pellakuri vidyullatha | Computer Vision | Excellence in Research

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Dr .pellakuri vidyullatha | Computer Vision | Excellence in Research

Associate Professor, Koneru Lakshmaiah Education Foundation, India

🔬 Short Biography 🌿💊📚

Dr. Pellakuri Vidyullatha is an Associate Professor in the Department of Computer Science and Engineering at Koneru Lakshmaiah Education Foundation (K L Deemed-to-be University), India. She holds a Ph.D. in Computer Science, with her research centered on advanced topics in artificial intelligence, machine learning, data mining, and neural networks. Dr. Vidyullatha has contributed extensively to the field through numerous research publications, particularly focusing on applications of deep learning and image segmentation techniques, including recent work on gastrointestinal tract imaging. She is also actively involved in guiding postgraduate and doctoral students, playing a significant role in academic mentorship and research supervision at the university. Her commitment to quality teaching and impactful research has earned her recognition within the academic community. Dr. Vidyullatha continues to advance knowledge in computational intelligence, contributing to both theoretical developments and practical innovations in AI and data science.

Profile

Orcid

Scopus

🎓 Education

Dr. Pellakuri Vidyullatha holds dual Post-Doctoral Fellowships in Artificial Intelligence—from the University of South Florida, USA (2023–2025) under Dr. Bhuvan Unhelkar, and the Industrial University of Ho Chi Minh City, Vietnam (2022–2023) under Dr. Bui Thanh Hung. She earned her Ph.D. in Computer Science and Engineering from Koneru Lakshmaiah Education Foundation in 2017, after completing her M.Tech in Computer Science and Technology with distinction (82%) from JNTU Anantapur in 2012. Her educational background is deeply rooted in AI, machine learning, and data science, with a continuous commitment to advancing academic excellence and research acumen.

💼 Professional Experience

With over 20 years of academic and research experience, Dr. Vidyullatha is currently an Associate Professor in the Department of Computer Science Engineering at KL University, Andhra Pradesh, since 2017. Prior to that, she served as Assistant Professor at Narayana Engineering College (2006–2017). She has also completed prestigious postdoctoral fellowships in the USA and Vietnam, focusing on computer vision, deep learning, and natural language processing. Dr. Vidyullatha has successfully organized and contributed to numerous international conferences, workshops, and faculty development programs, and she has played key roles in NAAC, NBA, and NIRF-related institutional development.

🛠️ Skills and Editorial Roles

Dr. Vidyullatha specializes in Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing, Quantum Machine Learning, and Big Data Analytics. She is proficient in tools like Python, TensorFlow, Keras, PyTorch, Tableau, and the Hadoop ecosystem. Her pedagogical strengths include flipped learning, inquiry-based learning, project-based learning, and collaborative instruction models. She also holds numerous global certifications from platforms such as Google Cloud, Microsoft Azure, Oracle, and Cisco Networking Academy, and actively participates in global AI challenges on Kaggle and TechGig.

🏅 Awards and Recognition

Dr. Vidyullatha is a multi-award-winning academic, recognized with honors such as the Best Teacher Award (2021–2023) by KL University, Dr. Sarvepalli Radhakrishnan Best Teacher Award, Inspiring Women Award (2023), and the Outstanding Post Doctoral Fellow Award (2023) by Novel Research Academy. She has been appreciated as a keynote speaker, technical session chair, and guest lecturer at various national and international platforms. She also serves as a reviewer for IEEE, InderScience, IJIRST, and other reputed journals and conferences.

Research Focus

Dr. Vidyullatha’s research is centered on advanced AI systems, deep learning models, computer vision, and NLP applications in healthcare, agriculture, and cybersecurity. Her work also spans big data analytics, graph-based algorithms, and recommender systems. With over 72 SCOPUS-indexed publications, 480 citations, and an h-index of 10, she has significantly contributed to scholarly literature. Her most recent works include topics such as emoji-based sentiment analysis, cancer prediction using AI, blockchain communication in IoT, and optimized machine learning models for image segmentation and information retrieval.

🏁conclusion:

In conclusion, Dr. Pellakuri Vidyullatha is highly deserving of the “Excellence in Research” Award. Her commitment to advancing cutting-edge technologies, mentoring future talent, and contributing to the global research community reflects the very essence of this award. With minor enhancements in high-impact publications and funded projects, her profile would be even more formidable on a global scale.

Nisar Hussain | Artificial Intelligence and Machine Learning | Best Researcher Award

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Mr.Nisar Hussain |Artificial Intelligence and Machine Learning|Best Researcher Award

Mr.  Nisar Hussain Instituto Politechnico Nacional, Mexico City, Mexico

Nisar Hussain is a researcher affiliated with the Instituto Politécnico Nacional (IPN) in Mexico City, Mexico. He is currently enrolled in the Doctorate in Computer Science program at IPN’s Centro de Investigación en Computación (CIC), focusing his research on offensive language detection and sentiment analysis in code-mixed text on social media.Throughout his academic career, Hussain has contributed to various studies in the field of Natural Language Processing (NLP). Notably, he co-authored the paper titled “ORUD-Detect: A Comprehensive Approach to Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning–Deep Learning Models with Embedding Techniques,” published in the journal Information in February 2025.In addition to his work on offensive language detection, Hussain has explored other areas of NLP. He co-authored a study on guilt detection in text, which was published in Scientific Reports in July 2023.

Publication Profile

Google scholar

orcid

Education :

Ph.D. in Computer Science (2022-2025, Ongoing)
Instituto Politécnico Nacional, MéxicoMaster’s in Computer Science (2014-2017)
University of Agriculture, Faisalabad, PakistanBachelor of Science in Computer Science (BSCS) (2010-2014)
COMSATS University Islamabad, Sahiwal Campus

Experience :

With 4+ years of experience in developing and deploying ML and NLP systems, I have actively contributed to multiple projects, applying NLP techniques for real-world problem-solving. I have worked with large, complex datasets, implementing hybrid ML-DL approaches for automated text processing, sentiment analysis, and multilingual content understanding. My research collaborations span multiple institutions, focusing on AI-driven solutions for text analysis and detection tasks.

Research Focus :

I specialize in Natural Language Processing (NLP) and Machine Learning, with a particular emphasis on Offensive Language Detection and Sentiment Analysis of Code-Mixed Data. My research explores multilingual and low-resource language models, leveraging and fine-tuning mBERT, XLM-R, IndicBERT, and Google’s BERT-based models. I am particularly interested in hate speech detection, sentiment analysis, language identification, and emotion analysis in complex linguistic environments. My work integrates deep learning techniques, transformers, and hybrid ML-DL models to improve text processing and understanding in diverse multilingual contexts.

Awards:

Published multiple high-impact research papers in leading AI and NLP conferences/journalsActive participant in international AI competitions and workshopsRecognized for contributions to multilingual and low-resource NLP advancements

Publication :

  • Shaheen, M., Awan, S. M., Hussain, N., & Gondal, Z. A. (2019). Sentiment analysis on mobile phone reviews using supervised learning techniques. IJMECS, 11(7), 32.

 

  • Mehak, G., Qasim, A., Meque, A. G. M., Hussain, N., Sidorov, G., & Gelbukh, A. (2025, January). TechExperts (IPN) at GenAI Detection Task 1: Detecting AI-Generated Text in English and Multilingual Contexts. In Proceedings of the 1st Workshop on GenAI Content Detection (GenAIDetect) (pp. 161-165).

 

  • Hussain, N., Qasim, A., Mehak, G., Kolesnikova, O., Gelbukh, A., & Sidorov, G. (2025). Hybrid Machine Learning and Deep Learning Approaches for Insult Detection in Roman Urdu Text. AI, 6(2), 33. https://doi.org/10.3390/ai6020033

 

  • Qasim, A., Mehak, G., Hussain, N., Gelbukh, A., & Sidorov, G. (2025). Detection of Depression Severity in Social Media Text Using Transformer-Based Models. Information, 16(2), 114. https://doi.org/10.3390/info16020114

 

  • Manzoor, M. I., Shaheen, M., Khalid, H., Anum, A., Hussain, N., & Faheem, M. R. (2018). Requirement Elicitation Methods for Cloud Providers in IT Industry. IJMECS, 10(10).

 

  • Hussain, N., & Anees, T. (2018). Development of a novel approach to search resources in IoT. International Journal of Advanced Computer Science and Applications, 9(9).

 

  • Faheem, M. R., Iftikhar, A., & Hussain, N. (2022). Automated Diagnosing of Eye Disease in Real Time. Journal of Computing & Biomedical Informatics, 3(1), 282-288.

 

  • Shaheen, M., Anees, T., Hussain, N., & Obaid, I. (2019, April). A Research on SOA in the IT Industry of Pakistan. In Proceedings of the 2019 ICCTA (pp. 149-154).

 

  • Meque, A. G. M., Hussain, N., Sidorov, G., & Gelbukh, A. (2023). Guilt Detection in Text: A Step Towards Understanding Complex Emotions. arXiv preprint arXiv:2303.03510.

 

  • Tash, M. S., Ahani, Z., Tonja, A., Gemeda, M., Hussain, N., & Kolesnikova, O. (2022, December). Word Level Language Identification in Code-mixed Kannada-English Texts using Traditional Machine Learning Algorithms. In Proceedings of the (ICON) (pp. 25-28).

 

 

 Conclusion

Given their strong publication record, hands-on experience with AI models, and focus on low-resource NLP, the candidate is highly competitive for the Best Researcher Award. Strengthening industry collaborations, increasing research impact, and securing grants will further enhance their research profile.