Associate Professor of KLEF- KL University Vijayawada Campus Andhra Pradesh, India
Dr. Bechoolal 🌟 is an esteemed Associate Professor in Computer Science/Data Science with a passion for inspiring students through a deep understanding of technology and research. With a solid academic foundation that includes a PGP in Data Science from Purdue University and multiple PhDs in Information Systems and Computer Science 🎓, he brings a wealth of expertise to his teaching and research. Dr. Bechoolal has extensive experience in various institutions, from KLEF KL Deemed University to Western College 🏫, and has made significant contributions through his numerous research publications and certifications 🏅. His interests span Machine Learning, Data Science, and programming languages, and he actively engages in projects that explore digital transformation and its societal impacts 💻🔍. Fluent in English and Hindi 🇬🇧🇮🇳, he continues to advance knowledge and inspire the next generation of tech professionals.
Publication profile
Education
Dr. Bechoolal 🎓 is a distinguished academic with a rich educational background in Computer Science and Data Science. He earned a PGP in Data Science from Purdue University 🌟, where he specialized in data regression models and predictive data modeling. Dr. Bechoolal holds multiple PhDs—one in Information Systems from the University of Mumbai and another in Computer Science from SJJT University 🧠. His foundational studies include a Master of Technology in Computer Science from AAI-Deemed University, a Master of Computer Applications from Banaras Hindu University, and an undergraduate degree in Statistics from MG. Kashi Vidyapeeth University 📚. His continuous quest for knowledge is also reflected in his various certifications, including Machine Learning from Stanford University and an IBM Data Science Professional Certificate 🏅.
Academic Qualification
- 📜 PGP in Data Science (2020-2021) from Purdue University, USA – Specializing in data regression models, predictive data modeling, and accuracy analyzing using machine learning.
- 📜 PhD in Information System (2015-2019) from the University of Mumbai, India – Research Area: Data Science.
- 📜 PhD in Computer Science (2011-2015) from SJJT University, India – Research Area: Machine Learning.
- 📜 Master of Technology (M. Tech) in Computer Science and Engineering (2004-2006) from AAI-Deemed University, Allahabad, India.
- 📜 Master of Computer Application (MCA) (1995-1998) from Institute of Science, Banaras Hindu University (BHU), India.
- 📜 Graduation (Statistics-Hons) (1990-1993) from the Department of Mathematics and Statistics, MG Kashi Vidyapeeth University, India.
Data Science Certifications and Training
- 🎓 Machine Learning, Stanford University, USA (2020)
- 🎓 IBM Data Science Professional Certificate (2020)
- 🎓 Data Science and Big Data Analytics (2019), ICT Academy, Govt. of India
- 🎓 Security Fundamentals, Microsoft Technology Associate (2017)
- 🎓 Intelligent Multimedia Data Warehouse and Mining (2009), University of Mumbai
- 🎓 Python Programming (2017), University of Mumbai, India
Teaching Interest
- 📘 Data Science/Machine Learning
- 📘 Database 📘 C/C++/Python Programming Languages
- 📘 Software Engineering
Research Interest
- 🔍 Machine Learning
- 🔍 Data Science
Computer Science/Data Science Skills
💻 Machine Learning, Data Visualization, Big Data Analytics
📊 Predictive Modelling: Supervised Learning (Linear and Logistic Regression, Decision Tree, Support Vector Machine (SVM), Naïve Bayes Classifiers), Unsupervised Learning (K-Means clustering, principal components analysis (PCA))
💻 Programming Languages: Python (NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn), SPSS, R-Programming
💻 Operating Systems/Platforms: UNIX/LINUX, WINDOWS, MS-DOS
💻 C/C++, CORE JAVA Programming Languages
💻 DBMS/RDBMS: Oracle, SQL, MySQL, NoSQL
Publication top notes
- Improving migration forecasting for transitory foreign tourists using an Ensemble DNN-LSTM model
Authors: Nanjappa, Y., Kumar Nassa, V., Varshney, G., Pandey, S., V Turukmane, A.
Journal: Entertainment Computing
Year: 2024
Citations: 0 📅
- Using social networking evidence to examine the impact of environmental factors on social followings: An innovative Machine learning method
Authors: Murthy, S.V.N., Ramesh, P.S., Padmaja, P., Reddy, G.J., Chinthamu, N.
Journal: Entertainment Computing
Year: 2024
Citations: 0 📅
- Real-Time Convolutional Neural Networks for Emotion and Gender Classification
Authors: Singh, J., Singh, A., Singh, K.K., Samudre, N., Raperia, H.
Conference: Procedia Computer Science
Year: 2024
Citations: 0 📅
- Identification of Brain Diseases using Image Classification: A Deep Learning Approach
Authors: Singh, J., Singh, A., Singh, K.K., Turukmane, A.V., Kumar, A.
Conference: Procedia Computer Science
Year: 2024
Citations: 0 📅
- Fake News Detection Using Transfer Learning
Authors: Singh, J., Sahu, D.P., Gupta, T., Lal, B., Turukmane, A.V.
Conference: Communications in Computer and Information Science
Year: 2024
Citations: 0 📅
- Reliability Evaluation of a Wireless Sensor Network in Terms of Network Delay and Transmission Probability for IoT Applications
Authors: Mishra, P., Dash, R.K., Panda, D.K., Lal, B., Sujata Gupta, N.
Journal: Contemporary Mathematics (Singapore)
Year: 2024
Citations: 0 📅
- TRANSFER LEARNING METHOD FOR HANDLING THE INTRUSION DETECTION SYSTEM WITH ZERO ATTACKS USING MACHINE LEARNING AND DEEP LEARNING
Authors: Upender, T., Lal, B., Nagaraju, R.
Conference: ACM International Conference Proceeding Series
Year: 2023
Citations: 0 📅
- Monitoring and Sensing of Real-Time Data with Deep Learning Through Micro- and Macro-analysis in Hardware Support Packages
Authors: Lal, B., Chinthamu, N., Harichandana, B., Sharmaa, A., Kumar, A.R.
Journal: SN Computer Science
Year: 2023
Citations: 0 📅
- An Efficient QRS Detection and Pre-processing by Wavelet Transform Technique for Classifying Cardiac Arrhythmia
Authors: Lal, B., Gopagoni, D.R., Barik, B., Kumar, R.D., Lakshmi, T.R.V.
Journal: International Journal of Intelligent Systems and Applications in Engineering
Year: 2023
Citations: 0 📅
- IOT-BASED Cyber Security Identification Model Through Machine Learning Technique
Authors: Lal, B., Ravichandran, S., Kavin, R., Bordoloi, D., Ganesh Kumar, R.
Journal: Measurement: Sensors
Year: 2023
Citations: 3 📅📈
