.simpat.2021.102307.

9. Neetesh Kumar , Navjot Singh, Deo Prakash Vidyarthi “ Artificial lizard search optimization (ALSO): a novel nature-inspired meta-heuristic algorithm " Soft Computing DOI : 0.1007/s00500-021-05606-7.

10. Neetesh Kumar , Rashmi Chaudhry, O.P. katwariya, “Green Communication in Software Defined Social Internet of Vehicles, IEEE Transactions on Intelligent Transportation System. DOI: 10.1109/TITS.2020.3028695.

11. Neetesh Kumar , S. Rahman and Naveen Dhakad, “Fuzzy Inference Enabled Deep Reinforcement Learning based Traffic Light Control for Intelligent Transportation System” IEEE Transactions on Intelligent Transportation System (ITS) DOI: 10.1109/JSEN.2018.2869629.

12. Neetesh Kumar , D.P. Vidhyarthi (2018), “A Green Routing Algorithm for IoT enabled Software Defined Wireless Sensor Network " IEEE Sensors journal, 18(22), 9449-9460 DOI: 10.1109/JSEN.2018.2869629 . notified by IEEE council in the list of world’s top 15 most downloaded articles in the month of Oct-Nov 2018.

13. Rashmi Chaudhry, Shashikala Tapaswi, Neetesh Kumar , “A Green Multicast Routing Algorithm for Smart Sensor Networks in Disaster Management ” IEEE Transactions on Green Communications and Networking . DOI: 10.1109/TGCN.2019.2891752.

14. Neetesh Kumar , D.P. Vidhyarthi (2017), “An Energy Aware Cost-Effective Scheduling Framework for Heterogeneous Cluster System”, in Elsevier, Future Generation Computer Systems 71, 73–88, DOI: 10.1016/j.future.2017.01.015.

15. Rashmi Chaudhry, Shashikala Tapaswi, Neetesh Kumar "Forwarding zone enabled Many-objective Particle Swarm Optimization for Multicast Routing Problem", (2019)Information Sciences, Elsevier. DOI: 10.1016/j.ins.2019.05.002.

16. Neetesh Kumar , D.P. Vidhyarthi, “A green SLA constrained scheduling algorithm for parallel/scientific applications in heterogeneous cluster systems”, in Journal of Sustainable Computing, Elsevier, 22 (2019) 107–119. DOI: 10.1016/j.suscom.2019.02.001.

17. Asif ali laghari, Hui He, Asiya Khan, Neetesh Kumar , Kharel, Rupak (2018), “QoC: Quality of Experience (QoE) Framework for Cloud Computing”, IEEE Access, 6, 64876-64890. DOI: 10.1109/ACCESS.2018.2865967.

18. Neetesh Kumar , D.P. Vidhyarthi (2018), “GA Inspired Hybrid Heuristic for Load Balancing on Multi-Core Many/core Systems” in the Computer Journal Oxford Press. DOI: 10.1093/comjnl/bxy085.

19. Rashmi Chaudhry, Shashikala Tapaswi, Neetesh Kumar (2018), "Forwarding Zone enabled PSO routing with Network lifetime maximization in MANET", in Applied Intelligence, Springer, 1-28. DOI: 10.1007/s10489-017-1127-5.

20. Neetesh Kumar , D.P. Vidhyarthi (2017), “A GA based energy aware scheduler for DVFS enabled multicore systems,” in Computing, Springer. Computing, 99(10), 955-977 . DOI: 10.1007/s00607-017-0540-2.

21. Neetesh Kumar , D.P. Vidhyarthi (2016), “A Model for Resource Constrained Project Scheduling using Adaptive-PSO,” in Soft Computing, Springer , 20(4), 1565–1580, DOI: 10.1007/s00500-015-1606-8 .

22. Neetesh Kumar, D.P. Vidhyarthi (2016), “A novel hybrid PSO–GA meta-heuristic for scheduling of DAG with communication on multiprocessor systems,” in Engineering with Computers , Springer, 32(1), 35-47. . DOI: 10.1007/s00366-015-0396-z.

23. Neetesh Kumar , D.P. Vidhyarthi (2014), “Improved Scheduler for Multi-Core Many –Core Systems,” in Journal of Computing. Springer . Computing 96(11), 1087–1110. DOI: 10.1007/s00607-014-0420-y.



Publications (Conferences)

1. Vaibhav Garg, Anuj Sachan, Neetesh Kumar, Sarthak Mittal, “ Congestion Control utilizing Software Defined Control Architecture at the Traffic Light Intersection " IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS) (2021) (Published)

2. Anuj Sachan, Neetesh Kumar “ Intelligent Traffic Control System for Emergency Vehicles " International Conference on Wireless Sensor Networks, Ubiquitous Computing and Applications 2021 (ICWSNUCA-2021) (Published)

3. Pooja Mishra , W Wilfred Godfrey, Neetesh Kumar “ A Green Computing-based Algorithm in Software Defined Network with Enhanced Performance " 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (Published)

4. Pooja Mishra , Neetesh Kumar , W Wilfred Godfrey, “ A hybrid Meta-heuristic solution for Energy-Efficient routing in Software-Defined Wireless Sensor Network " (Published)

5. Pooja Mishra , Neetesh Kumar , W Wilfred Godfrey, " A Meta-heuristic-based Green-routing Algorithm in Software-Defined Wireless Sensor Network " 2021 6th International Conference on Inventive Computation Technologies (ICICT) (Published)

6. Aishwarya Karmarkar, Prasenjit Chanak and Neetesh Kumar , " An optimized SVM based Fault Diagnosis Scheme for Wireless Sensor Networks ", SCEECS-2020: 2020 IEEE International Students' Conference on Electrical, Electronics and Computer Science, MANIT Bhopal, India, Feb-2020. (Published)

7. Sanjay Patidar, Rajni Jindal, and Neetesh Kumar , " Streamed Covid-19 Data Analysis using LSTM a Deep Learning Technique " , SocPros 2020, IIT Indore, (Published) Honor: Best Paper Award at SocProS 2020.

8. R. Jindal, Neetesh Kumar , S. Patidar, " IoT stream data compression using LDPC coding ", International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2020), January 4 -5, 2020. (Published)

9. Rajni Zindal, Neetesh Kumar and Hitesh Nirwan, " MTFCT: A task offloading approach for fog computing and cloud computing ", IEEE Confluence-2020:10th International Conference Amity Noida. (Published)

10. Swarup Padhy, Juhi Tiwari, Shivam Rathore and Neetesh Kumar , " Emergency Signal Classification for the Hearing Impaired using Multi-channel ", IEEE CICT 2019, IIIT Allahabad. (Published) Honor: Best Paper Award at IEEE CICT 2019.

11. Pratyush Ranjan, Shubhanker Srivastava, Vidit Gupta, Shashikala Tapaswi and Neetesh Kumar ," Decentralized and Distributed System for Organ/Tissue Donation ", CICT 2019, IIIT Allahabad. (Published)

12. Neetesh Kumar and S. Rahman, " Deep Reinforcement Learning with Vehicle Heterogeneity based Traffic Light Control for Intelligent Transportation System ", in 2nd IEEE International Conference on Industrial Internet (ICII-2019), Orlando, Florida, USA. (Published)

13. Anuj Sachan and Neetesh Kumar ," Light Weighted Mutual Authentication and Dynamic Key Encryption for IoT Devices Applications ", 2019 international conference on Issues and challenges in Intelligent Computing, Ghaziabad India. (Published)

14. Rashika Bangroo, Neetesh Kumar , Reya Sharma, " A Model for Multi-Processor Task Scheduling Problem using Quantum Genetic Algorithm, Hybrid Intelligent Systems ", 2018. (Published)

15. Reya Sharma, Rashika Bangroo, Manoj Kumar and Neetesh Kumar ," A Model for Resource Constraint Project Scheduling Problem using Quantum inspired PSO ", Next Generation Computing Technologies (NGCT 2017). (Published)

16. Y. Lu, L. Yang, V. C. Bhavsar, Neetesh Kumar ," Tree structured data processing on GPUs ", in: 7th IEEE International Conference on Cloud Computing, Data Science and Engineering Confluence, 2017, pp. 504–511. doi:978- 1-5090-3519-9/17. (Published)

17. Neetesh Kumar , Chandresh Kumar Maurya, "DR: A Novel and Practical Non-Comparison Based Sorting Algorithm ", Poster presentation at Research Colloquia in XRCI Open 2016. Honor: Travel Grant Awarded with IEEE IPDPS International

18. Neetesh Kumar , D.P. Vidhyarthi, " Improved Scheduler for Multi-Core Many–Core Systems ", Poster, in 29-th International Symposium on Parallel and Distributed Computing (IPDPS 2015) (Published) Honor: Travel Grant Awarded with IEEE IPDPS International Society.

19. Pooja Mishra, W. W. Wilfred Godfrey and Neetesh Kumar ," A Meta-heuristic-based Green Routing Algorithm In Software Defined Wireless Sensors Network ", ICICT 2021. (Presented). 120-22 Jan 2021.

Prof. Partha Pratim Roy
Publications (Journals):

1. M. Madhiarasan, P.P. Roy , Hybrid Transformer Network for Different Horizons-based Enriched Wind Speed Forecasting, arXiv preprint arXiv:2204.09019

2. M. Madhiarasan, P.P. Roy , A Comprehensive Review of Sign Language Recognition: Different Types, Modalities, and Datasets, arXiv preprint arXiv:2204.03328

3. T. Rangari, S. Kumar, P.P. Roy, D.P. Dogra, B.G. Kim , Video based exercise recognition and correct pose detection, Multimedia Tools and Applications, 1-16

4. D.D. Chakladar, S. Datta, P.P. Roy, A.P. Vinod , Cognitive Workload Estimation Using Variational Auto Encoder & Attention-based Deep Model, IEEE Transactions on Cognitive and Developmental Systems [In Press]

5. G. Siddhad, A. Gupta, D.P. Dogra, P.P. Roy , Efficacy of Transformer Networks for Classification of Raw EEG Data, arXiv preprint arXiv:2202.05170

6. S. Behera, D.P. Dogra, M.K. Bandyopadhyay, P.P. Roy, Crowd Characterization in Surveillance Videos Using Deep-Graph Convolutional Neural Network, IEEE Transactions on Cybernetics [In Press]

7. J. Manhas, R.K. Gupta, P.P. Roy, A Review on Automated Cancer Detection in Medical Images using Machine Learning and Deep Learning based Computational Techniques: Challenges and Opportunities, Archives of Computational Methods in Engineering, 1- 41

8. S. Behera, D.P. Dogra, M.K. Bandyopadhyay, P.P. Roy, Understanding crowd flow patterns using active-Langevin model, Pattern Recognition 119, 108037

9. M. Madhiarasan, M. Louzazni, P.P. Roy, Novel Cooperative Multi-Input Multilayer Perceptron Neural Network Performance Analysis with Application of Solar Irradiance Forecasting, International Journal of Photoenergy 2021

10. A. Gupta, P.P. Roy, V. Dutt, Evaluation of Instance-Based Learning and Q-Learning Algorithms in Dynamic Environments, IEEE Access 9, 138775-138790

11. R. Saini, P. Kumar, P. P. Roy, U. Pal, Modeling local and global behavior for trajectory classification using graph-based algorithm, in Pattern Recognition Letters, 2021

12. D.D. Chakladar, P. Kumar, S. Mandal, P.P. Roy, M. Iwamura, B.G. Kim, 3D Avatar Approach for Continuous Sign Movement Using Speech/Text, Applied Sciences 11 (8), 3439

13. A. Pathak, S. Kumar, P.P. Roy, B.G. Kim, Aspect-Based Sentiment Analysis in Hindi Language by Ensembling Pre-Trained mBERT Models, Electronics 10 (21), 2641

14. A. Gupta, G. Siddhad, V. Pandey, P.P. Roy, B.G. Kim, Subject-Specific Cognitive Workload Classification Using EEG-Based Functional Connectivity and Deep Learning, Sensors 21 (20), 6710

15. D. D. Chakladar, P. P. Roy and M. Iwamura, EEG-Based Cognitive State Classification and Analysis of Brain Dynamics Using Deep Ensemble Model and Graphical Brain Network, in IEEE Transactions on Cognitive and Developmental Systems, 2021

16. K. K. Santhosh, D. P. Dogra, P. P. Roy, A. Mitra, Vehicular Trajectory Classification and Traffic Anomaly Detection in Videos Using a Hybrid CNN-VAE Architecture, IEEE Transactions on Intelligent Transportation Systems, 2021

17. P. Keserwani, P. P. Roy, Text Region Conditional Generative Adversarial Network for Text Concealment in the Wild, IEEE Transactions on Circuits and Systems for Video Technology, 2021

18. Y.-J. Heo, B. G. Kim, P. P. Roy, Frontal Face Generation Algorithm from Multi-view Images based on Generative Adversarial Network, Journal of Multimedia Information System, 2021

19. K. K. Santhosh, D. P. Dogra, A. Mitra, P. P. Roy, Vehicular Trajectory Classification and Traffic Anomaly Detection in Videos Using a Hybrid CNN-VAE Architecture, IEEE Transactions on Intelligent Transportation Systems, 2021

20. S. Behera, D. P. Dogra, M. K. Bandyopadhyay, P. P. Roy, Understanding Crowd Flow Patterns Using Active-Langevin Model, Pattern Recognition, 2021

21. A. Ahmed, R. Pal, D. P. Dogra, S. Kar, P. P. Roy and D. K. Prasad, Topic-based Video Analysis: A Survey, ACM Computing Surveys, 2021

22. V. Khurana, P. Kumar, P. P. Roy and D. P. Dogra, E. Scheme and M. Soleymani, A Survey on Neuromarketing using EEG Signals, IEEE Transactions on Cognitive and Developmental Systems, 2021

23. P. Keserwani, A. Dhankhar, R. Saini, and P. P. Roy, Quadbox: Quadrilateral Bounding Box Based Scene Text Detection Using Vector Regression, IEEE Access, 2021

24. S. K. Behera, P. Kumar, D. P. Dogra, and P. P. Roy, A Robust Biometric Authentication System for Handheld Electronic Devices by Intelligently Combining 3D Finger Motions and Cerebral Responses, IEEE Transactions on Consumer Electronics, 2021

25. P. P. Roy, P. Kumar and B.-G. Kim, An efficient Sign Language Recognition (SLR) System using Camshift Tracker and Hidden Markov Model (HMM), SN Computer Science, 2021

26. S. Ghosh, S. Ghosh, P. Kumar, E. Scheme and P. P. Roy, A Novel Spatio-Temporal Siamese Network for 3D Signature Recognition, Pattern Recognition Letters, 2021

27. D. D. Chakladar, P. Kumar, P. P. Roy, D. P. Dogra, E. Scheme and V. Chang, A multimodal-Siamese Neural Network (mSNN) for Person Verification using Signatures and EEG, Information Fusion, 2021

28. P. P. Roy, P. Kumar, S. Patidar and R. Saini, 3D Word Spotting using Leap Motion Sensor, Multimedia Tools and Applications, 2020.

29. L.-N. Wang, W. Liu, G. Zhong, P. P. Roy, J. Dong and K. Huang, Compressing Deep Networks by Neurons Agglomerative Clustering, Sensors, 2020

30. M. Chhetri, S. Kumar, P. P. Roy and B.-G. Kim, Deep BLSTM-GRU Model For Monthly Rainfall Prediction A case study of Simtokha, Bhutan, Remote Sensing, vol. 12, pp. 3174, 2020

31. G. Kumar, P. Keserwani, P. P. Roy and D. P. Dogra, "Logo detection using weakly supervised saliency map", Multimedia Tools and Applications, 2020

32. K. K. Santhosh, D. P. Dogra and P. P. Roy "Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey", ACM Computing Surveys, 2020

33. A. Sharma, P. Kumar, V. Maddukuri, N. Madamshetti, K. Kg, S. S. S. Kavuru, R. Balasubramanian and P. P. Roy, "Fast Griffin Lim based Waveform Generation Strategy for Text-to-Speech Synthesis", Multimedia Tools and Applications, 2020

34. S. Kumar, K. De and P. P. Roy, "Movie Recommendation System using Sentiment Analysis from Microblogging Data", IEEE Transactions on Computational Social Systems, vol. 7(4), pp. 915-923, 2020

35. A. Ahmed, D. P. Dogra, S. Kar, P. P. Roy and D. K. Prasad, "Can we automate diagrammatic reasoning?", Pattern Recognition, vol. 106, pp. 107412, 2020

36. D. D. Chakladar, S. Dey, P. P. Roy and D. P. Dogra. "EEG-based Mental Workload Estimation Using Deep BLSTM-LSTM Network and Evolutionary Algorithm", Biomedical Signal Processing and Control, vol. 60, pp. 101989, 2020

37. A. Ahmed, D. P. Dogra, S. Kar, P. P. Roy and D. Prasad. "ELM-HTM Guided Bio-inspired Unsupervised Learning for Anomalous Trajectory Classification", Cognitive Systems Research, vol. 63, pp. 30-41, 2020

38. S. Gupta, P. P. Roy, D. P. Dogra and B.-G. Kim, "Retrieval of colour and texture images using local directional peak valley binary pattern", Pattern Analysis and Applications, 2020

39. A. Ahmed, D. P. Dogra, S. Kar and P.P. Roy, "Video trajectory analysis using unsupervised clustering and multi-criteria ranking", Soft Computing, 2020

40. S. Behera, D. P. Dogra, M. K. Bandyopadhyay and P. P. Roy, "Estimation of Linear Motion in Dense Crowd Videos using Langevin Model", Expert Systems With Applications, vol. 150, pp. 113333, 2020

41. P. P. Roy, P. Kumar and V. Chang, "A Hybrid Classifier combination for Home Automation using EEG Signals", Neural Computing and Applications, 2020

42. S. Kumar, M. Gahalawat, P. P. Roy, D. P. Dogra and B.-G. Kim, "Exploring impact of Age and Gender on Sentiment Analysis using Machine Learning", Electronics, vol. 9(2), pp. 374, 2020

43. S. Ghose, A. Das, A. K. Bhunia and P. P. Roy, "Fractional Local Neighborhood Intensity Pattern for Image Retrieval using Genetic Algorithm", Multimedia Tools and Applications, vol. 79, pp. 18527–18552, 2020

44. B. Kaur, D. Singh and P. P. Roy, "A Study of EEG for Enterprise Multimedia Security", Multimedia Tools and Applications, vol. 79, pp. 10805–10823, 2020



Publications (Conference):

1. P. Kumar, S. Jain, R. Balasubramanian, P. P. Roy, and M. Iwamura, End-to-end Triplet Loss based Emotion Embedding System for Speech Emotion Recognition, International Conference on Pattern Recognition (ICPR), Italy, pp. 8766-8773, 2020.

2. D. D. Chakladar, S. Dey, P. P. Roy and M. Iwamura, EEG-Based Cognitive State Assessment Using Deep Ensemble Model and Filter Bank Common Spatial Pattern, International Conference on Pattern Recognition (ICPR), Italy, pp. 4107-4114, 2020

3. A. Kumar, S. Ghose, P. N. Chowdhury, P. P. Roy and U. Pal, UDBNET: Unsupervised Document Binarization Network via Adversarial Game, International Conference on Pattern Recognition (ICPR), Italy, pp. 7817-7824, 2020

4. S. Ghose, P. N. Chowdhury, P. P. Roy and U. Pal, Modeling Extent-of-Texture Information for Ground Terrain Recognition, International Conference on Pattern Recognition (ICPR), Italy, pp. 4766-4773, 2020

5. S. Behera, D. P. Dogra, M. K. Bandyopadhyay and P. P. Roy, "Segmentation and Visualization of Crowd Flows in Videos using Hybrid Force Model". VISIGRAPP, pp. 861-867, 2020

6. R. Saini, P. Kumar, S. Patidar, P. P. Roy and M. Liwicki, "Trilingual 3D Script Identication and Recognition using Leap Motion Sensor". WML@ICDAR, pp. 24-28, 2019

7. S. Sahoo, P. Kumar, R. Balasubramanian and P. P. Roy, "A Segment Level Approach to Speech Emotion Recognition using Transfer Learning", Asian Conference on Pattern Recognition (ACPR), New Zealand, pp. 435-448, 2019

8. J. Jaiswal, A. Chaubey, B. S. K. Reddy, S. Kashyap, P. Kumar, R. Balasubramanian and P. P. Roy, "A Generative Adversarial Network based Ensemble Technique for Automatic Evaluation of Machine Synthesized Speech", Asian Conference on Pattern Recognition (ACPR), New Zealand, pp. 580-593, 2019

9. S. Rajpal, D. Sadhya, K. De, P. P. Roy and R. Balasubramanian, "EAI-NET: Effective and Accurate Iris Segmentation Network", International Conference on Pattern Recognition and Machine Intelligence (PReMI), India, pp. 442-451, 2019

10. P. Keserwani, K. De, P. P. Roy and U. Pal, "Zero Shot Learning Based Script Identification in the wild", International Conference on Document Analysis and Recognition (ICDAR), Australia, 2019

11. A. K. Bhunia, A. K. Bhunia, A. Sain and P. P. Roy, "Improving document binarization via adversarial noise-texture augmentation", IEEE International Conference on Image Processing (ICIP), Taiwan, pp. 2721-2725, 2019

12. P. Mukherjee, A. Das, A. K. Bhunia and P. P. Roy, "Cogni-Net: Cognitive feature learning through deep visual perception", IEEE International Conference on Image Processing (ICIP), Taiwan, pp. 4539-4543 , 2019

13. A. K. Bhunia, A. Das, A. K. Bhunia, S. R. K. Perla and P. P. Roy, "Handwriting Recognition in Low-resource Scripts using Adversarial Learning", Conference on Computer Vision and Pattern Recognition (CVPR), USA, pp.4767-4776, 2019

14. S. Mukherjee, S. Ghosh, S. Ghosh, P. Kumar and P. P. Roy, "Predicting Video-frames using encoder-convLSTM combination", International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2027-2031 , 2019

15. S. Nag, A. K. Bhunia, A. Konwer and P. P. Roy, "Facial Micro-expression Spotting and Recognition using Time Contrasted Feature with Visual Memory", International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2022-2026 , 2019

16. S. R. K. Perla, A. K. Bhunia, S. Ghose and P. P. Roy, "User Constrained Thumbnail Generation using Adaptive Convolutions", International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 1677-1681 , 2019

17. A. K. Bhunia, S. R. K. Perla, P. Mukherjee, A. Das and P. P. Roy, "Texture Synthesis Guided Deep Hashing for Texture Image Retrieval", Winter Conference on Applications of Computer Vision (WACV), USA, pp. 609-618 , 2019

18. S. Halder, K. De and P. P. Roy, "Perceptual Conditional Generative Adversarial Networks for End-to-End Image Colourization", Asian Conference on Computer Vision (ACCV), Australia, pp. 269-283, 2018

19. S. K. Behera, A. K. Dash, D. P. Dogra and P. P. Roy, "Air Signature Recognition Using Deep Convolutional Neural Network-Based Sequential Model", International Conference on Pattern Recognition (ICPR), China, pp. 3525-3530, 2018
Prof. Pradumn Kumar Pandey
Publications (Journals):

1. Gangwal, U., Singh, M., Pandey, P. K., Kamboj, D., Chatterjee, S., & Bhatia, U. (2022). Identifying early-warning indicators of onset of sudden collapse in networked infrastructure systems against sequential disruptions. Physica A: Statistical Mechanics and its Applications, 591, 126796

2. Pandey, P. K., & Singh, R. (2021). Fast Average-consensus on Networks using Heterogeneous Diffusion. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(11), 3421-3425

3. Pandey, P. K., & Singh, M. (2020). Quantifying nonrandomness in evolving networks. IEEE Transactions on Computational Social Systems, 7(6), 1447-1459

4. Pandey, P. K., Adhikari, B., Mazumdar, M., & Ganguly, N. (2020). Modeling signed networks as 2-layer growing networks. IEEE Transactions on Knowledge and Data Engineering

5. Pandey, P. K., Singh, M., Goyal, P., Mukherjee, A., & Chakrabarti, S. (2020). Analysis of reference and citation copying in evolving bibliographic networks. Journal of Informetrics, 14(1), 101003

6. Pandey, P. K., & Badarla, V. (2019). Small-world regular networks for communication. IEEE Transactions on Circuits and Systems II: Express Briefs, 67(8), 1409-1413

7. Pandey, P. K., Adhikari, B., & Chakraborty, S. (2019). A diffusion protocol for detection of link failure and utilization of resources in multi-agent systems. IEEE Transactions on Network Science and Engineering, 7(3), 1493-1507

8. Pandey, P. K., Bhattacharya, S., & Ganguly, N. (2019, January). Non-link Preserving Network Embedding using Subspace Learning for Network Reconstruction. In Proceedings of the ACM India Joint International Conference on Data Science and Management of Data (pp. 10-17)

9. Pandey, P. K., & Singh, M. (2019). MSP-N: Multiple selection procedure with ‘N’ possible growth mechanisms. Plos one, 14(12), e0224383

10. Pandey, P. K., Adhikari, B., & Chakraborty, J. (2018). Interpreting nucleation as a network formation process. Journal of Mathematical Chemistry, 56(5), 1467-1480

11. Pandey, P. K., & Badarla, V. (2018). Reconstruction of network topology using status-time-series data. Physica A: Statistical Mechanics and its Applications, 490, 573-583

12. Pandey, P. K., & Adhikari, B. (2017). A parametric model approach for structural reconstruction of scale-free networks. IEEE Transactions on Knowledge and Data Engineering, 29(10), 2072-2085

13. Pandey, P. K. (2017, June). Network Representation Learning Using Local Sharing and Distributed Matrix Factorization (LSDMF). In Dynamics on and of Complex Networks (pp. 169-181). Springer, Cham

14. Pandey, P. K., & Adhikari, B. (2015). Context dependent preferential attachment model for complex networks. Physica A: Statistical Mechanics and its Applications, 436, 499-508

Publications (Conferences)

1. Pandey, P. K., Adhikari, B., & Gupta, R. (2015, January). Measuring diversity of network models using distorted information diffusion process. In 2015 7th International Conference on Communication Systems and Networks (COMSNETS) (pp. 1-4). IEEE

2. Yadav, A.K., Misra, M., Pandey, P.K., Kaur, K., Garg, S. and Liyanage, M., LEMAP: A Lightweight EAP based Mutual Authentication Protocol for IEEE 802.11 WLAN. In 2022, IEEE International Conference on Communication (ICC) (Rank: Qualis-A2)
Prof. Pravendra Singh
Journals

1. HetConv: Beyond Homogeneous Convolution Kernels for Deep CNNs, Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri, International Journal of Computer Vision (IJCV), 2019.

2. FALF ConvNets: Fatuous Auxiliary Loss based Filter-pruning for Efficient Deep CNNs, Pravendra Singh, Vinay Sameer Raja Kadi, Vinay P. Namboodiri, Image and Vision Computing (IVC), 2019.

3. EDS Pooling Layer, Pravendra Singh, Prem Raj, Vinay P. Namboodiri, Image and Vision Computing (IVC), 2020.

4. GIFSL - Grafting based Improved Few-Shot Learning, Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri, Image and Vision Computing (IVC), 2020.

5. Acceleration of Deep Convolutional Neural Networks using Adaptive Filter Pruning, Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri, IEEE Journal of Selected Topics in Signal Processing (JSTSP), 2020.

6. Calibrating Feature Maps for Deep CNNs, Pravendra Singh, Pratik Mazumder, Mohammed Asad Karim, Vinay P. Namboodiri, Neurocomputing (NEUCOM), 2021.

7. Optimizing nonlinear activation function for convolutional neural networks, Munender Varshney, Pravendra Singh, Signal, Image and Video Processing (SIVP), 2021.

8. Context Extraction Module for Deep Convolutional Neural Networks, Pravendra Singh, Pratik Mazumder, Vinay P. Namboodiri, Pattern Recognition (PR), 2021.

9. Dual class representation learning for few-shot image classification, Pravendra Singh, Pratik Mazumder, Knowledge-Based Systems (KNOSYS), 2022.

10. On Restoration Of Degraded Fingerprints, Indu Joshi, Ayush Utkarsh, Pravendra Singh, Antitza Dantcheva, Sumantra Dutta Roy, Prem Kumar Kalra, Multimedia Tools and Applications (MTAP), 2022.

11. Protected Attribute Guided Representation Learning for Bias Mitigation in Limited Data, Pravendra Singh
, Pratik Mazumder, Knowledge-Based Systems (KNOSYS), 2022.

12. Few-Shot Image Classification with Composite Rotation based Self-Supervised Auxiliary Task, Pravendra Singh
, Pratik Mazumder, Vinay P. Namboodiri, Neurocomputing (NEUCOM), 2022.

Conference

1. Fair Visual Recognition in Limited Data Regime using Self-Supervision and Self-Distillation, Pravendra Singh
, Pratik Mazumder, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA, 2022.

2. Knowledge Consolidation based Class Incremental Online Learning with Limited Data, Mohammed Asad Karim, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai, International Joint Conference on Artificial Intelligence (IJCAI), Virtual Conference, 2021.

3. Rectification-based Knowledge Retention for Continual Learning, Pravendra Singh
, Pratik Mazumder, Piyush Rai, Vinay P. Namboodiri, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Virtual Conference, 2021. 4. Few-Shot Lifelong Learning, Pravendra Singh, Pratik Mazumder, Piyush Rai, AAAI Conference on Artificial Intelligence (AAAI), Virtual Conference, 2021. 5. Improving Few-Shot Learning using Composite Rotation based Auxiliary Task, Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA (shifted online), 2021.

6. AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings, Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA (shifted online), 2021.

7. RNNP: A Robust Few-Shot Learning Approach, Pratik Mazumder, Pravendra Singh, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA (shifted online), 2021.

8. Calibrating CNNs for Lifelong Learning, Pravendra Singh
, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai, Conference on Neural Information Processing Systems (NeurIPS ), Virtual Conference, 2020.

9. Minimizing Supervision in Multi-label Categorization, Rajat, Munender Varshney, Pravendra Singh, Vinay P. Namboodiri, IEEE/CVF Conference on Computer Vision and Pattern Recognition - Workshop Proceedings (CVPR-W), Seattle, Washington, USA, 2020.

10. CPWC: Contextual Point Wise Convolution for Object Recognition, Pravendra Singh
, Pratik Mazumder, Vinay P. Namboodiri, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2020.

11. SkipConv: Skip Convolution for Computationally Efficient Deep CNNs, Pravendra Singh, Vinay P. Namboodiri, IEEE International Joint Conference on Neural Networks (IJCNN), Glasgow, Scotland, UK, 2020.

12. Passive Batch Injection Training Technique: Boosting Network Performance by Injecting Mini-Batches from a different Data Distribution, Pravendra Singh, Pratik Mazumder, Vinay P. Namboodiri, IEEE International Joint Conference on Neural Networks (IJCNN), Glasgow, Scotland, UK, 2020.

13. Accuracy Booster: Performance Boosting using Feature Map Re-calibration, Pravendra Singh, Pratik Mazumder, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Colorado, USA, 2020.

14. Cooperative Initialization based Deep Neural Network Training, Pravendra Singh, Munender Kumar, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Colorado, USA, 2020.

15. Leveraging Filter Correlations for Deep Model Compression, Pravendra Singh
, Vinay Kumar Verma*, Piyush Rai, Vinay P. Namboodiri, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Colorado, USA, 2020.

16. A "Network Pruning Network" Approach to Deep Model Compression, Vinay Kumar Verma, Pravendra Singh, Vinay P. Namboodiri, Piyush Rai, IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Colorado, USA, 2020.

17. Stability Based Filter Pruning for Accelerating Deep CNNs, Pravendra Singh, Vinay Sameer Raja Kadi, Nikhil Verma, Vinay P. Namboodiri, IEEE Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA, 2019.

18. Multi-layer Pruning Framework for Compressing Single Shot MultiBox Detector, Pravendra Singh, Manikandan R, Neeraj Matiyali, Vinay P. Namboodiri, IEEE Winter Conference on Applications of Computer Vision (WACV), Hawaii, USA, 2019.

19. Play and Prune: Adaptive Filter Pruning for Deep Model Compression, Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri, International Joint Conference on Artificial Intelligence (IJCAI), Macao, China, 2019.

20. HetConv: Heterogeneous Kernel-Based Convolutions for Deep CNNs, Pravendra Singh, Vinay Kumar Verma, Piyush Rai, Vinay P. Namboodiri, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Long Beach, USA, 2019.

Prof. Rahul Thakur
1. Thakur, R.; Agarwal, S., “Clustering and Transmit Power Control for Social Assisted D2D Cellular Networks” in Proceedings of the IEEE 19th Annual Consumer Communications & Networking Conference (CCNC), 2022, pp. 871-876. [Core Rank: B]

2. Shukla, S.; Thakur, R.; Agarwal, S., “Particle Swarm Optimization Algorithms for Altitude and Transmit Power Adjustments in UAV-Assisted Cellular Networks,” in Proceedings of the 93rd IEEE Vehicular Technology Conference (VTC Spring), Finland, 2021, pp. 1-6. [Core Rank: B, Qualis: A1]

3. Jain, B.; Trivedi, K.; Agarwal, S.; Thakur, R., “MeshSOS: An IoT Based Emergency Response System” in Proceedings of the Hawaii International Conference on System Sciences (HICSS), Hawaii, 2020, pp. 1-10. [ERA: A, Qualis: A1]

4. Agarwal, S.; Thakur, R.; Yadav, U.; Rathore, H., “Socio-Cellular Network: A Novel Social Assisted Cellular Communication Paradigm,” in Proceedings of the 91st IEEE Vehicular Technology Conference (VTC Spring), Belgium, 2020, pp. 1-5. [Core Rank: B, Qualis: A1]

5. Agarwal, S.; Thakur, R.; Mishra, S., “A Link Analysis Based Approach to Predict Character Death in Game of Thrones,” in Proceedings of the 14th International Conference on Testbeds and Research Infrastructures for the Development of Networks & Communities (TRIDENTCOM), People's Republic of China, 2019, pp. 229-244. [Core Rank: B]
Prof. Raksha Sharma
Recent Publications

1. Chakraborty, Abhik, and Raksha Sharma. "See Deeper: Identifying Crystal Structure from X-ray Diffraction Patterns." In 2020 International Conference on Cyberworlds (CW), pp. 49-54. IEEE, 2020. (CORE Ranking: B) 2. Sharma, Raksha Sharma, and Girish Palshikar. "Virus Causes Flu: Identifying Casuality in the Biomedical Domain Using an Ensemble Approach with Target-Specific Semantic Embedings." In International Conference on Applications of Natural Language to Information Systems, pp. 93-104. Springer, Cham, 2021. (ERA Ranking B)

3. Mondal, Anik, and Raksha Sharma. "Team_KGP at SemEval-2021 Task 7: A Deep Neural System to Detect Humor and Offence with Their Ratings in the Text Data." In proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pp. 1169-1174. 2021

4. Gupta, Vansh, and Raksha Sharma. "NLPIITR at SemEval-2021 Task 6: RoBERTa Model with Data Augmentation for Persuasion Techniques Detection." In proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pp. 1061-1067. 2021

5. Amish Garg, Tanav Shah, Vinay K. Jain and Raksha Sharma. "CrypTop12: A Dataset For Cryptocurrency Price Movement Prediction From Tweets And Historical Prices." 20th IEEE International Conference on Machine Learning and Applications (ICMLA), pp. 379-384. 2021. (CORE Ranking: B)

6. Chakraborty, Abhik and Raksha Sharma. "A deep crystal structure identification system for X-ray diffraction patterns." The Visual Computer (2021): 1-8. (SJR Ranking: Q2)

7. Vasava, Himil, Prameg Uikey, Gaurav Wasnik and Raksha Sharma. "Transformer-based Architecture for Empathy Prediction and Emotion Classification." In Proceedings of the 12th Workshop on computational Approaches to Subjectivity, Sentiment & Social Media Analysis, pp. 261-264. 2022

8. Sharma, Gagan, Sunil Gajanan Gitte, Shlok Goyal and Raksha Sharma. "IITR CodeBusters at SemEval-2022 Task-5: Misogyny Identification using Transformers.", In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval) 2022.
Prof. Sateesh Kumar Peddujo
1. Anshul Arora, and Sateesh K. Peddoju, “PermPair : Android Malware Detection using Permission Pairs,” IEEE Transactions on Information Forensics & Security, IEEE, vol. 15, pp. 1968-1982, 2020, (LINK: doi: 10.1109/TIFS.2019.2950134). (SCIE, Scopus)(IF=4.332).
(Anshul Arora is the Ph. D student with Sateesh K. Peddoju)

2. Anshul Arora, and Sateesh K. Peddoju, “Detecting Encrypted and Non-Encrypted Android Malware Traffic by Clustering of Flows,” Journal of Network and Computer Applications, Elsevier, (MINOR REVISIONS DUE). (SCIE, Scopus)(IF=3.991).
(Anshul Arora is the Ph. D student with Sateesh K. Peddoju)

3. S. Prasad, Sateesh K. Peddoju, and D. Ghosh, “Agriculture-as-a-Service,” IEEE Potentials, in Press, 2019.
(Shitala Prasad did his Ph. D thesis work with Sateesh K. Peddoju, Dr. Debashis Ghosh is the colleague to Sateesh K. Peddoju and is the Co-Supervisor to Shitala Prasad)

4. V.C. Pandey, Sateesh K. Peddoju, and Prachi Deshpande, “A Statistical and Distributed Packet Filter against DDoS Attacks in Cloud Environment,” Sadhana Journal, Springer, vol. 43, no. 3, pp. 32:1-9, 2018. (SCIE, JCR, Scopus)(IF=0.592). DOI: https://doi.org/10.1007/s12046-018-0800-7.
(Vikash Chandra Pandey did his M.Tech thesis work with Sateesh K. Peddoju, and Prachi Deshpande is the Ph. D student working with Sateesh K. Peddoju (Co-Supervisor))

5. S. Prasad, Sateesh K. Peddoju, and D. Ghosh, “An adaptive plant leaf mobile informatics using RSSC,” Multimedia Tools and Applications, Springer, vol. 76, No. 20 pp. 21339-21363, 2017. (SCIE, JCR, Scopus, DBLP, ACM)(IF=1.541). DOI: https://doi.org/10.1007/s11042-016-4040-8.
(Shitala Prasad did his Ph. D thesis work with Sateesh K. Peddoju, Dr. Debashis Ghosh is the colleague to Sateesh K. Peddoju and is the Co-Supervisor to Shitala Prasad)

6. S. Prasad, Sateesh K. Peddoju , and D. Ghosh, “An efficient low vision plant leaf shape identification system for smart phones,” Multimedia Tools and Applications, Springer, vol. 76, No. 5, pp. 6915-6939, 2017. (SCIE, JCR, Scopus, DBLP, ACM)(IF=1.541). DOI: https://doi.org/10.1007/s11042-016-3309-2.
(Shitala Prasad did his Ph. D thesis work with Sateesh K. Peddoju, Dr. Debashis Ghosh is the colleague to Sateesh K. Peddoju and is the Co-Supervisor to Shitala Prasad)

7. S. Garg, Sateesh K. Peddoju, and A. K. Sarje, “Network-based detection of Android malicious apps,” International Journal of Information Security, Springer, vol. 16, No. 4, pp. 385-400, 2017. (SCIE, JCR, Scopus, DBLP, ACM)(IF=1.658). DOI: https://doi.org/10.1007/s10207-016-0343-z.
(Shree Garg did her Ph. D thesis work with Dr. Anil K. Sarje. Sateesh K. Peddoju is the colleague to Dr. Anil K. Sarje and is the Co-Supervisor to Shree Garg)

8. S. Prasad, Sateesh K. Peddoju, and D. Ghosh, “Multi-resolution mobile vision system for plant leaf disease diagnosis,”
Prof. Sudip Roy
Recent Publications

1. Debraj Kundu, Sudip Roy, Sukanta Bhattacharjee, Sohini Saha, Krishnendu Chakrabarty, Partha Pratim Chakrabarti and Bhargab B. Bhattacharya "Mixing Models as Integer Factorization: A Key to Sample Preparation with Microfluidic Biochips," in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 3, pp. 558-570, March 2022

2. Debraj Kundu, Jitendra Giri, Sataru Maruyama, Sudip Roy and Shigeru Yamashita, “Fluid-to-cell assignment and fluid loading on programmable microfluidic devices for bio protocol execution”, Elsevier Integration, the VLSI Journal, vol. 78, pp. 95-109, 2021.

3. Shuaijie Ying, Sudip Roy, Juinn-Dar Huang and Shigeru Yamashita, "Design for Restricted-Area and Fast Dilution using Programmable Microfluidic Device based Lab-on-a-Chip," in proceedings of the 24th Euromicro Conference on Digital System Design (DSD), 2021.

4. Sumit Sharma and Sudip Roy, "Optical Waveguide Channel Routing with Reduced Bend-Loss for Photonic Integrated Circuits," in proceedings of the 34th International Conference on VLSI Design and 2021 20th International Conference on Embedded Systems (VLSID), pp. 246-251, 2021.

5. Sumit Sharma and Sudip Roy, “Design of all-optical parallel multipliers using semiconductor optical amplifier-based Mach–Zehnder interferometers”, Springer Journal of Supercomputing, vol. 77, pp. 7315–7350, 2021.

6. Debasis Gountia and Sudip Roy, Security model for protecting intellectual property of state-of-the-art microfluidic biochips, Journal of Information Security and Applications, Volume 58, 102773, ISSN 2214-2126, 2021.