Staff Profile

Introduction

I am a Senior Lecturer in Signal Processing and Machine Learning at the School of Engineering, Newcastle University. I am a core member of Intelligent Sensing and Communications research group. My research is focused in the multidisciplinary area of biomedical signal processing and artificial intelligence that involves developing intelligent signal processing and machine learning tools for the digital healthcare technologies. I am passionate about developing intelligent models by integrating the conventional mathematical and signal processing techniques with the cutting-edge machine learning algorithms. These models are utilised in analysing complex biomedical and healthcare data and making important decisions for risk-prediction, risk-prevention, personalised digital healthcare and assistive robotics.

I received my PhD from Newcastle University, UK and MSc from Northumbria University, Newcastle, UK. My PhD study was in biomedical signal processing that was directed to enhance performance of the hand-held surgical robots during vitreoretinal microsurgeries. My PhD research was a fine blend of signal processing, multidimensional and quaternion modelling, and machine learning, which was aimed to offset the undesired vibration from the tip of the hand-held surgical robots. I have BEng. in Electronics and Communication Engineering from Institute of Engineering, Pulchwok Campus, Nepal. 

My Google Scholar page can be viewed on here. 

Roles and Responsibilities within the School

• 2021 - : Degree Programme Director for MSc Communications and Signal Processing programme
• 2019 - 2021: Stage 1 Tutor for undergraduates studying electrical & electronic degree programmes

Qualifications

·        2013-2019: PhD in Real-time Estimation of Physiological Tremor for Robotic Handheld Surgical Instruments, Newcastle University, UK 

·        2008-2010: Postgraduate Certificate in Education (PGCE), Huddersfield University, UK

·     2006-2007: MSc in Optoelectronics and Communication Systems, Northumbria University, UK

·        2000-2004: BEng in Electronics and Communication Systems, Institute of Engineering(IOE), Pulchowk Campus, Tribhuvan University, Nepal

Memberships

• Fellow of Higher Education Academy (HEA)
• Institute of Electrical and Electronics Engineers (IEEE)

Previous Positions

• 2008-2010: Lecturer, South Tyneside College, South Shields, UK
• 2004-2006: Lecturer, Apex College Nepal

Research Interests

• Applications of AI and Machine Learning in Digital Healthcare
• Biomedical Signal Processing
• Intelligent Signal Processing
• Personalised Digital Healthcare and Assistive Robotics
• Mathematical Modelling of Complex Biological Data
• Multidimensional and Quaternion Modelling
• Adaptive Filtering

Undergraduate

• EEE2010 : Electrical Engineering II
• ENG1002:  Sustainable Design Creativity and Professionalism  

Previous

• EEE8074-MSc
• Coursework
• Stage 1 Labs
• Stage 2 Labs
• EEE2008-Buggy Project Supervision

• Articles

  • Cavus M, Allahham A, Adhikari K, Giaouris D. A hybrid method based on logic predictive controller for flexible hybrid microgrid with plug-and-play capabilities. Applied Energy 2024, 359, 122752.
  • Cavus M, Ugurluoglu YF, Ayan H, Allahham A, Adhikari K, Giaouris D. Switched Auto-Regressive Neural Control (S-ANC) for Energy Management of Hybrid Microgrids. Applied Sciences 2023, 13(21), 11744.
  • Cavus M, Allahham A, Adhikari K, Zangiabadi M, Giaouris D. Energy Management of Grid-Connected Microgrids using an Optimal Systems Approach. IEEE Access 2023, 11, 9907-9919.
  • Makarfi AU, Rabie KM, Kaiwartya O, Adhikari K, Nauryzbayev G, Li X, Kharel R. Toward Physical-Layer Security for Internet of Vehicles: Interference-Aware Modeling. IEEE Internet of Things Journal 2020, 8(1), 443-457.
  • Adhikari K, Tatinati S, Veluvolu KC, Chambers JA. Physiological tremor filtering without phase distortion for robotic microsurgery. IEEE Transactions on Automation Science and Engineering 2020, n/a, n/a.
  • Rathore RS, Sangwan S, Prakash S, Adhikari K, Kharel R, Cao Y. Hybrid WGWO: whale grey wolf optimization-based novel energy-efficient clustering for EH-WSNs. Eurasip Journal on Wireless Communications and Networking 2020, 2020, 101.
  • Wang Y, Tatinati R, Adhikari K, Huang L, Nazarpour K, Ang WT, Veluvolu KC. Multi-step prediction of physiological tremor with random quaternion neurons for surgical robotic applications. IEEE Access 2018, 6, 42216-42226.
  • Adhikari K, Tatinati S, Ang WT, Velovulu KC, Nazarpour K. A quaternion weighted Fourier linear combiner for modeling physiological tremor. IEEE Transactions on Biomedical Engineering 2016, 63(11), 2336-2346.

• Conference Proceedings (inc. Abstracts)

  • Adhikari K, Tatinati S, Veluvolu KC, Chambers JA, Nazarpour K. Real-time physiological tremor estimation using recursive singular spectrum analysis. In: Proceedings of the 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2017, Seogwipo, South Korea: IEEE.
  • Adhikari K, Tatinati S, Veluvolu KC, Nazarpour K. Modeling 3D Tremor Signals with a Quaternion Weighted Fourier Linear Combiner. In: 7th Annual International IEEE/EMBS Conference on Neural Engineering (NER 2015). 2015, Montpellier, France: IEEE.
  • Adhikari K, Tatinati S, Veluvolu KC, Nazarpour K. Improvement in modelling of physiological tremor by inclusion of grip force in quaternion weighted Fourier linear combiner. In: 2nd IET International Conference on Intelligent Signal Processing. 2015, London: IET.