Shivalika Goyal

About

I am Shivalika Goyal, currently pursuing my PhD at CSIR-Central Scientific Instruments Organisation through Academy of Scientific and Innovative Research. I work under the supervision of Dr. Amit Laddi in the Imagitronics Lab, Department of Biomedical Instrumentation.

My research focuses on computer vision and image processing, with an emphasis on eye gaze tracking. I aim to develop optimized and accessible systems that understand, support, and predict human behavior in complex environments, contributing to improved human–machine interaction.

Employment

• RMIT University PhD Scholar
  2024 - 2028
• CSIR-Central Scientific Instruments Organisation PhD Scholar
  2021 - Present
• Inmed Prognostics Research Analyst
  2020 - 2021

Education

• University of Rajasthan Integrated M.Tech in Cognitive Neurosciences
  2015 - 2020
• St Anselm's Pink City School Malviya Nagar Intermediate (12th) with PCBM
  2013 - 2014
• St Anselm's Pink City School Malviya Nagar Matriculation (10th)
  2012 - 2013

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• Evaluating Feature-Based Machine-Learning Models with Post Hoc Explainability for Eye-Tracking-Based Task Type and Workload Inference
  AI 2026 DOI: 10.3390/ai7080325
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• Vein segmentation and visualization of upper and lower extremities using convolution neural network
  Biomedical Engineering / Biomedizinische Technik 2024 DOI: 10.1515/bmt-2023-0331
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• Machine Learning Techniques for Emotion Detection Using Eye Gaze Localisation
  2024 DOI: 10.4018/979-8-3693-4143-8.ch002
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• Machine Learning for Developing Neurorehabilitation-aided Assistive Devices
  Computational Intelligence and Deep Learning Methods for Neuro-rehabilitation Applications 2023 DOI: https://doi.org/10.1016/B978-0-443-13772-3.00007-8
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• Applications of multimodal biometric technology
  Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision 2023
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• Designing Real-Time Frame Modification Functions Using Hand Gesture Recognition
  Computer Vision and Robotics 2023 DOI: 10.1007/978-981-19-7892-0_26
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