Dr Akshi Kumar

Akshi has distinct expertise in Natural Language Processing, AI ethics, cyber-informatics, and AI-driven healthcare

Staff details

Dr Akshi Kumar

Position

Senior Lecturer

Department

Computing

Email

Akshi.Kumar (@gold.ac.uk)

I am a Senior Lecturer (Associate Professor), Director of Postgraduate Research, and Chair of Research Ethics in Computing at Goldsmiths, University of London. With 15+ years in academia, my expertise spans NLP, AI ethics, and explainable AI. Recognized among the Top 2% highly cited scientists globally (2021–2024), I have 110+ journal and 70+ conference papers. My research focuses on AI and NLP in high-stakes domains like health, finance, and education—advancing clinical decision support, fraud detection, and adaptive learning. As a Steering Committee member for Online Safety (Mayor of London’s VRU), I shape policies for safer digital spaces. I have contributed to two POSTnotes on AI and mental health and four UK Parliament inquiries on AI’s impact. Author of Language Intelligence: Expanding Frontiers in NLP (IEEE-Wiley, 2025) and Web Technology: Theory and Practice (CRC, 2018), I collaborate globally, promoting AI for social good, ethical innovation, and diversity.

Academic qualifications

  • PhD (Computer Science & Engineering)-Web Mining, University of Delhi, India 2011
  • MTech (Computer Science & Engineering), GGSIPU, Delhi, India 2005
  • BE (Computer Science & Engineering), MDU, Rohtak, India 2003

Research interests

  • Artificial Intelligence – Advancing AI for high-stakes decision-making.
  • Natural Language Processing – Developing NLP solutions for critical domains.
  • Explainable and Responsible AI – Ensuring transparency, fairness & trust in AI.
  • AI in Healthcare and Finance – Leveraging AI for clinical insights, risk assessment, and decision support.
  • Cyber-Informatics & Online Safety – Addressing fake news, rumours, deepfakes, hate speech, cyberbullying, and applied network science.

    • Featured publications

    2024: Resp-BoostNet: Mental Stress Detection from Biomarkers Measurable by Smartwatches using Boosting Neural Network Technique.
    IEEE Access (Volume: 12) Page(s): 149861 - 149874

    2023: Am I Hurt?: evaluating psychological pain detection in Hindi text using transformer-based models
    ACM Transactions on Asian and Low-Resource Language Information Processing (ACM TALLIP), 23(8), 1-17.

    2023: SIRA: A Model for Propagation and Rumor Control with Epidemic Spreading and Immunization for Healthcare 5.0
    Soft Computing, A Fusion of Foundations, Methodologies and Applications, Springer

    2021: Hierarchical Deep Neural Network for Mental Stress State Detection using IoT based Biomarkers
    Pattern Recognition Letters, Elsevier, Vol.145, pp. 81-87

    2020: Hybrid Context Enriched Deep Learning Model for Fine-grained Sentiment Analysis in Textual and Visual Semiotic Modality Social Data
    Information Processing and Management, Elsevier, Vol. 57, No. 1, 102141

    Publications and research outputs

    Book

    Article

    Conference or Workshop Item

    Digital

    Professional Activity

    Project

    Report

    Other

    Professional projects

    NLP-Powered Job Matching for Blue-Collar Workers (2023-2024)
    Research Consultant | Funded by Hirers (hirers.co.in)
    • Spearheaded the research and implementation of a Natural Language Processing (NLP)-driven solution to enhance job matching for blue-collar workers.
    • Developed and refined NLP algorithms to improve the accuracy and speed of matching job descriptions with candidate profiles.
    • Applied techniques such as aspect-based sentiment analysis and intent detection to enhance the semantic understanding of job postings and resumes.
    • Provided consultancy for platform design improvements that increased user engagement through customized job recommendations and enhanced communication tools.
    • Delivered comprehensive reports on the integration of fine-grained sentiment analysis and emotion detection for optimizing platform performance and user experience.

    ExplainED: Enhancing Feedback Precision in Education Using NLP and Explainable AI (Started Jan 2025)
    Research Consultant | Deziwebapp Systems Private Limited (KTP)

    This collaborative project focuses on employing advanced Natural Language Processing
    (NLP) and Explainable AI (XAI) techniques to enhance feedback systems in education. The
    primary objectives include:
    • Automating the feedback process for assignments and discussions to save educators
    time and enhance precision.
    • Ensuring transparency through explainable AI mechanisms for actionable insights.
    • Analyzing student engagement to identify and address learning gaps effectively.

    Conferences and talks

    2023: ‘Enabling Natural Communication in the Social Metaverse: Role of Natural Language Processing’
    Keynote Speaker, 6th International Conference on Web Services Computing–Social Metaverse Summit, 26th May, 2023 at SCMS COCHIN Campus, India

    2023: 'Opportunities and Threats of Generative AI in medicine, science, and academic publishing’
    Keynote Speaker, International Conference on Advancement in Computation & Computer Technologies, Chandigarh University, India, May 5-6, 2023

    Highlights

    Endorsed by the Royal Academy of Engineering, United Kingdom as an Exceptional Talent in the field of Artificial Intelligence/Data Science in 2022.

    13 research awards for Excellence in Research.