Dr Vaibhav Gandhi is an accomplished academic leader and researcher with over two decades of experience spanning higher education, research, and professional service in the UK and India. Currently serving as Head of Computer Science at University of Southampton Delhi, he provides high-level academic leadership in education and research. Previously, as Director of Programmes for Product Design & Engineering at Middlesex University London, he spearheaded programme design, accreditation, curriculum innovation, and student engagement while strengthening industry and professional body collaborations. His research journey includes pioneering work in cognitive robotics, brain-computer interfacing, and intelligent systems, with successful supervision of doctoral and postgraduate students. A Senior Fellow of the Higher Education Academy (UK) and active member of professional bodies, Dr Gandhi has contributed extensively to global academic standards through roles with the QAA, external examinations, and journal/conference reviewing. With a proven record of leadership, innovation in pedagogy, and commitment to advancing engineering and computer science education, he continues to shape academic excellence and impactful research.
Dr Vaibhav Gandhi is an academic leader and researcher with expertise in brain–computer interfaces (BCIs), assistive robotics, biomedical signal processing, and emerging technologies. He is the founding Head of Computer Science at University of Southampton Delhi, where he leads academic strategy and research development. Prior to this, he held leadership roles at Middlesex University London, most notably as Director of Programmes for Product Design & Engineering, where he spearheaded programme design, accreditation, and practice-based learning initiatives that enhanced both teaching excellence and student employability.
With two decades of experience in computing and engineering education, Dr Gandhi has made significant contributions to research and pedagogy, particularly in areas such as BCIs, assistive robotics, speech disfluency detection, and adaptive human-computer interaction systems. His research includes pioneering the use of quantum mechanics-inspired models for physiological signal processing and developing user-centric interfaces that improve information transfer for BCI users. He champions a project-driven and experiential learning approach, embedding real-world applications into the curriculum to equip students with both technical depth and transferable skills. Alongside his teaching and research, he has supervised doctoral, postgraduate, and undergraduate students, underscoring his commitment to academic mentorship.
Dr Gandhi holds a PhD in Computing and Engineering, jointly completed at Ulster University (UK) and IIT Kanpur (India) under the prestigious UKIERI scholarship. He also holds an MEng in Electrical Engineering, a BEng in Instrumentation & Control, and an MBA in Senior Leadership. Recognized as a Senior Fellow of the UK Higher Education Academy, he has also served as Deputy Chair for the QAA (The UK’s Quality body for Higher Education) to lead the review of Subject Benchmark Statements (SBS) for Engineering (2021-23) thereby contributing to the development of UK higher education standards. A member of the Chartered Management Institute (UK) and a life member of the Indian Society for Technical Education, Dr Gandhi continues to advance interdisciplinary innovation at the intersection of technology, education, and society.
Gandhi, “Brain-computer interface (BCI) technology provides a means of communication that allows individuals with severely impaired movement to communicate with assistive devices using the electroencephalogram (EEG) or other brain signals.”, Elsevier, October 2014. (ISBN: 978-0-12-801543-8).
R Ramar, T Marimuthu, V Gandhi, “Exploring Deep Learning Algorithms and Applications”, Cengage, 2025 (Expected Oct. 2025).
Iva Valentinova Valcheva Vaibhav Gandhi, Eris Chinellato, “Real-Time Gesture Classification Using sEMG Signals for Robotic Control: A Machine Learning Approach” (in-preparation).
Mehta, Vatsal, Glenford Mapp, and Vaibhav Gandhi, “New technologies such as vehicular networks allow more information be available in realtime, and this information can be used with new analytical models to obtain more accurate estimates of journey times.” Future Internet 17, no. 7: 302, 2025. https://doi.org/10.3390/fi17070302.
Arunachalam, M., Ramar, R., Gandhi, V. and Ananthan, B., “Parkinson’s disease (PD) is a common neuro-degenerative issue, evaluated via the continuous deterioration of motor functions over time.”, Indonesian Journal of Electrical Engineering and Computer Science, 37 (2), pp. 1140-1149, Feb. 2025.
Malathi, R. Ramalakshmi, V. Gandhi, A. Bhuvanesh, “This study presents a novel method for Parkinson’s disease prediction using freely accessible resources. The suggested approach starts with band-pass filter data preprocessing and uses Empirical Mode Decomposition (EMD) for feature extraction.”, Journal of Technology and Health Care, Sage Publications, Nov. 2024.
N Sharma, P Mahapatra, V Gandhi, “Speech is essential for communication as it allows us to express ourselves and enables us to use the systems that are speech-based. Disfluency is referred to as any interruption in speaking and can often adversely impact an individual’s life quality.”, 9th International Congress on Information and Communication Technology (ICICT), 19-22 February 2024.
Jones, V. Gandhi, A. Y. Mahiddine, and C. Huyck, “Speech is essential for communication as it allows us to express ourselves and enables us to use the systems that are speech-based. Disfluency is referred to as any interruption in speaking and can often adversely impact an individual’s life quality,” Sensors, vol. 23, no. 21, p. 8880, Nov. 2023, doi: 10.3390/s23218880.
B Ramar, V Gandhi, R Ramalakshmi, P Pandiselvam, “The proposed research introduces an Improved Convolutional Neural Network (ICNN) to construct EEG-based emotion detection models. This study has utilized an EEG dataset of 15 subjects available from a BCMI laboratory.” Proceedings of the 2nd Int’l Conference on Edge Computing and Applications (ICECAA 2023), 19-21 July 2023, India.
N Sharma, V Kumar, P Mahapatra, V Gandhi, “Speech plays a vital role in communication, from expressing oneself, to utilizing speech-based platforms, speech is a necessity. Any disruption in speech is referred to as disfluency, and can impact one’s quality of life.”, Speech Communication, Elsevier, Speech Communication, Vol. 150, pp. 23-31, 2023.
Murugavalli, R. Ramalakshmi, M. Pallikonda Rajasekaran, V. Gandhi, “The neural brain activations are triggered or stimulated by predetermined external influences, including music, videos, audio, meditation and several others.”, Int. Journal of Biomedical Engineering and Technology, Vol 43(2), pp. 101-130, 2023.
K. Murugavalli, R. Ramalakshmi, M. P. Rajasekaran and V. Gandhi, “Undoubtedly one of the most important strands of the brain-computer interface (BCI) method is an alternate communication method via brain signals. BCI converts electroencephalogram (EEG) signals from a perception of activity in the brain into user action utilising software and hardware.,” 2022 4th International Conference on Advances in Computing, Communication Control and Networking (ICAC3N), Greater Noida, India, 2022, pp. 1624-1630, doi: 10.1109/ICAC3N56670.2022.10074500.
Z Yang, and V Gandhi, “Neuromorphic Building Blocks for Locomotion Pattern Generation”, International Conference on Machine Learning, Control, and Robotics (MLCR 2022), 29-31 October 2022, Suzhou, China.
V Mehta, G Mapp, V Gandhi, The 5th International Workshop on Intelligent Transportation and Autonomous Vehicles Technologies (ITAVT 2022)in conjunction with IEEE/IFIP Network Operations and Management Symposium (NOMS 2021) 25-29 APRIL, 2022 – BUDAPEST, HUNGARY.
V Mehta, V Gandhi, and G Mapp (2021), “Transportation accessibility greatly represents and influences regional social-economic
development. The demand for passenger transportation, especially by road, has been increasing due to the globalization process, resulting in delays and traffic congestion.”, In: Third UK Mobile, Wearable and Ubiquitous Systems Research Symposium, 5th Jul – 6th July 2021, Department of Computer Science, University of Oxford, UK.
Cenit, V. Gandhi “This paper reviews the different exoskeleton designs and presents a working prototype of a surface electromyography (EMG) controlled exoskeleton to enhance the strength of the lower leg. The computer aided design (CAD) model of the exoskeleton is designed, 3D printed with respect to the golden ratio of human anthropometry, and tested structurally.”, Journal of Mechatronics, Electrical Power, and Vehicular Technology, Vol 11 (2), 2020.
Onyeulo EB, V Gandhi, “This paper also reflects on the current design of social robots as a means of interaction with humans and also reports potential solutions about several important questions around the futuristic design of these robots.”, Journal: Information, Special Issue: Advances in Social Robots, 2020, 11, 43.
Miller, O.G., Gandhi, V., Swarm robotic systems are heavily inspired by observations of social insects. This often leads to robustness being viewed as an inherent property of them. , Journal of King Saud University – Engineering Sciences (2019).
V Mehta, V Gandhi, and G Mapp, In: Second UK Mobile, wearable and ubiquitous systems have a pivotal role in today’s society and daily life. Research and innovation in these domains has the potential to unlock important new applications and open the door to a better understanding of their use. 1stJul – 2nd July 2019, Department of Computer Science, University of Oxford, UK.
Bisi, S., De Luca, L., Shrestha, B., Yang, Z.,Gandhi, V., “The proposed robot’s structure is specifically designed to provide modularity and is controlled by a Raspberry Pi 3 running on top of an ROS application and a Teensy microcontroller.”, Robotics, 2018, 7, 36.
M Krawczyk, Z Yang, V Gandhi, Mehmet Karamanoglu, Felipe MG França, Priscila MV Lima, Xiaochen Wang and Tao Geng,“Robotic hands are used in a wide range of applications. They have many different shapes, constructions and capabilities.”, Advances in Robotics and Automation, January 2018.
V Gandhi, Z Yang, M Aiash, “Engineering field constantly evolves and thus teaching a module to engineering students should involve current state-of-the-art research trends.”, International Journal of Continuing Engineering Education and Life-Long Learning, Vol. 27, No. 3, 2017.
N Singh, C Huyck, V Gandhi, A Jones, “A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model.,” International Journal of Biomedical and Biological Engineering Vol:4, No:2, 2017.
Kalyani G.K., Yang Z., Gandhi V., Geng T. (2017) Assimilating intelligence plays an important role in the field of robotics that enables a computer to model or replicate some of the intelligent behaviors of human beings but with minimal human intervention.. In: Gao Y., Fallah S., Jin Y., Lekakou C. (eds) Towards Autonomous Robotic Systems. TAROS 2017. Lecture Notes in Comp Sc, vol 10454. Springer.
P. Parmar, A. Joshi, V. Gandhi, “A robotic arm and hand controlled by simulated neurons is presented. The robot makes use of a biological neuron simulator using a point neural model.”, 5th Nirma University International Conference on Engineering (NUiCONE), India, Nov. 2015.
V. Krasim, V. Gandhi, Z. Yang, and M. Karamanoglu, “Electromyography (EMG) signals can be used to integrate with machines and form one assistive system such as a powered exoskeleton.”,IEEE International Joint Conference on Neural Network, Killarney, Republic of Ireland, 11th – 17th July 2015.
Z. Yang, V. Gandhi, M. Karamanoglu, B. Graham, “The Izhikevich spiking neuron model is a relatively new mathematical framework which is able to represent many observed spiking neuron behaviors, excitatory or inhibitory, by simply adjusting a set of four model parameters”, IEEE International Joint Conference on Neural Network, Killarney, Republic of Ireland, 11th – 17th July 2015.
Gandhi, G. Prasad, D. Coyle, L. Behera, and T. M. McGinnity, “The raw EEG signal acquired non-invasively from the sensorimotor cortex during the motor imagery (MI) performed by a brain-computer interface (BCI) user is naturally embedded with noise while the actual noise-free EEG is still unattainable. “, Neurocomputing, Vol. 170, pp. 161–167, 25 December 2015.
V. Gandhi, G. Prasad, D. Coyle, L. Behera, and T. M. McGinnity, “A major challenge in two-class brain-computer interface (BCI) systems is the low bandwidth of the communication channel, especially while communicating and controlling assistive devices, such as a smart wheelchair or a telepresence mobile robot, which requires multiple motion command options in the form of forward, left, right, backward, and start/stop.”, IEEE Transactions on Systems Man & Cybernetics: Systems, Vol. 44, No. 9, pp. 1278-1285, 2014.
V. Gandhi, G. Prasad, D. Coyle, L. Behera, and T. M. McGinnity, “A novel neural information processing architecture inspired by quantum mechanics and incorporating the well-known Schrodinger wave equation is proposed in this paper.”, IEEE Transactions On Neural Networks and Learning Systems, Vol. 25, No. 2, pp 278- 288, 2014.
V. Gandhi and T. M. McGinnity, “A filtering methodology inspired by the principles of quantum mechanics and incorporating the well-known Schrodinger wave equation is investigated for the first time for filtering EMG signals.”, 2013 IEEE International Joint Conference on Neural Network, 4 – 9 Aug., 2013, USA.
V. Gandhi, V Arora, L. Behera, G. Prasad, D Coyle, and M. McGinnity, “Brain-computer interface (BCI) technology is a means of communication that allows individuals with severe movement disability to communicate with external assistive devices using the electroencephalogram (EEG) or other brain signals.,” in IEEE International Joint Conference on Neural Network, 31 July – 5 Aug., 2011, USA.
Gandhi, V Arora, L. Behera, G. Prasad, D Coyle, and M. McGinnity, “The brain-computer interface (BCI) technology is a means of communication that allows individuals with severe movement disability to communicate with external assistive devices using the electroencephalogram (EEG) or other brain signals”, in The Institution of Engineering and Technology (IET), 6 April, 2011, UK.
V. Gandhi, G. Prasad, D. Coyle, L. Behera, and T. M. McGinnity, “A brain computer interface (BCI) allows a person to communicate with external devices using electroencephalogram (EEG) or other brain signals.”, in Irish Signals and Systems Conference, Ireland, 10-11 June, 2009, Ireland.
V. Gandhi, D. Coyle, G. Prasad, C. Bharti, L. Behera, and T. M. McGinnity, “Interfacing a dynamic Interface Paradigm for Multiple Target Selection Using a Two Class Brain Computer Interface“, in Indo – US Workshop on System of Systems Engineering, 26-28 Oct. 2009, IIT Kanpur, India.
V. Gandhi and D.N.Priyadarshi, “Foundation Fieldbus – Introduction of Digital Control Network for Industrial Automation”, in Networking: Technology and Applications, IETE, India, 2008.
V. Gandhi, “Analyzing the performance of backpropagation neural network in Image classification problem”, in Smart Computing and Communication, IETE, India, 2007.
V. Gandhi, “Lecture delivered on topic of image classification based on textural features using unsupervised neural network in 1st International Indian Geographical Congress conference.“, in 1st International Indian Geographical Congress, India, 2006.
K.Shah and V. Gandhi, “Image classification plays an important part in the fields of Remote sensing, Image analysis and Pattern recognition.”, in Institution of Engineers (I), Vol 4, pp. 72-77, 2004.
Designing EEG-controlled robotic systems for individuals with severe motor disabilities.
Develop and validate a robust, automated system capable of accurately detecting and classifying a comprehensive range of speech disfluencies using machine learning. (PhD thesis supervision of N Sharma: Detection and Classification of Speech Disfluencies)
Developing quantum-inspired signal de-noising models for BCI applications.
Creating sEMG-driven robotic devices to support mobility (UG and PG student projects).
A robotic arm and hand, driven by a simulated neural network organized as a finite state automaton, demonstrating a proof-of-concept pick-and-place task that bridges neuroscience, robotics, and psychology with the dual aim of advancing flexible robot design and deepening understanding of biological motor control. (PhD thesis supervision of N Singh: Neuron based control mechanisms for robot arm movement)
Presents a novel Markovian framework, including the Zero Server Markov Chain, to analyze delays at junctions and along roads for more accurate journey time estimation. Validated through SUMO simulations and real-world routes, the work demonstrates clear improvements over existing methods and offers strong potential for advancing intelligent traffic management. (PhD thesis supervision of V Mehta: Developing Traffic Predictions from Source to Destination using Stochastic Modelling)
Our group brings together engineers and computer scientists to discover new approaches to prevent, diagnose and manage health and medical conditions.
Our group explores the theory behind technological areas including control, machine learning and computer vision.
We aim to improve education across the whole of Electronics and Computer Science in a meaningful, healthy, and sustainable way.
