Raj Mani

Raj Mani Shukla

Computing and Information Science, Anglia Ruskin University, Cambridge, UK

Raj Mani Shukla

Computing and Information Science, Anglia Ruskin University, Cambridge, UK

About Me

I am a Senior Lecturer (~Assistant Professor) at Anglia Ruskin University, Cambridge, UK. My research focuses on the intersection of trustworthy and responsible AI, privacy-preserving AI, safety and security of AI application, Internet of Things, and Cloud/Edge computing. Additionally, I engage in interdisciplinary research, utilizing AI for various applications such as healthcare, sustainable and smart cities, cybersecurity, and Software-defined Network (SDN).

Prior to joining ARU, I worked as a KTP Associate - Data Scientist at the University of Bristol. I completed my Ph.D. in Computer Science and Engineering at University of Nevada, Reno under the supervision of Dr. Shamik Sengupta. I worked as Junior Research Fellow (JRF) at IIT Kanpur. I received my masters degree from NIT Kurukshetra and completed my B.Tech from BIET Jhansi.

I would be happy to consider applications from prospective PhD students. Visit department page Computing and Information Science PhD to know more about our PhD program.

Publications

Farah Al-Adwan, Raj Mani Shukla, Hossein Abroshan, Shareeful Islam, and Ronak Al-haddad, "From Spatial to Frequency Domain: Defending Medical Image Classification Against Steganography-Based Adversarial Attacks" , in IEEE International Conference on Big Data, Washington DC, USA, December 2024.

Tapadhir Das, Raj Mani Shukla, and Shamik Sengupta, "Poisoning the Well: Adversarial Poisoning on ML-based Software-defined Network Intrusion Detection Systems" , IEEE Transactions on Network Science and Engineering, November 2024.

Ashwin Kumar, Raj Mani Shukla, and Amar Nath Patra, "Fortifying SplitFed Learning: Strengthening Resilience Against Malicious Clients" , in Annual Conference of the IEEE Industrial Electronics Society, Chicago, USA, November 2024.

Gowtham Vinjamuri, Suvendu Chandan Nayak, Rekha Sahu, Raj Mani Shukla, and Tapadhir Das, "Decentralized Privacy-Preserving Federated Learning for Ultrasonic Nerve Image Segmentation", in Annual Conference of the IEEE Industrial Electronics Society, Chicago USA, November 2024.

Shashank Pulijala, Sara Shahin, Tapadhir Das, Raj Mani Shukla, "Evaluation of Ensemble Learning for Mitigating Adversarial Attacks in Industrial Object Detection", in Annual Conference of the IEEE Industrial Electronics Society, Chicago USA, November 2024.

Tomisin Awosika, Raj Mani Shukla, and Bernardi Pranggono, "Transparency and Privacy: The Role of Explainable AI and Federated Learning in Financial Fraud Detection", in IEEE Access, April 2024.

Sulfikar Shajimon, Raj Mani Shukla, and Amar Nath Patra, "Precision at Heart: An IoT-based Vertical Federated Learning Approach for Heterogeneous Data-Driven Cardiovascular Disease Risk Prediction", December 2023.

Chandima Samarakoon, Raj Mani Shukla, and Tapadhir Das, "A Comprehensive Study of Exploiting GPT Models with PoS Enhanced Adversarial Techniques" , in Authorea Preprints, July 2024.

Tapadhir Das, Raj Mani Shukla, Mohammed Ben-Idris, and Shamik Sengupta, "Vulnerabilities of Machine Learning Algorithms to Adversarial Attacks for Cyber-Physical Power Systems" , in Authorea Preprints, July 2024.

Manas Ranjan Mohapatra, Rahul Radhakrishnan, and Raj Mani Shukla, "A Hybrid Approach using ARIMA, Kalman Filter and LSTM for Accurate Wind Speed Forecasting", in IEEE International Symposium on Smart Electronic Systems, Ahmedabad, India, December 2023.

Angela Grace Famera, Raj Mani Shukla, and Suman Bhunia, "Cross Device Federated Intrusion Detector for Early Stage Botnet Propagation in IoT ", in IEEE International Systems Conference , Montreal, QC, Canada, April 2024.

Lochana Telugu Rajesh, Tapadhir Das, Raj Mani Shukla, and Shamik Sengupta, "Give and Take: Federated Transfer Learning for Industrial IoT Network Intrusion Detection", in IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Exeter, UK, November 2023.

Sankalp Vyas, Amar Nath Patra, and Raj Mani Shukla, "Histopathological Image Classification and Vulnerability Analysis using Federated Learning", in IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Exeter, UK, November 2023.

Prathyusha Devabhakthini, Sasmita Parida, Raj Mani Shukla, and Suvendu Chandan Nayak, "Analyzing the Impact of Adversarial Examples on Explainable Machine Learning".

Aysha Thahsin Zahir Ismail and Raj Mani Shukla "Analyzing the vulnerabilities in SplitFed Learning: Assessing the robustness against Data Poisoning Attacks".

Nam Hoang, Prathyusha Devabhakthini, Raj Mani Shukla, and Suman Bhunia, "Network Coverage Improvement during Natural Disaster using Self-Organizing Maps", in IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering, Tenerife, Canary Islands, Spain, July 2023.

Agnes Barsi, Suvendu Chandan Nayak, Sasmita Parida, and Raj Mani Shukla, "A Deep Learning-based Compression and Classification Technique for Whole Slide Histopathology Images" , in International Journal of Information Technology, Springer Nature Singapore, Pages 1-10, June 2023.

Tapadhir Das, Raj Mani Shukla, Suman Rath, and Shamik Sengupta, "Bringing To Light: Adversarial Poisoning Detection in Multi-controller Software-defined Networks".

Aaron Walker, Raj Mani Shukla, Tapadhir Das, and Shamik Sengupta, "Runs in the Family: Malware Family Variants Identification through API Sequence and Frequency Analysis", in IEEE International Conference on Multimedia Computing, Networking and Applications (MCNA), Valencia, Spain, June 2023.

Tapadhir Das, Osama Abu Hamdan, Raj Shukla, Shamik Sengupta, and Engin Arslan, "UNR-IDD: Intrusion Detection Dataset using Network Port Statistics", in IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2023.

Raj Mani Shukla and Shamik Sengupta, "A novel machine learning pipeline to detect malicious anomalies for the Internet of Things", in Elsevier Internet of Things, November 2022.

Tapadhir Das, Raj Mani Shukla, and Shamik Sengupta, "What Could Possibly Go Wrong?: Identification of Current Challenges and Prospective Opportunities for Anomaly Detection in Internet of Things", in IEEE Network, October 2022.

Raj Mani Shukla and John Cartlidge, "Challenges Faced by Industries and their Potential Solutions in Deploying Machine Learning Applications", in IEEE Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, Nevada, January 2022.

Aaron Walker, Raj Mani Shukla, Tapadhir Das, and Shamik Sengupta, "Ohana Means Family: Malware Family Classification using Extreme Learning Machines", in IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2022.

Narayan Bhusal, Mukesh Gautam, Raj Mani Shukla, Mohammed Benidris, and Shamik Sengupta, "Coordinated Data Falsification Attack Detection in Distributed Generation Domain Using Deep learning  ", accepted and to appear in Elsevier International Journal of Electrical Power and Energy Systems, January 2022.

Tapadhir Das, Raj Mani Shukla, and Shamik Sengupta, "The Devil is in the Details: Confident & Explainable Anomaly Detector for Software-Defined Networks", in IEEE International Symposium on Network Computing and Applications, Boston, Massachusetts, December 2021.

Raj Mani Shukla and John Cartlidge, "AgileML: A Machine Learning Project Development Pipeline Incorporating Active Consumer Engagement", in IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE), December 2021.

Aaron Walker, Tapadhir Das, Raj Mani Shukla, and Shamik Sengupta, "Friend or Foe: Discerning Benign vs Malicious Software and Malware Family ", in IEEE Global Communication Conference (GLOBECOM), December 2021.

Tapadhir Das, Raj Mani Shukla, and Shamik Sengupta, "Imposters Among Us: A Supervised Learning Approach to Anomaly Detection in IoT Sensor Data", in IEEE World Forum on Internet of Things (WF-IoT), July 2021.

Narayan Bhusal, Raj Mani Shukla, Mukesh Gautam, Mohammed Benidris, and Shamik Sengupta, "Deep Ensemble Learning-based approach to Real-time Power System State Estimation", in Elsevier International Journal of Electrical Power and Energy Systems, January 2021.

Raj Mani Shukla, Shahriar Badsha, Deepak Tosh and Shamik Sengupta, "Robust Machine Learning using Diversity and Blockchain", Book chapter, in Aversary-aware Learning Techniques and Trends in Cyber-security, Eds. Prithviraj (Raj) Dasgupta, Joseph B. Collins, Ranjeev Mittu, Springer Nature, March 2020.

Raj Mani Shukla and Shamik Sengupta, "Scalable and Robust Outlier Detector using Hierarchical Clustering and Long Short-Term Memory (LSTM) Neural Network for Internet of Things", in Elsevier Internet of Things Journal January 2020.

Raj Mani Shukla and Shamik Sengupta, "Towards Robust Outlier Detector for Internet of Things Applications", Book chapter, in Modeling and Design of Secure Internet of Things, Eds. Charles A. Kamhoua, Laurent L. Njilla, Alexander Kott, Sachin S. Shetty, Wiley-IEEE Press, February 2020.

Raj Mani Shukla and Shamik Sengupta, "COP: An integrated Communication, Optimization, and Prediction unit for smart Plug-in Electric Vehicle Charging", in Elsevier Internet of Things Journal, December 2019.

Watson Jia, Raj Mani Shukla and Shamik Sengupta, "Anomaly Detection using Supervised Learning and Multiple robust Statistical Methods", Accepted and to appear in special topics on Machine and Deep Learning in Cyber Security and Privacy Issues, IEEE International Conference on Machine Learning and Applications (ICMLA-2019), Boca Raton, Florida, December 2019.

Raj Mani Shukla and Shamik Sengupta, "Analysis and Detection of Outliers due to Data Falsification Attacks in Vehicular Traffic Prediction Application", In Proceedings IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York, USA, November 2018.

Raj Mani Shukla, Shamik Sengupta and Amar Nath Patra, "Software-defined Network Based Resource Allocation in Distributed Servers for Unmanned Aerial Vehicles", In Proceedings of IEEE Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, Nevada, January 2018.

Raj Mani Shukla, Shamik Sengupta and Amar Nath Patra, "Smart Plug-in Electric Vehicle Charging to Reduce Electric Load Variation at a Parking Place", In Proceedings of IEEE Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, Nevada, January 2018.

Raj Mani Shukla, Shamik Sengupta and Mainak Chatterjee, "Software-Defined Network and Cloud-Edge Collaboration for Smart and Connected Vehicles", In Proceedings of International Conference on Distributed Computing and Networking (ICDCN), Varanasi, India, January 2018.

Raj Mani Shukla and Shamik Sengupta, "A Novel Software-defined Network Based Approach for Charging Station Allocation to Plugged-in Electric Vehicles", In Proceedings of 16th IEEE International Symposium on Network Computing and Applications (NCA 2017), Boston, USA, November 2017.

Raj Mani Shukla and Arslan Munir, "An Efficient Computation Offloading Architecture for the Internet of Things (IoT) Devices", Proc. of IEEE Consumer Communications & Networking Conference (CCNC), Las Vegas, Nevada, January 2017.

Raj Mani Shukla, Prasanna Kansakar, and Arslan Munir, "A Neural Network-based Appliance Scheduling Methodology for Smart Homes and Buildings with Multiple Power Sources", Proc. of IEEE International Symposium on Nanoelectronic and Information Systems (iNIS), Gwalior, India, December 2016.

Raj Mani Shukla and Arslan Munir, "A Computation Offloading Scheme Leveraging Parameter Tuning for Real-time IoT Devices", Proc. of IEEE International Symposium on Nanoelectronic and Information Systems (iNIS), Gwalior, India, December 2016.