Dr Raj Mani Shukla

Raj conducts research in the general area of artificial intelligence and data science with an interest in cross-disciplinary applications.

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Background

Raj’s research bridges the Machine Learning, Data Science, Cyber Security and Internet of Things. He is particularly interested in pursuing interdisciplinary research. Raj has published many papers at the intersection of these areas. To view the updated list of publications, please refer to Raj’s homepage or Google Scholar profile. Raj would be pleased to talk with the students and researchers to work and collaborate on innovative projects.

Prior to joining ARU, Raj worked as a KTP Associate - Data Scientist at the University of Bristol. He completed PhD in Computer Science and Engineering at University of Nevada, Reno, USA. Raj worked as Junior Research Fellow (JRF) at IIT Kanpur. He received a master's degree from NIT Kurukshetra and completed bachelor's from BIET Jhansi.

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

Spoken Languages

English
Hindi

Research interests

• AI/Machine Learning
• Data Science
• Cyber Security
• Internet of Things
• Interdisciplinary research

Teaching

• Neural Computing and Deep Learning
• Machine Learning

Qualifications

• PhD in Computer Science and Engineering, University of Nevada, Reno, USA
• M.Tech in Instrumentation, National Institute of Technology, Kurukshetra, India
• B.Tech in Electronics and Communication, Bundelkhand Institute of Engineering and Technology, Jhansi, India

Memberships, editorial boards

• TPC member, IEEE Consumer Communications and Networking Conference
• TPC member, EmergencyComm 2020: The International Workshop on Security, Privacy, and Trust for Emergency Events

Selected recent publications

Shukla, R. and Cartlidge, J., 2022, Challenges Faced by Industries and their Potential Solutions in Deploying Machine Learning Applications, Proceedings of IEEE Annual Computing and Communication Workshop and Conference

Walker, A., Shukla, R., Das, T. and Sengupta, S., 2022, Ohana Means Family: Malware Family Classification using Extreme Learning Machines, Proceedings of Annual Consumer Communications & Networking Conference (CCNC)

Bhusal, N., Gautam, N., Shukla, R., Benidris, M., and Sengupta, S., 2022, Coordinated data falsification attack detection in the domain of distributed generation using deep learning, International Journal of Electrical Power & Energy Systems

Shukla, R. and Cartlidge, J., 2021, AgileML: A Machine Learning Project Development Pipeline Incorporating Active Consumer Engagement. Proceedings of IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)