Dr. Kalluri Shareef Babu

Dr. Kalluri Shareef Babu is a researcher and academician specializing in Speech Signal Processing and Machine Learning, with a strong focus on Speaker Profiling, Speaker Diarization, Language Diarization, Automatic Speech Recognition (ASR), and Human Behavior Analysis using text and speech modalities. He earned his Ph.D. in Department of Electronics and Communication Engineering  from the National Institute of Technology Karnataka (NITK) Surathkal (2021), where he explored speaker profiling techniques for estimating physical characteristics such as height, age, and weight from speech. 

As a Postdoctoral Fellow in Dept. of Computer and Information Science at Seikei University, Dr. Shareef Babu worked on Motivational Interviewing, applying speech-based analysis to behavioural and psychological assessments. Later, as a Postdoctoral Fellow at the Indian Institute of Science (IISc) Bangalore, his research focused on speech applications in conversational environments, including multilingual and multi-speaker ASR, speaker diarization, and language diarization.

Dr. Shareef Babu played a key role in organizing the  Diarization of Speaker and Language in Conversational Environments (DISPLACE ) 2024 Challenge, a special session at Interspeech 2024, Kos Island, Greece.  

• Assistant Professor, School of Computer Science, UPES, Dehradun (Dec-2024 – till now)
• Postdoctoral Researcher, LEAP Lab, Dept of Electrical Engineering, IISc Bangalore  (2023- 2024)
• Postdoctoral Researcher, Dept. of Computer and Information Science at Seikei University, Tokyo, Japan (May 2021 – March 2023) 

Dr. Shareef Babu's research focuses on applying  deep learning to Speech Technologies. His key interests include:

• Speaker Diarization in multi speaker conversations
• Speaker Profiling
• Language Diarization in codemix and code switching scenarios
• Automatic speech Recognition
• Speech Pathology

His research aims to bridge the gap between speech technologies and their application in complex real-world scenarios, leveraging interdisciplinary AI-driven approaches

Dr. Shareef believes in a hands-on, research-driven approach to teaching. He emphasizes:

• Application-based learning using real-world datasets
• Adaptive to diverse learning styles and promote an open, respectful classroom.
• Exposing students to cutting-edge research and motivate participation in multidisciplinary projects.
• Use of open-source tools like Python, TensorFlow, and PyTorch for practical implementation
• Bridging the gap between theoretical learning and industry-oriented skills

• Technical Program Committee Member: 29th International Conference on Neural Information Processing (ICONIP 2022), IIT Indore, India.
• Registration Committee Member: International Conference on Advances in Engineering Research and Applications (ICAERA-2016).
• Referee Service:
• IEEE Signal Processing Letters
• IEEE Sensors Journal
• IEEE Transactions on Cybernetics
• IEEE JBHI
• Artificial Intelligence Review (AIRE)
• IEEE Conference on Information and Communication Technology (CICT)-2022
• The 3rd International Conference on Computer, Big Data and Artificial Intelligence (ICCBDAI 2022)
• The Seventh International Conference on Energy Engineering and Environmental Protection
• Asia-Pacific Signal and Information Processing Association (APSIPA ASC 2022) 

• MHRD fellowship for Ph.D, Government of India, December 2013- December 2018 
• Awarded Grant of 280 USD - for the Student volunteer co-ordination in ICASSP 2019, Brighton, UK. May 2019. 
• IEEE Signal Processing Society - Student Travel Grant 2016 for attending IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), 2016, Salerno, Italy. 
• TEQIP-II International Travel Grant- Student Travel Grant 2016 for attending IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), 2016, Salerno, Italy. 
• Won First Prize in National Level Student Technical Symposium (INTERACT2K10), Anil Neerukonda Institute of Technology, Visakhapatnam, A.P, India. 2010 

Professional Services

• Reviewer : Journal of Speech Commnication
• Reviewer: Interspeech 2021-2024
• PC Member: Annual conference on Intelligent User Interfaces (IUI) 2022-2024
• Reviewer: SPECOM 2023
• Reviewer: IEEE CONNECT 2020 

• Gave a talk on DIarization of SPeaker and LAnguage in Conversational Environments (DISPLACE)  at EECS symposium, IISc Bangalore, April 2024.  
• Presented a poster at  Interspeech 2024 Kos Islands, Greece, September 2024.
• Presented a poster at  ICASSP 2019, Brighton, UK, May, 2019.
• Presented a poster at 2017 IEEE TENCON, Penang, Malaysia, November, 2017.
• Presented a poster at IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), Salerno, Italy, September 2016.
• Presented a paper at IEEE 22nd Annual International Conference on Advanced Computing and Communication (ADCOM,) Bangalore, India, September, 2016.
• Attended Interspeech 2018, Hyderabad, India, September, 2018.
• Mentored students in research projects 

Key Publications 

1. MDF-DTA: A Multi-Dimensional Fusion Approach for Drug-Target Binding Affinity Prediction - Journal of Chemical Information and Modeling, 2024. 
2. KG-DTA: A knowledge graph-based meta-path learning framework for predicting drug-target binding affinity - IEEE AI-ML Systems, 2024. 
3. Trans-ARG: Predicting Antibiotic Resistance Genes with a Transformer-Based Model - IEEE AI-ML Systems, 2024. 
4. GNN-ARG: A Graph Neural Network-based Framework for Predicting Antibiotic Resistance Genes - IEEE Big Data, 2024. 
5. ESM-ARG: Identification and Classification of Antibiotic Resistance Genes using ESM-2 and Machine Learning - NAR Genomics and Bioinformatics, 2024 (Under Revision). 
6. Machine learning for automated classification of lung collagen in a urethane-induced lung injury mouse model - Biomedical Optics Express, 2024. 
7. Molecule generation toward target protein (SARS-CoV-2) using reinforcement learning-based graph neural network via knowledge graph - Network Modeling Analysis in Health Informatics and Bioinformatics, 2023. 
8. Generating novel molecules for target protein (SARS-CoV-2) using drug–target interaction based on graph neural network - Network Modeling Analysis in Health Informatics and Bioinformatics, 2022. 
9. GAN for synthesizing CT from T2-weighted MRI data towards MR-guided radiation treatment - Magnetic Resonance Materials in Physics, Biology and Medicine, 2021. 
10. Training Generative Adversarial Networks (GANs) over Parameter Server and Worker Node Architecture - International Conference on Machine Learning and Big Data Analytics, 2022. 
11. Modified GAN for image quality enhancement of low-resolution images - International Workshop on UAV Swarms for Internet of Vehicles, IEEE ANTS, 2023. 
12. Transfer Learning Based Approach for Pneumonia Detection Using Customized VGG16 Deep Learning Model - International Conference on Internet of Things and Connected Technologies, 2021. 
13. Deep-learning based mobile-traffic forecasting for resource utilization in 5G network slicing - International Conference on Internet of Things and Connected Technologies, 2020. 
14. Web Service Selection Mechanism in Service Oriented Architecture based on Publish Subscribe Pattern in FOG environment - International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems, 2020. 
15. ESM-ARG: Identification and Classification of Antibiotic Resistance Gene through Evolutionary Scale Modelling (ESM-2) and Machine Learning - NAR Genomics and Bioinformatics, 2024 (Under Revision). 

shareef@ddn.upes.ac.in