Ph.D.: National Institute of Technology, warangal, Pursuing
PG: M.Tech (Computer Science and Engineering), Jawaharlal Nehru Technical University, Hyderabad, 2014
UG: B.Tech (Information Technology), Jawaharlal Nehru Technical University, Hyderabad, 2011
Teaching Experience: 11 years 4 months
Research Experience: 2 years 6 months
Industry Experience: 1year
Contact Number: 7416945839
BVRITN Employee ID: BVRITN00642
JNTUH Registration ID: 69150404-154132
AICTE Registration ID: 2501285779
- Machine Learning
- Image processing with Deep Learning
- Natural Language Processing
- ACM Annual Membership
- ISTE Lifetime Membership
- Achieved State 4th Rank and National wide 44th Rank in National AI Olympiad Conducted by Talent Sprint part Of Accenture
- Completed Foundations In DATA SCIENCE course from One fourth Labs conducted by PadhAI.com duration of 22 weeks.
- Completed “NASSCOM BIGDATA ANALYTICAL” Training program at VEDIC.
- Successfully Completed the requirements to be recognized as a Microsoft Technology associate for “Introduction to Programming using python”.
- G Uday Kiran, M.Mounika et al. (2023). A Machine Learning Pipeline and Application for Automatic Classification of Clinical Documents. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10), 481–490. https://doi.org/10.17762/ijritcc.v11i10.8512
- Published a paper on Predicting The Winter Olympic Medals: Logistic Regression, JASC Volume VII, Issue VI, June/2020, Page No:80
- U. Kiran, V. Srilakshmi, G. J. P. Reddy, M. Mounika, B. Divya, and H. B. Laxmi, “SynapGraph: A lightweight adaptive spatio-temporal GNN for robust EEG emotion recognition,” in *2026 IEEE International Conference for Convergence in Computing Technology (I3CTCON)*, 2026, pp. 1–6, doi: 10.1109/I3CTCON68242.2026.11507454.
- Venu Gopal, T. Ashwini, M. Mounika, Ch. Lakshmi Vignesh Reddy, Mohd Ghouse, and A. Mahesh Kumar, “A multi-phase reliability-aware framework for human motion-based behavioral evidence analysis,” in *2026 IEEE International Conference for Convergence in Computing Technology (I3CTCON)*, 2026, pp. 1–6, doi: 10.1109/I3CTCON68242.2026.11507181.
- U. Kiran, V. Srilakshmi, M. Mounika, B. Lavanya, B. Priyanka, P. Gudavalli, and S. Dubey, “Exploring the impact of neural architecture search on human pose detection techniques,” in *2025 IEEE International Conference on Contemporary Computing and Communications (InC4)*, 2025, pp. 1–5, doi: 10.1109/InC465408.2025.11256496.
- Kiran, M. Z. Anwar, U. S. Samyuktha, S. Valaboju, M. Mounika, and M. A. Reddy, “Advanced traffic flow optimization for intelligent transportation system,” in *2025 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC)*, 2025, pp. 1–8, doi: 10.1109/ASSIC64892.2025.11158065.
- P. K. Reddy, M. Mounika, and U. Nagavelli, “Edge computing and federated learning: Enhancing privacy and efficiency in cloud-based machine learning systems,” in *2025 International Conference on Next Generation Communication & Information Processing (INCIP)*, 2025, pp. 339–345, doi: 10.1109/INCIP64058.2025.11020061.
- Srilakshmi, V., Uday Kiran, G., Mounika, M., Akhil, V.N.S., Manasa, M., “Evolving Convolutional Neural Networks with Meta-Heuristics for Transfer Learning in Computer Vision”, Procedia Computer Science, Vol 230, pp. 658-668, 2023.
- Sirisha, A. Kiran, M. Arshad and M. M, “Automating ML Models Using MLOPS,” in 2024 International Conference on Advancements in Smart, Secure and Intelligent Computing (ASSIC), Bhubaneswar, India, 2024, pp. 1-5, doi: 10.1109/ASSIC60049.2024.10507923.
keywords: {Adaptation models;Automation;Machine learning algorithms;Computational modeling;Pipelines;Machine learning;Production} - Mounika, S. H. Sharma, S. Harshini, and G. Srilaxmi, “Lung cancer detection using convolutional neural networks and virtual reality,” in *2024 3rd International Conference on Automation, Computing and Renewable Systems (ICACRS)*, 2024, pp. 1507–1512, doi: 10.1109/ICACRS62842.2024.10841699.
- Mounika, S. P. K. Reddy, A. Abhinaya, and G. Akshay, “Quantum machine learning: Bridging the gap between theory and practice,” in *Intelligent Computing and Big Data Analytics*, vol. 2234, *Communications in Computer and Information Science*, pp. 89–105, 2024, doi: 10.1007/978-3-031-74682-6_7.
- P. K. Reddy, M. Mounika, J. Harikiran, and B. S. Chandana, “Design of an improved model for pothole detection using multiple scale CNNs and deep neural decision forest ensemble process,” in *2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)*, 2024, pp. 1–6, doi: 10.1109/SCOPES64467.2024.10991311.
- Das, N. S. Dey and M. Mounika, “Automated Brain Tumor Segmentation in MRI : An Enhanced Mask Generation Approach,” 2023 7th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Kirtipur, Nepal, 2023, pp. 891-897, doi: 10.1109/I-SMAC58438.2023.10290265.
- Published a paper on Object Detection Using Single shot multibox detector in world Conference, WCSEM.
- Published a patent on ”Transformer-Based DeepFake Detection System Using Spatio-Temporal Features”.
- Published a patent on “Multi-Objective NAS for Edge Latency in Deep Models”.
- Published a patent on “Blockchain, Cloud, AI, ML based Criminal Digital Forensic Investigation Application”.
- Published a textbook on block chain Technology and decentralized apps in advanced application by independent publishers
- Successfully Completed NPTEL Course Neural Networks for ”Computer Vision and Neural Language Processing” with Elite+Silver.
- Successfully Completed NPTEL Course “Introduction to Large Language Models (LLMs)”.
- Sucessfully Completed Swayam Online Course Certification On “Data Mining”
- Successfully Completed NPTEL Course “Deep Learning With Computer Vision”.
- Suceessfully Complted NPTEL Course”Machine Learning and Deep learning Applications.
- One Week FDP for “Exploratory Data Analysis for Data Science with R Software”.
- One Week FDP for “Neural Networks for Computer Vision and Natural Language Processing”.
- One Week FDP for “Introduction to Large Language Models (LLMs)”.
- One Week FDP for “Responsible & Safe AI Systems”.
- One Week FDP for “Mathematics for Machine Learning”
- Three day national level workshop FDP for “MACHINE LEARNING AND PREDICTIVE ANALYTICS USING R-PROGRAMMING”.
- 5day FDP for“HADOOP “
- 5 day FDP for “Data Science and Big Data Analytics”
- 2 day FDP for “Introduction on Python Programming”5. 6 day FDP for “Outcome Based Education & NBA Accreditation”.
- 6 day FDP for “Artificial Intelligence”.
- 6 day FDP for “Advanced Data Science and its Applications”.
- One Week FDP for “Introduction to Machine Learning Developing Potentials-Emerging Technologies of computer science”.
- 5 day FDP for “DATA SCIENCE BEHIND NATURAL LANGUAGE PROCESSING”.
- 6 day FDP on “Artificial Intelligence Applications through Machine Learning”.