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Certificate Course on Network Science and its Applications
(CCNSA)

February 09 - March 31, 2019

Centre for Advanced Research in Applied Mathematics and Statistics, MAHE, Manipal, India

Network science, or the science of networks, is the study of the theoretical foundations of network structure/dynamic behavior and the application of networks to many sub fields.

Objectives

The objective of the present course is to introduce the science of networks and  to study the subfields of the network science which include social network analysis (SNA), collaboration networks (bibliographic citations, product marketing, online social networks), synthetic emergent systems (power grids, the Internet), physical science systems (phase transition, percolation theory, Ising theory), and life science systems (epidemics, metabolic processes, genetics).

Prerequisite: Basic understanding of the graphs and probability will be helpful although it is not mandatory

Unit 1:  (3 sessions)

Introduction to Network Science and its characteristics – Basics of probability: Definition, properties, conditional probability, random variables and some important distributions – Basics of graphs, characteristics and parameters, types of graphs – Matrices associated with graphs – Spectral properties of graphs – Problems and solutions related to networks, using programming.

Unit 2:  (3 sessions)

Random networks: generation, degree distributions, entropy, properties and analysis, average path length, cluster coefficient and link efficiency – Properties: Diameter, radius – Closeness calculation – Weak ties in random network – Randomization and analysis.

Small world networks: Generation of SWNs, Watts-Strogatz (WS) procedure, degree sequences of SWNs – Properties of SWNs: Entropy vs. Rewiring Probability, Entropy vs. Density, Path length of SWN, Cluster coefficient of SWN, Closeness in SWNs – Path length and fact transition – Navigating small worlds – Weak ties in SWNs.

Unit 3:  (2 sessions)

Scale free networks: Generating scale free networks, Barabasi-Albert network – Scale free network power law – Properties of scale free network: Hub degree vs. density, average path length, closeness, cluster coefficient – Navigation in SFNs: Maximum degree navigation vs. density, Maximum degree navigation vs. Hub degree, Weak ties in scale-free Pointville, and analysis of path length and communication, cluster coefficient, Hub degree.

Network emergence: Open loop emergence, feedback loop emergence. Emergence in different branches of science: Social science, physical science, and biology – Genetic evolution: Hub emergence, cluster emergence – Designer network: Degree sequence emergence, generating networks with given degree sequence – Permutation network emergence – Applications of emergence.

Unit 4:  (2 sessions)

Epidemics models: Kermack-McKendrick model, Epidemic thresholds, SIR model, peak infection density in structured networks, SIS epidemics – Persistent epidemic in the network – Random network epidemic threshold, epidemic threshold in general network, fixed point infection density – Epidemic simulation – Counter measures algorithm – Counter measure seeding strategies, antigen simulation.

Unit 5:  (2 sessions)

Network Risk – Critical Node Analysis – Game Theory Considerations – The General Attacker–Defender Network Risk Problem – Critical Link Analysis – Stability Resilience in Kirchhoff Networks.

Static Models in Biology – Dynamic Analysis – Protein Expression Networks – Mass Kinetics Modeling.

Seminars may be chosen from the following topics:

Synchrony: A Cricket Social Network, Kirchhoff Networks, Pointville Electric Power Grid

Influence Networks: Anatomy of Buzz, Power in Social Networks, Conflict in I-Nets, Command Hierarchies, Emergent Power in I-Nets

Vulnerability: Network Risk, Critical Node Analysis, Game Theory Considerations, The General Attacker–Defender Network Risk Problem, Critical Link Analysis, Stability Resilience in Kirchhoff Networks.

Text books & References:
  1. Bapat RB. Graphs and matrices. New York: Springer; 2010.
  2. Deo N. Graph theory with applications to engineering and computer science. Courier Dover Publications; 2017.
  3. Lewis TG. Network Science: Theory and applications. John Wiley & Sons; 2011.
  4. Newman M. Networks. Oxford university press; 2018.
  5. Ramachandran S, Arumugam S. Invitation to graph theory. Scitech publication pvt. Ltd, Reprint. 2009.

Evaluation Method:

The course is of 3 credit and the performance of any participant will be continuously evaluated in the tutorials, through submission of assignments, and the delivery of seminars. 100% attendance and aggregate grade point of 5 or above is necessary for the successful completion of the course.

Number of seats- 12

Eligibility:

Faculty and Research Scholars of Science, Medicine and Technology having the research interest in the applications of Network Theory, PG and UG students with basic knowledge of graphs and Probability.

Course fee is nil in this academic year. Preference is given to the applicants in the order of faculty members, research scholars and graduate students, as our focus in the present year is to train our in house faculty and build capacity in the subject.

Certificate Course on Network Science and its Applications

February 09 - March 31, 2019

Registration

No Course Fee

Course fee is nil in this academic year. Preference is given to the applicants in the order of faculty members, research scholars and graduate students, as our focus in the present year is to train our in house faculty and build capacity in the subject.

Certificate Course on Network Science and its Applications

February 09 - March 31, 2019

Schedule

Schedule

Course Duration- 12 weeks
Start Date February 09, 2019
Day Every Saturday
Time 2.00 pm – 5.00 pm
Lecture 1.25 Hrs.
Tutorials 1.25 Hrs.

(Changes in schedule are subject to holidays and availability of resource person.)

Certificate Course on Network Science and its Applications

February 09 - March 31, 2019

Speakers

Dr. S. Arumugam
Adjunct Professor
Amrita Vishwa Vidyapeetham, Coimbatore, India

Research Interests: Network Analysis, Graph Theory and its applications, Fuzzy logic and its applications to pattern recognition, Topology , Geometry… Read more
Achievements: He has more than 250 publications and more than 20 books. Most of these books are prescribed as… Read more

Dr. Manjunatha Prasad Karantha
Professor & Coordinator, CARAMS
Manipal Academy of Higher Education, Manipal

Research Interests: Generalized Inverse of Matrices and their Applications, Linear Models, Covariance Matrices and Applications, Nonnegative Matrices, Projective Modules and… Read more
Achievements: He completed his phd in Indian Statistical Institute, Calcutta (July 1993). He has more than 40 publications in… Read more

Dr. Vinay Madhusudanan
Assistant Professor
Manipal Institute of Technology, Manipal

Research Interests: Algebra and Graph Theory Read more
Achievements: Read more

Dr. G. Sudhakara
Professor and HOD, Department of Mathematics
Manipal Institute of Technology, MAHE, Manipal

Research Interests: Graph Theory, Combinatorics, Linear Algebra, Algebra Read more
Achievements: He is a Life-time Member of Ramanujan Mathematical Society since 1995. He has given various talks in national… Read more

Certificate Course on Network Science and its Applications

February 09 - March 31, 2019

Participants

Certificate Course on Network Science and its Applications

February 09 - March 31, 2019

Contact

Contact us at

carams.mahe@gmail.com

Dr. K. Manjunatha Prasad

Coordinator, CARAMS

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