Parallel K-Means Clustering Using Mapreduce: Implemented Parallel K-Means Clustering Using Mapreduce.
K-means algorithm is the most well-known and commonly used clustering method.
The map function performs the procedure of assigning each sample to the closest center while the reduce function performs the procedure of updating the new centers.
In order to decrease the cost of network communication, a combiner function is developed to deal with partial combination of the intermediate values with the same key within the same map task Solving 0-1 Multi-Dimensional Knapsack problem using a discrete binary version of Grey Wolf Optimizer Algorithm in Java (April, 2015): A discrete binary version of the GWO algorithm called Discrete Binary Grey Wolf Optimizer (DBGWO) was proposed to solve the NP-Hard 0-1 Multi-Dimensional Knapsack Problem (MKP) and was tested for seven MKP benchmark problems.
Online History Quiz application Using JSP, Servlet and MySQL ( August, 2014): In this project, an online history quiz application was created where a registered history teacher can create quiz questions after getting logged in.
The students can answer the questions and asses themselves.
Optimization of Multi-Dimensional function using Grey Wolf Optimization Algorithm in MATLAB (November, 2013): Complex multi-dimensional tests functions which has multiple peaks was optimized using the novel Grey Wolf Optimizer Algorithm (GWO) which imitates the hunting behavior Grey wolves.
Genetic Programming Tool box (GPTIPS) for modeling the strain break of polymers (July, 2014): In this project, Genetic Programming Tool box (GPTIPS) in MATLAB was used as used as a regression technique to model the strain break of polymers from the polymer design data.
Study and Implementation of Joins Using Map Reduce (July, 2014): Studied and implemented joins using Map Reduce.
The Map Reduce programs were implemented using Java and Hadoop-2.0.
Android Car Theft Prevention App for BMV of Ohio (March, 2014): This app was developed using Java and Android Studio.
This app contains contacts of specialists of varying areas of Specialty for use during the time of theft.
Link Prediction Algorithm for Social Networks in Java ( December, 2013): Link predictions algorithms namely Common neighbors, Jaccard's coefficient and Adamic-Adar methods was used to predict link in undirected social network datasets.
Implementation of Kohonen Self Organized Maps in MATLAB (September, 2013): This project involved using the Unsupervised Neural Network Learning Approach for Clustering the tests data sets using Kohonen-Self Organizing Map.
Krylov Subspace Method for solving Complex, Large and Sparse Electric Networks Using MATLAB (September, 2013): In this project, the frequency domain analysis of linear electric circuits using Krylov Subspace methods namely conjugate and biconjugate gradient was performed.
Design and Simulation of Cascaded H-Bridge Multilevel Inverter Based DSTATCOM for Compensation of Reactive Power and Harmonics using MATLAB Simulink Modeling (April,2013): This project involves an performance evaluation of five-Level Cascaded H - bridge (CHB) Inverter as Distribution Static Compensator (DSTATCOM) in Power System (PS) for compensation of reactive power and harmonics.
MASTER'S RESEARCH AREA AND THESIS: Research Area: Artificial Intelligence, Evolutionary Algorithms, Bio Inspired Computing, Parallel computing, Renewable Energy Prediction and Management, Energy Storage Management, Demand Side Management, Smart Grids.
Thesis: Grey Wolf Optimizer Algorithm for optimizing power consumption cost saving of a green home integrated with renewable energy resources and smart grid (August, 2014 - July, 2015 ) : A new swarm intelligence based algorithm called Grey Wolf Optimizer (GWO) mimicking the social hierarchy and hunting behavior of grey wolves is proposed to optimally schedule the operation of Energy Storage Unit in a green smart home to reduce the cost of power consumption and to balance the load on the grid.
The proposed algorithm was tested with data obtained from United States Department of Energy for the Chicago region.
The performance of the GWO is compared with the traditional Particle Swarm Optimization (PSO) Algorithm.
The results show that the GWO outperforms the PSO and provides higher cost saving.
CO-CURRICULAR AND EXTRA-CURRICULAR ACTIVITIES: Participated in team programming contest Semicolons, conducted by Persistent Systems, Columbus, USA.
Underwent training in ACSI fabrication at NIELIT (National Institute of electronics and information technology).
Attended SPARK training program conducted by Infosys.
Active student member of IEEE (Institute of Electrical and Electronics Engineers).
Learnt Vocal Carnatic Classical Music and had given vocal concerts.
Professional Summary
Ardent and intelligent software engineer capable of providing sterling service using my technical prowess, hard working nature and interpersonal skills.
ACADEMIC ACHIEVEMENTS: Received Silver medal for obtaining 2nd rank in University Semester Examinations. Graduate Teaching Assistantship Award from the University of Toledo consecutively for Fall-2013, Spring-2014 and Summer-2015 semesters. Tuition Scholarship Award from the University of Toledo for Spring-2015 and Summer-2015 semesters.
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