Machine Intelligence: Curriculum and Research Perspective at PES Prof Dinkar Sitaram Prof K V Subramaniam

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 Semester 3 Foundations of Statistics Semester 4 Linear Algebra Electives Semester 6 Data Mining Machine Learning Multi-Core Programming Semester 7 Big Data Technologies Natural Language Processing Special Topics After Semester 4; 2 credits R programming Mini projects

MI - CS Curriculum - MTech Core Machine Learning Electives Big DataData Analytics Specializations Big Data & IOT Offered by CCBD Additional Big Data Electives

MI  Research Domains  KaNOE –Knowledge Analytics and Ontological Engineering  CCBD – Cloud Computing and Big Data  Algorithms MI ApplicationsSystems for MIMI Algorithms

MI  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