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Dr. Vivek Kumar

Dr. Vivek Kumar

Research Fellow, ADAPT

Research Fellow, Trinity Business School

Biography

Dr. Vivek Kumar is currently a Research Scientist (Fellow) at the ADAPT Research Centre and Trinity Business School, Trinity College Dublin. His work spans Natural Language Processing, Large Language Models, AI Bias, Mental Health, and Domain Adaptation. Previously, he was a Senior Researcher at the University of the Federal Armed Forces, Munich, under the German Ministry of Defence and coordinated the EU Horizon Europe project STELAR. In 2019, he was awarded the prestigious Marie Sk"odowska-Curie Fellowship under the EU Horizon 2020 PhilHumans ITN, where he conducted research at Philips Research (Netherlands) and the University of Cagliari (Italy), receiving his doctorate in 2023. Before that, he worked as a Research Engineer on the Search for Hidden Particles (SHiP) project at CERN. Dr. Kumar is a Senior Member of IEEE, a Fellow of SCRS, and serves as a reviewer and programme committee member for leading AI and NLP conferences, including ARR/ACL, EMNLP, IJCAI, ECAI, ECML-PKDD, IJCNN, ACM-SAC, ICASSP,
IEEE DSAA, IEEE WCCI.

RESEARCH INTERESTS
" Natural Language Processing, AI Bias, Domain Adaptation, Mental Health, Psychology, Large Language Models and Knowledge Graphs.

Publications and Further Research Outputs

  • Vivek Kumar; Pushpraj Singh Rajawat; Eirini Ntoutsi, Mitigating Semantic Drift: Evaluating LLMs Efficacy in Psychotherapy through MI Dialogue Summarization Leveraging MITI Code, International Joint Conference on Neural Networks (IJCNN), Rome, Italy, International Joint, 2025Conference Paper, 2025, URL
  • Balloccu S., Reiter E., Li K.J.-H., Sargsyan R., Kumar V., Recupero D.R., Riboni D., Dusek O., Ask the experts: Sourcing a high-quality nutrition counseling dataset through Human-AI collaboration, EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Findings of EMNLP 2024, 2024, p11519 - 11545, p11519-11545Conference Paper, 2024, DOI
  • Jain P.H., Kumar V., Samuel J., Singh S., Mannepalli A., Anderson R., Artificially Intelligent Readers: An Adaptive Framework for Original Handwritten Numerical Digits Recognition with OCR Methods, Information (Switzerland), 14, (6), 2023Journal Article, 2023, DOI
  • Sangher K.S., Singh A., Pandey H.M., Kumar V., Towards Safe Cyber Practices: Developing a Proactive Cyber-Threat Intelligence System for Dark Web Forum Content by Identifying Cybercrimes, Information (Switzerland), 14, (6), 2023Journal Article, 2023, DOI
  • Gupta S., Singh A., Kumar V., Emoji, Text, and Sentiment Polarity Detection Using Natural Language Processing, Information (Switzerland), 14, (4), 2023Journal Article, 2023, DOI
  • Wu Z., Balloccu S., Kumar V., Helaoui R., Reforgiato Recupero D., Riboni D., Creation, Analysis and Evaluation of AnnoMI, a Dataset of Expert-Annotated Counselling Dialogues ", Future Internet, 15, (3), 2023Journal Article, 2023, DOI
  • Samuel Y., Brennan-Tonetta M., Samuel J., Kashyap R., Kumar V., Krishna Kaashyap S., Chidipothu N., Anand I., Jain P., Cultivation of human centered artificial intelligence: culturally adaptive thinking in education (CATE) for AI, Frontiers in Artificial Intelligence, 6, 2023Journal Article, 2023, DOI
  • Kumar V., Medda G., Recupero D.R., Riboni D., Helaoui R., Fenu G., How Do You Feel? Information Retrieval in Psychotherapy and Fair Ranking Assessment, Communications in Computer and Information Science, 1840 CCIS, 2023, p119 - 133, p119-133Conference Paper, 2023, DOI
  • Kumar V., Reforgiato Recupero D., Helaoui R., Riboni D., K-LM: Knowledge Augmenting in Language Models Within the Scholarly Domain, IEEE Access, 10, 2022, p91802 - 91815, p91802-91815Journal Article, 2022, DOI
  • Wu Z., Balloccu S., Kumar V., Helaoui R., Reiter E., Recupero D.R., Riboni D., ANNO-MI: A DATASET OF EXPERT-ANNOTATED COUNSELLING DIALOGUES, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 2022-May, 2022, p6177 - 6181, p6177-6181Conference Paper, 2022, DOI
  • Kumar V., Recupero D.R., Riboni D., Helaoui R., Ensembling Classical Machine Learning and Deep Learning Approaches for Morbidity Identification from Clinical Notes, IEEE Access, 9, 2021, p7107 - 7126, p7107-7126Journal Article, 2021, DOI
  • Wu Z., Helaoui R., Kumar V., Reforgiato Recupero D., Riboni D., Towards detecting need for empathetic response in motivational interviewing, ICMI 2020 Companion - Companion Publication of the 2020 International Conference on Multimodal Interaction, 2020, p497 - 502, p497-502Conference Paper, 2020, DOI

Research Expertise

Natural language processing, Machine learning, Artificial intelligence and machine learning,

Recognition

  • Marie Sklodowska-Curie Fellowship 2019
  • Fellow SCRS 2025
  • Ministry of Education & Science Fellowship 2014
  • Senior Member - IEEE 2023
  • Senior Member - Institute of Electrical and Electronics Engineers (IEEE)
  • International Affiliate - American Psychological Association (APA)
  • Fellow - Soft Computing Research Society (SCRS)