Assistant Professor
Department of Artificial Intelligence and Data Science (AI&DS)
CMR Institute of Technology - Bangalore, India
Email: anushree.g@cmrit.ac.in
Phone: 6364328746
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Brief Profile:
Anushree G is an accomplished academic professional currently serving as an Assistant Professor in the Department of Artificial Intelligence and Data Science at CMR Institute of Technology (CMRIT), Bengaluru. She has a strong passion for Machine Learning and is actively pursuing a Ph.D. in Machine Learning, reflecting her commitment to advancing research and innovation in this rapidly evolving field. Her interests lie in applying intelligent systems to solve real-world problems and in mentoring students toward academic and industry excellence.
Educational Qualification:
MTech in Computer science and Engineering,UVCE
BE in Compter Science and Engeeniring ,EWIT
Experience:
Worked as Assistant Lecturer in NITK Surathkal, Manglore.
Worked as Assistant Professor in AMC Engineering College Bangalore.
Area of Interest:
Machine Learning, Auto ML.
Courses teaching currently/taught
DataStructure and algorithm
Data Mining
Operating System
Web Technology
Design Of Digital System
OOP With Java
Python Programming
C Programming
Event Participated:
Participated in the AICTE sponsored “Faculty Development Program on Data Sciences”, organized by UVCE and ATAL Academy.
Participated in the AICTE sponsored “Faculty Development Program on Artificial Intelligence”, organized by UVCE and ATAL Academy.
Participated in the AICTE sponsored “Faculty Development Program on “Cyber security and Ethical Hacking “, organized by Sambhram institute of Technology.
Publications:
"Audio/Text Aided System Using Sign Language", IJCCN International Journal of Computing, Communications and Networking.
"Keyword selection on Google Ads", International Conference on VLSI, Communication and Computer Networks.
AI-Driven Precision Agriculture: Analysing Its Impact on Crop Yield, Sustainability, and Farm Efficiency
Data Driven Crop Prediction: Combining Ensemble Methods with Interpretable AI
Exploring the Synergy of Quantum-Classical Integration in Machine Learning Algorithms
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