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Dr. Lekshmi C. R.

Assistant Professor, Centre for Computational Engineering and Networking, School of Artificial Intelligence, Coimbatore

Qualification: M.Tech., Ph.D
cr_lekshmi@cb.amrita.edu
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Research Interest: Signal Processing using deep learning, Neural networks, Generative adversarial networks, Transformer architectures, Attention mechanism

Bio Publications Qualifications Peer-reviewed Positions Awards Miscellaneous Research Scholars
Bio

Dr. Lekshmi C. R. is an Assistant Professor at the Centre for Computational Engineering and Networking, School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Coimbatore. She earned her Ph.D. from the College of Engineering Trivandrum, focusing on “Predominant Instrument Recognition and Separation in Polyphonic Music Using Deep Learning Frameworks.”

Her research interests include image and audio processing with deep learning, attention mechanisms, generative adversarial networks, and transformer architectures. Dr. Lekshmi holds a B.Tech in Electronics and Communication Engineering from CUSAT and a Master’s in Applied Electronics from Anna University, Chennai.

Publications

Journal Article

Year : 2026

Explainable AI Framework for Automated Lesion Segmentation and Severity Assessment in Neonatal Hypoxic-Ischemic Encephalopathy

Cite this Research Publication : Athira Chandran, Lekshmi Chandrika Reghunath, Explainable AI Framework for Automated Lesion Segmentation and Severity Assessment in Neonatal Hypoxic-Ischemic Encephalopathy, Journal of Computational and Cognitive Engineering, BON VIEW PUBLISHING PTE, 2026, https://doi.org/10.47852/bonviewjcce62027647

Publisher : BON VIEW PUBLISHING PTE

Year : 2026

Learning graph representations from Mel-spectrogram segments for predominant instrument recognition in polyphonic music

Cite this Research Publication : Riya Rajeev, Lekshmi Chandrika Reghunath, Noumida A., Rajeev Rajan, Learning graph representations from Mel-spectrogram segments for predominant instrument recognition in polyphonic music, Journal on Audio, Speech, and Music Processing, Springer Science and Business Media LLC, 2026, https://doi.org/10.1186/s13636-026-00471-4

Publisher : Springer Science and Business Media LLC

Year : 2026

Functional Assessment of Neonatal Hypoxic–Ischemic Encephalopathy Using Long-Duration EEG and Interpretable Deep Learning Models

Cite this Research Publication : Athira Chandran, Lekshmi Chandrika Reghunath, Claudio Tomazzoli, Christian Napoli, Cristian Randieri, Functional Assessment of Neonatal Hypoxic–Ischemic Encephalopathy Using Long-Duration EEG and Interpretable Deep Learning Models, Big Data and Cognitive Computing, MDPI AG, 2026, https://doi.org/10.3390/bdcc10060175

Publisher : MDPI AG

Year : 2025

Artificial Intelligence for Iteration Count Prediction in Real-Time CORDIC Processing

Cite this Research Publication : Ratheesh Sudheerbabu, Lekshmi Chandrika Reghunath, Valentina Franzoni, Alfredo Milani, Cristian Randieri, Artificial Intelligence for Iteration Count Prediction in Real-Time CORDIC Processing, Mathematics, MDPI AG, 2025, https://doi.org/10.3390/math13243957

Publisher : MDPI AG

Year : 2025

Cross-Attentive CNNs for Joint Specral and Pitch Feature Learning in Predominant Instrument Recognition from Polyphonic Music

Cite this Research Publication : Lekshmi Chandrika Reghunath, Rajeev Rajan, Christian Napoli, Cristian Randieri, Cross-Attentive CNNs for Joint Specral and Pitch Feature Learning in Predominant Instrument Recognition from Polyphonic Music, Technologies, MDPI AG, 2025, https://doi.org/10.3390/technologies14010003

Publisher : MDPI AG

Year : 2025

Dynamic Feature Learning with Involution and Convolution for Predominant Instrument Recognition in Polyphonic Music

Cite this Research Publication : C. R. Lekshmi, Jishnu Teja Dandamudi, Dynamic Feature Learning with Involution and Convolution for Predominant Instrument Recognition in Polyphonic Music, Circuits, Systems, and Signal Processing, Springer Science and Business Media LLC, 2025, https://doi.org/10.1007/s00034-025-03111-y

Publisher : Springer Science and Business Media LLC

Year : 2025

Beyond transformers: hierarchical contextualization and gated aggregation for multiple predominant instrument recognition in polyphonic music

Cite this Research Publication : C. R. Lekshmi, Rajeev Rajan, Beyond transformers: hierarchical contextualization and gated aggregation for multiple predominant instrument recognition in polyphonic music, The Journal of Supercomputing, Springer Science and Business Media LLC, 2025, https://doi.org/10.1007/s11227-025-07279-7

Publisher : Springer Science and Business Media LLC

Year : 2023

Predominant audio source separation in polyphonic music

Cite this Research Publication : Reghunath,L.C.,Rajan,R., ”Predominant Audio Source Separation”, Eurasip Journal of Audio Speech and Music Processing 49, (2023), , Impact factor: 2.4, SJR: 0.458, Indexing: SCIE

Year : 2023

Multiple Predominant Instruments Recognition in Polyphonic Music using Spectro/Modgd-gram Fusion

Cite this Research Publication : Lekshmi C. R., Rajeev, R. “Multiple Predominant Instruments Recognition in Polyphonic Music using Spectro/Modgd-gram Fusion”, Circuits Syst Signal Process (CSSP) ,42, 3464–3484 (2023)., ,Impact factor: 2.3, SJR: 0.494, Indexing: SCIE

Year : 2022

POMET: a corpus for poetic meter classification

Cite this Research Publication : Rajan, R., ChandrikaReghunath, L. & Varghese, L.T. POMET: a corpus for poetic meter classification. Lang Resources & Evaluation 56, 1131–1152 (2022)., Impact factor: 2.7, Indexing: SCIE

Year : 2022

Transformer-based Ensemble Method for Multiple Predominant Instruments Recognition in Polyphonic Music

Cite this Research Publication : Reghunath, L C., Rajan, R., “Transformer-based Ensemble Method for Multiple Predominant Instruments Recognition in Polyphonic Music”, Eurasip Journal of Audio Speech and Music Processing (2022), Impact factor: 2.4, SJR: 0.458, Indexing: SCIE

Conference Paper

Year : 2025

Integrated Segmentation and Classification Framework for Neonatal HIE Using SegResNet and XGBoost

Cite this Research Publication : Athira Chandran, Lekshmi Reghunath, Integrated Segmentation and Classification Framework for Neonatal HIE Using SegResNet and XGBoost, 2025 IEEE 22nd India Council International Conference (INDICON), IEEE, 2025, https://doi.org/10.1109/indicon68490.2025.11392887

Publisher : IEEE

Year : 2025

Ai-Powered Pencil Strokes: Face Sketch Synthesis Using Cyclegan and Style Transfer

Cite this Research Publication : Sighakolli Dheeraj Venkata Sai, Simma Sathwik, Solleti Venkata Dhiraj, Peddi Deekshith, C. R Lekshmi, Ai-Powered Pencil Strokes: Face Sketch Synthesis Using Cyclegan and Style Transfer, 2025 International Conference on Inventive Computation Technologies (ICICT), IEEE, 2025, https://doi.org/10.1109/icict64420.2025.11005149

Publisher : IEEE

Year : 2025

Robust CNN-based Musical Instrument Recognition with Enhanced Feature Learning

Cite this Research Publication : Padmesh Sivalingam, Aamith Kishore T J, Sri Krishna P, Yaswanth Reddy B, Ragav S, Lekshmi C. R., Robust CNN-based Musical Instrument Recognition with Enhanced Feature Learning, 2025 International Conference on Inventive Computation Technologies (ICICT), IEEE, 2025, https://doi.org/10.1109/icict64420.2025.11005342

Publisher : IEEE

Year : 2024

Compact Convolutional Transformers for Multiple Predominant Instrument Recognition in Polyphonic Music

Cite this Research Publication : Lekshmi C. R., Rajeev Rajan, Compact Convolutional Transformers for Multiple Predominant Instrument Recognition in Polyphonic Music, 2024 9th International Conference on Communication and Electronics Systems (ICCES), IEEE, 2024, https://doi.org/10.1109/icces63552.2024.10860152

Publisher : IEEE

Year : 2021

Predominant Instrument Recognition in Polyphonic Music Using Convolutional Recurrent Neural Networks

Cite this Research Publication : Lekshmi.C.R. and Rajan, R., “Predominant Instruments recognition in Polyphonic music using Convolutional Recurrent Neural Networks”, in Proc. of the 15th International Symposium on CMMR, Tokyo, Japan,Nov. 15-19, 2021 ,pp 185-194

Year : 2021

Attention-based Predominant Instruments Recognition in Polyphonic Music

Cite this Research Publication : Lekshmi C. Reghunath. and Rajeev Rajan., “Attention-based Predominant Instruments Recognition in Polyphonic Music”, in Proceedings of 18th Sound and Music Computing Conference (SMC), Torino, Italy, 29 June – 01 July 2021, pp. 199–206

Book Chapter

Year : 2021

Predominant Instruments recognition in Polyphonic music using Convolutional Recurrent Neural Networks

Cite this Research Publication : Predominant Instruments recognition in Polyphonic music using Convolutional Recurrent Neural Networks”, in Proceedings of 15th International Symposium on Computer Music Multidisciplinary Research (CMMR-21), Tokyo, Japan, Nov 15 - 19, 2021, pp 185-194. In: Revised selected papers ,Music in the AI Era,. Lecture Notes in Computer Science, vol13770 . Springer, Cham

Year :

Facial emotion and sleep detection via audio feedback: An assistive AI system

Cite this Research Publication : Rakesh, Meesa, Jatin Chandra Gupta, Sai CH Virinchi, Majji Jayesh, and C. R. Lekshmi. "Facial emotion and sleep detection via audio feedback: An assistive AI system." In Artificial Intelligence, Computational Intelligence and Inclusive Technologies, pp. 830-834. CRC Press. 

Qualifications
  • PhD : 2019-2023
    Specialization: Signal processing using deep learning
    Thesis Title: Predominant Instrument Recognition and Separation in Polyphonic Music Using Deep Learning Frameworks.
  • M.Tech : 2013
    Specialization: Applied Electronics
    Thesis Title: Color document image authentication with data repair capability.
Peer-reviewed
  • C. R. and J. T. Dandamudi, “Spatio-Channel Complementary Learning for Polyphonic Music Instrument Recognition,” 2025 IEEE 2nd International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS), Bangalore, India, 2025, pp. 1-7, doi: 10.1109/ICITEICS64870.2025.11341086.
  • C R, L., Rajan, R. (2025) Focal Modulation Network: A Novel Solution for Polyphonic Music Instrument Recognition without Attention and Aggregation Strategy . Proc. Interspeech 2025, 3095-3099, doi: 10.21437/Interspeech.2025-930
  • Praneeth, S. Meera, N. Raaman, A. Mithul and L. C. R, “Enhancing Autonomous Driving Systems: Integrated Lane and Object Detection Using YOLOv3 and OpenCV,” 2025 9th International Conference on Inventive Systems and Control (ICISC), Coimbatore, India, 2025, pp. 193-199, doi: 10.1109/ICISC65841.2025.11188086.
  • Meghana, Kankipati & Supriya, Kondakindi & Kumar, Korumilli & Mahendra, Mula & R., Lekshmi. (2025). Performance Analysis of YOLOv5 for Real-Time Object Detection and Manipulation in Unity on CPU and GPU. 1712-1717. 10.1109/ICCMC65190.2025.11140623.
  • S. S. S.K, R. Nethra, C. H. V. Krishna, L. C. R and N. Mohan, “Integrated License Plate Recognition Using YOLO and CNN for Automated Vehicle Identification,” 2025 9th International Conference on Inventive Systems and Control (ICISC), Coimbatore, India, 2025, pp. 153-160, doi: 10.1109/ICISC65841.2025.11187533.
Positions
  • Assistant Professor from 03/06/2024 to till date at Amrita Viswa Vidyapeetham, Coimbatore campus
  • Worked as Assistant Professor in various engineering colleges.(Total experience: 7 years)
Awards
  • 3rd rank in KTU Ph. D. entrance (Availed KTU CERD Fellowship-2019), 31 st rank in ME Applied electronics (2013)
Miscellaneous

Membership/Associations

  • International SpeechCommunication Association (ISCA)-Member-2025-26

Reviewers (National/International Journals; Conferences)

  • IEEE Transactions on Audio, Speech, and Language Processing (TASLP)-ISSN: 1558-7916
  • Scientific Reports, Springer-ISSN: 2045-2322
  • IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)
  • Journal of Supercomputing, Springer-ISSN: 1573-0484
  • ASEAN Journal on Science and Technology for Development, Elsevier-ISSN: 2224-9028
Research Scholars
S.No. Student ID Name Date Activity
1 CB.AI.R4CEN26006 Anisree P G 15-07-2026 Course Work
2 CB.AI.R4CEN26007 Aswathy Chandran 17-07-2026 Course Work
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