Assistant Professor

Dr Sarvani Anandarao

Department of Computer Science and Engineering

Interests

  • Data Mining
  • Metaheuristic Optimization
  • Machine Learning and Deep Learning

Faculty Details

Education

2011

JNTUK
BTech

2014

JNTUK
MTech

2024

VIT University, Chennai
PhD

Experience

  • 2016-2024 – Senior Assistant Professor, Lakireddy Bali Reddy College of Engineering (Mylavaram, AP)

Research Interest

  • My area of interest encompasses a broad spectrum of deep learning, machine learning, and data mining techniques, with a particular focus on text mining and the processing of tweets. I am passionate about developing advanced algorithms for extracting meaningful insights from vast amounts of unstructured text data, leveraging state-of-the-art neural networks and natural language processing (NLP) methods. This includes exploring sophisticated deep learning models like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to enhance feature extraction and temporal analysis.

Awards & Fellowships

  • 2023 – Best Teacher Award – Lakireddy Bali Reddy College of Engineering

Memberships

  •  IEEE

Publications

 
  • Sarvani Anandarao, & Sweetlin Hemalatha Chellasamy. Nature Inspired-Based Remora Optimization Algorithm for Enhancement of Density Peak Clustering. Cogent Engineering, 10(2), Taylor & Francis. (SCIE, Web of Science, Clarivate Analysis) (2023).
  • Sarvani, A., Reddy, Y.S., Reddy, Y.M., Vijaya, R., & Lavanya, K. A Multi-level Optimized Strategy for Imbalanced Data Classification Based on SMOTE and AdaBoost. In Proceedings of Data Analytics and Management. ICDAM 2023. Springer Lecture Notes in Networks and Systems, vol 787, (2023)
  • Sarvani Anandarao, Polani Veenadhari, Gudivada Sai Priya, & Ginjupalli Raviteja. IPSO-SMOTE-AdaBoost: An Optimized Class Imbalance Strategy Using Boosting and PSO Techniques. Springer Lecture Notes in Networks and Systems (LNNS, volume 537). (2023).
  • Sarvani Anandarao, et al. Assessing the Influence of Memory-Based Collaborative Filtering Methods on Contextual Segments in Multicriteria Recommender Systems. Journal of Theoretical and Applied Information Technology, 101(13). (2023).
  • Sarvani Anandarao, & Sweetlin Hemalatha Chellasamy. A Comprehensive Study on Density Peak Clustering and Its Variants. International Journal of Intelligent Systems and Applications in Engineering, 11(2), 216-224. (SCOPUS) (2023).
  • Sarvani Anandarao, & Sweetlin Hemalatha Chellasamy. Hot Topic Detection in Tweets Using CNN-LSTM Classifier and Modified Bald Eagle Search Algorithm. Telematique, 4438-4453. (Web of Science, SCI) (2023).
  • Sarvani Anandarao, Madhavi Reddy, & Lavanya Kampa. Two-level Filtering Method with Extended Lasso and Information Gain in Microarray Data Analysis. International Conference on Inventive Computation Technologies (ICICT), IEEE, pp. 585-590. (SCOPUS) (2022).
  • A. Sarvani, Shaik Anjum Javeariya, Pathipati Swathi Lakshmi, & Venugopal Boppana. Behavior Based Machine Learning Approaches to Identify State-Sponsored Trolls on Twitter. Mathematical Statistician and Engineering Applications, 71(3), 228-236. (SCOPUS) (2022).
  • Sarvani Anandarao, & Sweetlin Hemalatha Chellasamy. Detection of Hot Topic in Tweets Using Modified Density Peak Clustering. Ingénierie des Systèmes d'Information, 26(6), ISSN: 1633-1311. (SCOPUS) (2021).
  • Sri Hari Nallamala, Usha Rani Bajjuri, Sarvani Anandarao, & Dr. D. Durga Prasad.. A Brief Analysis of Collaborative and Content Based Filtering Algorithms Used in Recommender Systems. IOP Conference Series: Materials Science and Engineering, IOP Publishing, Vol. 981. (SCOPUS) (2021)
  • Nagaraju Devarakonda, Sarvani Anandarao, Raviteja Kamarajugadda, & Yingxu Wang.. Unique Dragonfly Optimization Algorithm for Harvesting and Clustering the Key Features. 2019 IEEE 18th International Conference on Cognitive Informatics & Cognitive Computing (ICCI CC)*, ISBN: 978-1-7281-1419-4. (SCOPUS) (2020)
  • Sarvani Anandarao, Nagaraju Devarakonda, Unique Whale Optimization Algorithm for Harvesting and Clustering the Key Features. Lecture Notes in Electrical Engineering, Springer, Singapore, Volume 601, ISBN: 978-981-15-1420-3. (SCOPUS) (2020).
  • Sarvani Anandarao, et al.. Anomaly Detection Using K-means Approach and Outliers Detection Technique. Soft Computing: Theories and Applications (SOCTA 2017), Springer AISC series, Advances in Intelligent Systems and Computing, Volume 742, ISBN: 978-981-13-0589-4. (SCOPUS) (2018)
  • Sarvani Anandarao, et al. A Refined K-Means Technique to Find the Frequent Item Sets. Cognitive Science and Artificial Intelligence, Springer Briefs in Applied Sciences and Technology (ICCSAI-2017), Springer, Singapore, ISBN: 978-981-10-6698-6. (SCOPUS) (2017).
  • Sarvani Anandarao, et al. Clustering the Polymorphic Malware Traces. 2017 International Conference on Algorithms Methodology Models and Applications in Emerging Technologies (ICAMMAET), IEEE Xplore, ISBN: 978-1-5090-3378-2. (SCOPUS) (2017).

Contact Details

  • E-mail id: sarvani.a@srmap.edu.in
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