Dheeraj Kodati

Dr. Dheeraj Kodati is an Assistant Professor in the Department of Computer Science and Engineering at Mahindra University. He holds a Ph.D. in Computer Science and Engineering from NIT Warangal, an M.S. in Computer Science from the University of Central Missouri, USA, and a B.Tech. in Computer Science and Engineering. He was a DAAD Postdoctoral Fellow in Germany and previously served as an Assistant Professor at ABV-IIITM Gwalior. Dr. Kodati has more than 10 years of experience in the IT industry, including software engineering and Research and Development (R&D), along with over 2 years of teaching and academic experience. His core expertise includes Artificial Intelligence, Deep Learning, Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, and Explainable and Interpretable AI.

His research focuses on developing AI and LLM-based methods for analysing textual, biomedical, and multimodal data, with particular emphasis on Healthcare AI, mental health informatics, Bioinformatics, and Multimodal AI. His work explores contextual language understanding, emotion and behavioural analysis, explainability, and trustworthy AI. His broader research interests include data analytics, biomedical informatics, and intelligent healthcare systems.

• Ph.D. (CSE), National Institute of Technology, Warangal, India, Feb, 2025
• MS (CS), University of Central Missouri, USA, May, 2016
• B.Tech. (CSE) Bharat Institute of Engineering and Technology, Hyderabad, India, April, 2014

• Dheeraj Kodati and T. Ramakrishnudu, “Negative Emotions Detection on Mental Health Texts Using the MHA-BCNN Model,” Expert Systems with Applications, vol. 182, 2021, Art. no. 115265. DOI: 10.1016/j.eswa.2021.115265.
• Dheeraj Kodati and T. Ramakrishnudu, “Identifying Suicidal Emotions on Social Media Through Transformer-Based Deep Learning,” Applied Intelligence, vol. 53, no. 10, pp. 11885–11917, 2023. DOI: 10.1007/s10489-022-04060-8.
• Dheeraj Kodati and C. M. Dasari, “Negative Emotion Detection on Social Media During the Peak Time of COVID-19 Through Deep Learning with an Auto-Regressive Transformer,” Engineering Applications of Artificial Intelligence, vol. 127, 2024, Art. no. 107361. DOI: 10.1016/j.engappai.2023.107361.
• Dheeraj Kodati and T. Ramakrishnudu, “Advancing Mental Health Detection in Texts via Multi-Task Learning with Soft-Parameter Sharing Transformers,” Neural Computing and Applications, vol. 37, no. 5, pp. 3077–3110, 2025. DOI: 10.1007/s00521-024-10753-7.
• Dheeraj Kodati and T. Ramakrishnudu, “Emotion Mining for Early Suicidal Threat Detection Using Context Dynamic Masking-Based Transformer,” Multimedia Tools and Applications, 2024.
• Dheeraj Kodati and C. M. Dasari, “Detecting Critical Diseases Associated with Higher Mortality in Electronic Health Records Using a Hybrid Attention-Based Transformer,” Engineering Applications of Artificial Intelligence, 2025.
• T. Gadekallu, Dheeraj Kodati, et al., “Agentic AI in Healthcare 5.0: From Autonomous Systems to Symbiotic Care Ecosystems,” IEEE Internet of Things Journal, 2026.
• S. M. Yimam, U. Naseem, R. Geislinger, Dheeraj Kodati, C. Biemann, Tanmoy Chakraborty, et al., “POLAR-SemEval-26 Task,” Proceedings of the 20th International Workshop on Semantic Evaluation, ACL, 2026.
• S. M. Yimam, U. Naseem, R. Geislinger, Dheeraj Kodati, C. Biemann, Tanmoy Chakraborty, et al., “Detecting Multilingual, Multicultural and Multievent Online Polarization,” Proceedings of the 20th International Workshop on Semantic Evaluation, 2026.
• Dheeraj Kodati and B. S. Lakkireddy, “Identifying Contextual Triggers in Hate Speech Texts Using Explainable Large Language Models,” GlobalNLP–RANLP, 2025.
• C. M. Dasari, Dheeraj Kodati, N. Mittapally, S. Reddy A, and K. Reddy P, “Graph Neural Networks Based Explainability of Drug-Target Interactions,” BICOB, 2025.
• D. Sah, P. Sankar, Dheeraj Kodati, and C. M. Dasari, “Kmer-Based DNA Sequence Image Representation for Viral Disease Prediction,” ICBBB, 2025.
• M. Jahnavi, K. Chandana, P. C. Nair, and Dheeraj Kodati, “Classification of News Category Using Contextual Features,” ICKECS, IEEE, 2024.
• Dheeraj Kodati and T. Ramakrishnudu, “Detecting Sarcasm and Hate-Related Texts Using Two-Step Multi-Class Classification,” ICSET, 2024.
• Dheeraj Kodati, “Analysing COVID-19 News Influence on Social Media Aggregation,” International Journal of Advanced Trends in Computer Science and Engineering, 2020.
• A. Vidyavani, Dheeraj Kodati, M. Reddy, and K. H. Kumar, “Object Detection Based on YOLOv3 Using Deep Learning Networks,” International Journal of Innovative Technology and Exploring Engineering, 2019.
• M. P. N. Kumar and Dheeraj Kodati, “An Inverse Optimal Control Approach for Nonlinear System Design Using ANN,” World Academy of Science, Engineering and Technology, 2014.
• Pavan Parvatam, P. Krishna Reddy A, and Dheeraj Kodati, “Component Based Framework to Simplify Legal Documents: An Experiment on Indian Judgments,” 14th International Conference on Big Data and Artificial Intelligence (BDA 2026), 2026.
• Harshita Yadav, K. K. Pattanaik, and Dheeraj Kodati, “Resource-Aware Lightweight Runtime Adaptation for Edge-Cloud DNN Partitioning,” IEEE TENCON, 2026, Accepted.
• Dheeraj Kodati and C. M. Dasari, “Detecting Contextual Words for Emotion Mining from Suicide Related Texts Using Hierarchical Explainable Large Language Models,” SSRN Preprint, 2025.

• Assistant Professor, Mahindra University, Department of Computer Science and Engineering, Hyderabad, India, Sept 2026- Present
• Assistant Professor, Atal Bihari Vajpayee–Indian Institute of Information Technology and Management (ABV-IIITM), Department of Information Technology, Gwalior, India, Dec 2025-Aug 2026
• Assistant Professor, Mahindra University, Department of Computer Science and Engineering, Hyderabad, India, Jan 2025- Dec 2025
• Postdoc, University of Hamburg, Germany, Nov 2024-Dec 2025
• Senior Manager, Apollo Computing Laboratories, Hyderabad, India, Dec 2019- Jan 2025
• Software Project Consultant, Mission Bhagiratha, Government of Telangana, Hyderabad, India, Aug 2017-Dec 2019
• Java Programmer, Inverselogix, Hyderabad, India, June 2016-July 2017
•  Java Programmer, Scepter Technologies, Baltimore, Maryland, USA, Jan 2015-May 2015
• Software Engineer, Apollo Computing Laboratories, Hyderabad, India, April 2014-Dec 2014

My research areas include Artificial Intelligence, Deep Learning, Natural Language Processing (NLP), Large Language Models (LLMs), Generative AI, Explainable and Interpretable AI, Data Analytics, Healthcare AI, Bioinformatics, and Multimodal AI. My current research focuses on developing LLM and deep learning-based methods for contextual understanding and analysis of textual, biomedical, and multimodal data. Particular emphasis is placed on mental health informatics, emotion and behavioural analysis, biomedical data analysis, contextual language understanding, and explainability of AI models using techniques such as SHAP, LIME, and Integrated Gradients. I am also interested in trustworthy AI, multimodal learning, and data-driven decision support for healthcare and other real-world applications.