Ms. Taveena | Computer Science | Best Researcher Award

Indian Institute of Technology Roorkee, India

Author Profile

SCOPUS

ORCID

🎓 EARLY ACADEMIC PURSUITS

Ms. Taveena began her academic journey in Computer Science and Engineering at Punjabi University, Patiala, where she completed her undergraduate studies. She pursued her M.Tech. in CSE from IIT (ISM) Dhanbad, where she first ventured into deep learning for audio classification using recurrent neural networks. She is currently pursuing her Ph.D. at IIT Roorkee, focusing on decoding mental imagery through physiological signals under the guidance of Prof. Partha Pratim Roy.

🏢 PROFESSIONAL ENDEAVORS

Ms. Taveena has over 6 years of rigorous research experience, combining deep learning, physiological signal processing, and multimodal data analysis. She is adept at designing efficient neural architectures, contributing to diverse research areas such as neural architecture search (NAS), EEG-fMRI fusion, audio–EEG classification, and cross-modal generation tasks. She has been a key contributor to cutting-edge projects involving parameter-efficient tuning and low-rank adaptation techniques.

📚 CONTRIBUTIONS AND RESEARCH FOCUS IN COMPUTER SCIENCE

Her primary focus lies in developing deep learning frameworks for complex time-series and multimodal signals, particularly in:

• EEG-based motor imagery and speech imagery classification

• Silent speech decoding and mental imagery task adaptation

• Cross-session classification using self-supervised contrastive learning

• Multi-modal EEG–fMRI and image–EEG fusion

• Lightweight neural tuning with adapters

Her contributions extend into broader domains of natural language processing (NLP) and computer vision, focusing on foundational model architectures and cross-modal learning.

🏅 ACADEMIC CITATIONS, ACCOLADES AND RECOGNITION

• 📌 Journal Articles:

  • Biomedical Signal Processing and Control (IF: 4.9)

  • IEEE Transactions on Industrial Informatics (Under review, IF: 9.9)

  • International Journal of Activity and Behavior Computing

• 📌 Conference Presentations:

  • ICPR 2022 (Canada) and ICPR 2025 (India)

  • ABC Conference 2025 (Winner of SSDC challenge and Best Paper Award)

• 📌 Preprints & Community Contribution:

  • Active on arXiv with high-engagement preprints

🌍 IMPACT AND INFLUENCE

Ms. Taveena’s work addresses real-world challenges in neurotechnology, enhancing human–computer interaction, silent communication, and cognitive state monitoring. Her research on EEG signal decoding is paving the way for assistive technologies, particularly benefiting neurologically impaired individuals. She has influenced the academic and open research community through arXiv preprints and open-access contributions.

🧭 LEGACY AND FUTURE CONTRIBUTIONS

Ms. Taveena is poised to leave a lasting impact through:

• Novel deep learning tools for brain signal decoding

• Foundational model adaptation for low-resource and multimodal scenarios

• Open scientific collaboration via preprints and peer reviewing

• Future goals include bridging neuroscience and AI, making cognitive computing more accessible and inclusive

She aims to further contribute to large-scale cross-modal learning, AI for healthcare, and foundational model efficiency for real-time applications.

 ✅CONCLUSION

Ms. Taveena represents the next-generation AI researcher, combining deep theoretical knowledge with practical application in neuroscience, speech, and multimodal learning. With an excellent academic pedigree and significant contributions to EEG decoding and multimodal AI, she is a promising leader in Computer Science and Brain–AI interfaces.

🔬NOTABLE PUBLICATION: