Vivek Kumar Ph.D.

Vivek Kumar Ph.D.

Senior Researcher at the Chair of Open Source Intelligence

Dr. Vivek Kumar has worked at the CODE research institute since July 2023 as a Research Associate at the Chair of Open Source Intelligence. Dr. Kumar won the Marie Sklodowska-Curie fellowship in 2019 for the EU's Horizon 2020 ITN network program  PhilHumans .He worked as a Marie Curie Researcher with Philips Research, Netherlands, and the University of Cagliari, Italy, and received the doctorate in 2023. Prior to this,  he worked as  a Research Engineer for the project "Search for Hidden Particles" ( SHiP ) of the European Commission of Nuclear Research (CERN) at NUST-MiSiS.  He received his MS in Computer Science (red degree) from NUST-MiSiS, Russian Federation in 2017.

He has served as a PC/TPC member of several conferences/workshops (EMNLP, ACL, ACM-SAC, ICASSP, etc.)  and a reviewer for journals of Elsevier, IEEE, Springer, ACM, MDPI, etc.). 

Dr. Kumar is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and  the International Association of Engineers (IAENG). His current research focuses on NLP, Knowledge Graphs,  AI Fairness and BIAS, Mental Health, and Domain Adaptation. Dr. Kumar has published his research at top-ranked venues and has 500+ citations on Google Scholar . 

    Invited Keynote /Tech.Talks  

• Guest Speaker :  Data Makers Fest, 24-25 Sep 2024, Porto, Portugal. [ Link  ] 

• Keynote Speaker :  International Conference on Human-Computer Interaction & Cognitive Computing (HCICC) - 2025) , January 21, 2024. [ Link ]  

• Keynote Speaker : International Conference on  AI of Things for Sustainability, Jan 21, 2024. [ Link ] [ Link to Talk ] 
  

• Guest Speaker :  Data Makers Fest, 22-24 Oct 2023, Porto, Portugal. [ Link to Talk ] 

• Expert Talk: Global School of Excellence, India, 13th June 2023.  

• Expert Talk: PISG Workshop on  Using Knowledge Graph for Domain Adaptation in Natural Language Processing by Rutgers University , USA, 11th Nov 2022 .  

• Guest Talk: Webinar organized by Madhyanchal University, India, June 2021.  

• Guest Talk: Webinar organized by Madhyanchal University, India, June 2020.  

• Talk : SmartPhil Workshop, Italy, March 2020. 

   Selected publications     

Publication Title	Authors	Year	Source
Ask the experts: sourcing high-quality datasets in Mental Health through Human-AI collaboration [ Link ]	Simone Balloccu, Ehud Reiter, Vivek Kumar , Diego Reforgiato Recupero, and Daniele Riboni	2024	Accepted at EMNLP (Findings) - 2024
Unlocking LLMs: Addressing Scarce Data and Bias Challenges in Mental Health and Therapeutic Counseling [Link ]	Vivek Kumar, Eirini Ntoutsi, Pushpraj Singh Rajawat,  Giacomo Medda, and Diego Reforgiato Recupero	2024	Under Final Publications (NLPAICS)
How do you feel? Information Retrieval in Psychotherapy and Fair Ranking Assessment [ Link ]	Vivek Kumar , Giacomo Medda, Diego Reforgiato Recupero, Daniele Riboni, Rim Helaoui, and Gianni Fenu	2023	Proceedings of BIAS (ECIR, 2023) – published in Springer Advances in Bias and Fairness in Information Retrieval
Creation, Analysis & Evaluation of AnnoMI, a Dataset of Expert-Annotated Counseling Dialogues [ Link ]	Wu Zixiu, Simone Balloccu, Vivek Kumar , Rim Helaoui, Diego Reforgiato Recupero, and Daniele Riboni	2023	Future Internet (impact factor* 3.4 )
Data Augmentation for Reliability & Fairness in Counseling Quality Classification [ Link ]	Vivek Kumar , Simone Balloccu, Wu Zixiu, Rim Helaoui, Ehud Reiter, Rim Helaoui, D. Recupero, and D. Riboni	2022	Scarce Data in Artificial Intelligence for Healthcare (SDAIH) at IJCAI-ECAI
Anno-MI: A Dataset of Expert-Annotated Counseling Dialogues [ Link ]	Wu Zixiu, Simone Balloccu, Vivek Kumar , Rim Helaoui, Ehud Reiter, D. Recupero, and Daniele Riboni	2022	International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
K-LM: Knowledge Augmenting in Language Models within Scholarly Domain [ Link ]	Vivek Kumar , Diego Reforgiato Recupero, Rim Helaoui and Daniele Riboni	2022	IEEE Access , vol. 10 (impact factor* 3.47 )
Ensembling Classical Machine Learning and Deep Learning Approaches for Morbidity Identification from Clinical Notes [ Link ]	Vivek Kumar , Diego Reforgiato Recupero, Daniele Riboni and Rim Helaoui	2021	IEEE Access , vol. 9 (Impact factor* 3.47 )