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Machine Intelligence:
Curriculum and Research
Perspective at PES
Prof Dinkar Sitaram ([email protected])
Prof K V Subramaniam ([email protected])
Overview of Institution
 Founded in 1988
 Formerly PESIT
 Courses offered




B. Tech (CS ~ 300 students per year)
M. Tech (CS – 40 students per year)
MSc [Engg]
PhD
MI - CS Curriculum - BTech
Core
Electives
Special
Topics
Semester 3
Semester 4
• Foundations of
Statistics
• Linear Algebra
Semester 6
Semester 7
• Data Mining
• Machine Learning
• Multi-Core
Programming
• Big Data
Technologies
• Natural Language
Processing
After Semester 4;
2 credits
• R programming
• Mini projects
MI - CS Curriculum - MTech
Core
Machine
Learning
Electives
Big Data
Big Data & IOT
Specializations
• Offered by CCBD
• Additional Big
Data Electives
Data Analytics
MI Research@PES
 Research Domains
 KaNOE –Knowledge
Analytics and Ontological
Engineering
 CCBD – Cloud Computing
and Big Data
 Algorithms
MI Applications
Systems for MI
MI Algorithms
MI Research @PES
 8 PhD Students
 Learning Analytics, Landcover classifcation, Machine Translation,
Escalation Prediction, Face Recognition, Neural Simulation,
Speech Recognition, Graph Databases
 Publications
 Mainly through undergraduate/graduate students
 Patents
 Prof S Natarajan
 Industry Collaboration
 CCBD – GE, Nokia, AMD, HP
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