Dr. Dhruv Sharma | Deep Learning | Best Researcher Award

Amity University | India

Dr. Dhruv Sharma is an assistant professor at the Amity Centre for artificial intelligence, Amity university, noida, uttar pradesh, india. He earned his Ph.d. in electronics and communication engineering from Delhi technological university (dtu), specializing in machine learning, computer vision, and multimodal ai. his academic and research journey reflects a deep commitment to advancing artificial intelligence through innovative methodologies in signal processing, natural language processing, and deep-learning architectures. With a total of 7 publications in reputed sci and scopus-indexed journals, dr. sharma has made impactful contributions to the fields of intelligent perception and vision-language fusion. his research on multimodal radiology report generation, conducted in collaboration with the rajiv gandhi cancer institute and research centre, exemplifies his interdisciplinary approach to real-world problem-solving, Deep Learning . his scholarly influence is evidenced by 109 citations, an h-index of 6, and an i10-index of 3, demonstrating consistent research quality and impact. He has also published one patent and actively serves as a reviewer for leading ieee, elsevier, and springer journals. Dr. Sharma has been honored with the commendable research award and the premier research award from dtu, recognizing his excellence in artificial intelligence research and innovation.

Profiles: Orcid | Google Scholar

Featured Publications

Sharma, D., Dhiman, C., & Kumar, D. (2025, October). UnMA-CapSumT: Unified and multi-head attention-driven caption summarization transformer. Journal of Visual Communication and Image Representation.

Sharma, D., Dhiman, C., & Kumar, D. (2024, July). FDT−Dr2T: A unified Dense Radiology Report Generation Transformer framework for X-ray images. Machine Vision and Applications.

Sharma, D., Dhiman, C., & Kumar, D. (2024, May 30). Control with style: Style embedding-based variational autoencoder for controlled stylized caption generation framework. IEEE Transactions on Cognitive and Developmental Systems.

Rautela, K., Sharma, D., Kumar, V., & Kumar, D. (2024, January). Obscenity detection transformer for detecting inappropriate contents from videos. Multimedia Tools and Applications.

Sharma, D., Dhiman, C., & Kumar, D. (2024, January). XGL-T transformer model for intelligent image captioning. Multimedia Tools and Applications.

Mrs. Chittepu Sireesha - Deep Learning - Best Researcher Award

SR University - India

Author Profile

SCOPUS

ORCID

Summary

Sireesha Chittepu is a seasoned academic with over 15 years of teaching experience in computer science and engineering. Her educational background includes a B.Tech and M.Tech in software and computer sciences, and she is currently pursuing a Ph.D. in Computer Science and Engineering at SR University. Throughout her career, she has demonstrated strong proficiency in subjects ranging from data structures to NLP and software testing. Notably, she has contributed significantly to institutional development through her roles as a coordinator for national-level hackathons, class mentor, and virtual lab leader in collaboration with IITH. Her research interest is expanding into areas that blend software innovation with applied domains such as power electronics, where she aims to enhance the interaction between software systems and hardware frameworks. She has also designed internal tools such as attendance and feedback systems to streamline academic administration.

Early academic pursuits

Sireesha Chittepu laid the foundation of her academic journey with a strong focus on the sciences, securing 85.6% in her Intermediate studies and 82% in her SSC. She pursued her B.Tech in Computer Science and Information Technology from Rajiv Gandhi Memorial College of Engineering and Technology under JNTU, achieving 70%. Further strengthening her expertise, deep learning she completed an M.Tech in Software Engineering from VNR Vignana Jyothi Engineering College, Hyderabad, with 78%. Currently, she is pursuing a Ph.D. in Computer Science and Engineering from SR University, Telangana, aligning her research with cutting-edge trends including power electronics, AI integration, and automation.

Professional endeavors

With over 15 years of teaching experience, Sireesha Chittepu has been a cornerstone in the academic development of countless students. Her journey began in 2003 and includes tenure at Alpha College of Engineering, Sree Nidhi Institute of Science and Technology, and Stanley College of Engineering and Technology for Women. Since 2015, deep learning she has been serving as an Assistant Professor at Vasavi College of Engineering, Hyderabad, demonstrating excellence in pedagogy and department-level coordination. Her professional engagements frequently intersect with power electronics, where she integrates software systems to improve learning tools and virtual lab environments.

Contributions and research focus

Sireesha’s teaching expertise spans a wide range of computer science subjects such as Compiler Construction, Data Structures, Software Engineering, and Natural Language Processing. She has developed and implemented innovative tools such as an attendance tracking system and a feedback management system, both of which enhance academic management deep learning. Her research focus aligns with emerging technologies and includes interdisciplinary studies where software engineering intersects with hardware systems like power electronics, emphasizing system-level integration and smart computing applications.

Impact and influence

In her role as Department Coordinator for Hackathons, Co-curricular and Extracurricular Activities, and SPOC for Smart India Hackathons (2019–2020), Sireesha has mentored students in national-level innovation challenges. Her coordination with institutions like IIT-Hyderabad for virtual labs reflects her impact on advancing academic infrastructure. She also contributes to curriculum development and exam preparation, influencing academic delivery deep learning across several institutions. These contributions indirectly support power electronics education by encouraging cross-domain thinking and system-oriented learning approaches among students.

Academic cites

While her Ph.D. is ongoing, Sireesha Chittepu's academic involvement includes preparing university-level question papers, developing lesson plans, and assessing student performance through structured evaluation methods. Though no formal citation index was mentioned, her continuous evaluation roles, seminar engagements deep learning, and project mentorships suggest a strong academic presence that is evolving towards publication and citation in future academic platforms.

Legacy and future contributions

Sireesha aims to bridge the gap between education and innovation, with a long-term vision of contributing to academia through research, digital tools, and cross-disciplinary teaching. Her future goals include publishing impactful research, particularly in the convergence of software engineering and power electronics, and mentoring future educators and deep learning researchers. As she continues her doctoral research, she is poised to leave a legacy defined by practical innovation, academic excellence, and a deep commitment to student-centric learning.

Notable Publications

Title: Enhancing Medicinal Plant Prediction Through Deep Neural Network Algorithms
Authors: Munigala Swapna, Sireesha Chittepu, Sanjana Gavada, Sreeja Barigela
Publication: Communications in Computer and Information Science (CCIS) – Book Chapter
Year: 2025
Title: Improving Air Quality Prediction: A Study on Data-Driven Techniques and Advanced Sensing Technologies
Authors: Yeshwanth Reddy, C. Sireesha
Publication: Lecture Notes on Data Engineering and Communications Technologies – Book Chapter
Year: 2025
Title: Dynamic Conditional Encoding and Feature Frequency Parsing in Diffusion Probabilistic Models for Diabetic Foot Ulcer Detection Using Thermographic Imaging
Authors: Kousar Nikhath A, Sireesha C, Swapna M, Vijayetha Thoday, Esther Rani D
Publication: Journal of Biomedical Photonics & Engineering
Date: 2025-03-31
Title: A ResNet Based Plant Disease Diagnosis Platform
Authors: Sireesha Chittepu, Suchith B, Deepthi M
Publication: 2025 7th International Conference on Signal Processing, Computing and Control (ISPCC)
Date: 2025-03-06
Title: Enhancing the Surveillance, Assessment, and Tracking of Mental Health and Well-being Using Deep Learning Techniques
Authors: Sireesha Chittepu, Sheshikala Martha
Publication: 2025 7th International Conference on Signal Processing, Computing and Control (ISPCC)
Date: 2025-03-06

Conclusion

Sireesha Chittepu's career reflects a commitment to academic excellence, hands-on innovation, and student empowerment. Her proactive involvement in research, curriculum design, and co-curricular coordination showcases her holistic approach to education. As she continues her Ph.D., her contributions are expected to deepen, particularly in interdisciplinary research areas including power electronics, where her experience in software systems can offer new insights. Looking ahead, Sireesha is well-positioned to influence future educational practices, mentor the next generation of engineers, and contribute meaningfully to research that connects computation with real-world systems.