Vijesh Mohan
Engineer | Photographer | Researcher | A Restless Soul
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"You don't take a photograph, you make it." - Ansel Adams

Canon EOS 550D | 18-55mm | 50mm f1.8 | 55-250mm


"If you optimize everything, you will always be unhappy." - Donald Knuth

Google Summer of Code - 2013

Gephi | Legend Module | Java

A Navigation Algorithm Inspired by Human Navigation

Navigation Algorithm | Complex Networks | Reinforcement Learning

Prediction Of Arrival Of Nodes In A Scale Free Network

Scale Free Networks, Probabilistic Prediction, Differential Core Centrality

NodeJS | Bower | Bootstrap | jQuery | Grunt |

A Weight-Based Personalized Recommendation

Dimensionality Reduction | MovieLens | User Profiling | Network based Idiosyncratic and Collaborative Recommendation

Parallel Search Algorithm in Power Law Networks

Navigation Algorithm | Complex Networks | Graph Theory and Algorithms | Greedy Algorithm


Report Generation | PDFlatex | XML | Python

TweeBuzz - Local Trends in Twitter

Twitter | oAuth | synonym-based ranking

Boredom Detection in a classroom

Quantization of Boredom Level | Difference Method | Noise Computation


"If we knew what it was we were doing, it would not be called research, would it?" - Albert Einstein

  • Navigation Algorithm
  • Complex Networks
  • Reinforcement Learning
Human navigation has been a topic of interest in spatial cognition from the past few decades. It has been experimentally observed that humans accomplish the task of way-finding a destination in an unknown environment by recognizing landmarks. Investigations using network analytic techniques reveal that humans, when asked to way-find their destination, learn the top ranked nodes of a network. In this paper... (more)
  • Scale Free Networks
  • Probabilistic Prediction
  • Differential Core Centrality
Most of the networks observed in real life obey power-law degree distribution. It is hypothesized that the emergence of such a degree distribution is due to preferential attachment of the nodes. Barabasi-Albert model is a generative procedure that uses preferential attachment based on degree and one can use this model to generate networks with power-law degree distribution. In this model, the network is assumed to grow one node every time step. After the evolution... (more)
  • Dimensionality Reduction
  • MovieLens
  • User Profiling
  • Network based Idiosyncratic and Collaborative Recommendation
Personalized Recommendations serve as an important ingredient for several web based systems. These systems generally house a knowledge base containing the metadata about items and users. In this paper, we present an approach for the purpose of... (more)

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