Rohith Sethumadhavan, IT-IMS Certified Engineer in Windows

Rohith Sethumadhavan

IT-IMS Certified Engineer in Windows

Networking

Location
India
Education
Master's degree, Master Computer Applications
Experience
3 years, 1 Months

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Work Experience

Total years of experience :3 years, 1 Months

IT-IMS Certified Engineer in Windows at Networking
  • India
  • April 2012 to August 2012

• IT-IMS Certified Engineer in Windows, Networking, Linux, Hardware from KGISL, Appnomic, Coimbatore (April 2012 - August 2012)

Chennai, Asst Engineer, .Net developer and Data Extraction at Maa Business Solutions Pvt Ltd
  • India
  • May 2011 to December 2011

• Maa Business Solutions Pvt Ltd, Chennai, Asst Engineer, .Net developer and Data Extraction
May 2011- Dec 2011
Certification courses

Programming languages VB.net and project trainer at Software and Integrated Solution Private Limited
  • India
  • January 2006 to December 2007

• Programming languages VB.net and project trainer in VB.net (2006-2007) from Software and Integrated Solution Private Limited (SAFE), Palakkad.
• Programming languages C and C++ (2005-2006) from Software and Integrated Solution Private Limited(SAFE), Palakkad.
Computer System Skills
Programming Languages & Databases Known
• C, C++, HTML, VB.Net
• MS Access, SQL Server
Back Office Tools
• Microsoft Office
Concepts
Operating System, DBMS, Networking, System Analysis And Design
Operating Systems
• Windows (98, 2000, NT, XP, Vista, Win 7)


Academic Projects Done As Part Of 6th semester
Project Details
Title Facial Expression Recognition
Software MAT Lab
Duration 4 Months
Team Size 1
Description
The project work proposes an algorithm for facial expression recognition which can classify the given image into one of the seven facial expression categories (happiness, sadness, fear, surprise, anger, disgust, and neutral) . PCA is used for dimensionality reduction in input data while retaining those characteristics of the data set that contribute most to its variance, by keeping lower-order principal components and ignoring higher-order ones. Such low-order components contain the "most important" aspects of the data. The extracted feature vectors in the reduced space are used to train the supervised Neural Network classifier. This approach results extremely powerful because it does not require the detection of any reference point or node grid. The proposed method is fast and can be used for real-time applications

Education

Master's degree, Master Computer Applications
  • at Karpagam arts and science college
  • June 2010

• Master of Computer Applications (2007-2010) from Karpagam arts and science college, Coimbatore, Bharathiyar University, 74.8%

Bachelor's degree, Chemistry
  • at University of Calicut
  • January 2005

• Bachelor of Chemistry (2002-2005) from N.S.S college, Ottapalam, University of Calicut, 51% • +2 (2000-2002) from Puliyaparamb higher secondary school, Palakkad, Kerala board, 50%

High school or equivalent,
  • at Seventh Day Adventist Higher Secondary School
  • March 2000

• SSLC (2000) from Seventh day Adventist school, Ottapalam, State Board of Kerala, 60%

Specialties & Skills

Extraction
Data Extraction
MICROSOFT OFFICE
MS ACCESS

Languages

Hindi
Expert
Malayalam
Expert
English
Expert
Tamil
Intermediate

Training and Certifications

IBM Mainframe (Certificate)
Date Attended:
December 2010
Valid Until:
April 2011
Networking And IT-IMS (Information Technology - Infrastructure Management Services) (Certificate)
Date Attended:
April 2012
Valid Until:
August 2012