Assistant Engineering

Karinki Manikanta ****************@*****.***

Karinki Manikanta

Present Address Permanent Address

Room No: A211, Gautham Bhavan S/O Karinki Satyanarayana, Amrita Vishwa Vidyapeetam, Katakoteswaram (village),534305 Coimbatore, Tamilnadu, India-641112. Nidadavole(mandal) Phone: +91-984*******, 753******* West Godavari Dist. E-mail: ****************@*****.*** Andhra Pradesh, India. Objective

To secure a challenging position where i can effectively contribute my skills, innovative ideas and knowl- edge for growth of the organization.

Technical Proficiency

OS used : Ubuntu 16.04 and Windows Operating Systems.

Worked with Linux commands and Anconda environment.

Good Knowledge in Python 3.0, C basics

Tools: Matlab, Numpy, Scipy, Scikit-learn, Tensorflow, Keras, Pandas, Matplotlib.

Hardware worked with H1n Handy Recorder Device and Raspberry pi3.

Web Development: HTML, JavaScript, CSS

Educational Profile

Amrita Vishwa Vidyapeetam, Coimbatore

Computational Engineering and Networking

CGPA: 7.0 Postgraduate

Completed (June-2019)

Sasi Institute of Technology and Engineering Tadepalligudem West Godavari, Andhra Pradesh India

Major: Computer Science & Engineering Bachelor of Technology Aggregate percentage: 66.17 (2011-15)

Board of Intermediate Education, Andhra Pradesh

Sasi junior College, vellivennu Intermediate

Aggregate Percentage: 68.7 (2009-11)

Board of Secondary School Education, Andhra Pradesh Nagarjuna Model High School, Sankarapuram, West Godavari S.S.C. Aggregate Percentage: 68 (2008-09)

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Karinki Manikanta ****************@*****.***

Project

M.tech Thesis, “Automatic Crying Event Detection Method in Indoor Home Environment” Guide: Dr. K.P. Soman, Head and Professor at Amrita Center for Computational Engineering and Networking.

Co Guide: Dr. M. Sabarimalai Manikandan, Assistant Prof., School of Electrical Sciences, IIT Bhubaneswar, Orissa.

- Evaluating the performance of the automatic crying event detection method in indoor home en- vironment.

- In this project, using my own sound database (around 8 hours, 4 classes) recorded from real home environment with the help of H1n handly recorder and which include the electrical machine(Fan, AC), crying, speech (Male, Female, Children), and music (TV shows, Movies, News) sounds.

- Considering 16Khz sampling rate with three different frame length 100ms, 250ms, 500ms with 90 percent frame overlap extracting the features MFCCs and Spectrogram for classifying home environmental sounds. Investigating how frame length affect the classification accuracy.

- Comparing the performance of shallow classifier model Support Vector machine, Deep learning Neural Network model and Feed Forward Neural Network for home environmental sounds clas- sification.

- Making Deep Convolutional Neural Network model, which are designed specifically for object recognition in image, can be successfully trained to classify 2D home environmental sounds.

- Based on above feature classifying the accuracy of model with 5-fold cross validation.

- This project has numerous application in the field of machine health detection, robot navigation, home environment audio surveillance etc.

B.Tech Thesis, “ADMISSION PREDICTOR” Guide: Smt. Satya Srinivas, Assistant Professor, Dept. of Computer Science & Engg., Sasi Institute of Technology and Engineering Tadepalligu- dem, West Godavari, Andhra Pradesh.

Publications:

Conference Papers:

1. Karinki Manikanta, K.P. Soman and M.Sabarimalai Manikandan,“International Conference on Innovations in Computer Science and Engineering”, in Proc. 7th Int. Conf. on Innovations in Computer Science and Engineering, ICICSE-2019, Springer (Submitted) Workshops / Seminars

Shared Task workshop on machine translation in Indian language.

Block Chain Introduction.

Deep-chem 2017.

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Karinki Manikanta ****************@*****.***

Data Driven Model (Dynamic mode decomposition, singular value decomposition). Extra-curricular Activities

Initiated TECHNICAL, SPORTS AND CULTURAL CLUB in our Department.

Organized TECHNICAL EVENTS in our college.

Term work

Pedestrian detection using Convolution Neural Networks.

Sentimental Analysis with Convolution Neural Networks. Research Interest

Machine Learning, Deep Learning, Artificial Intelligence. References

1. Dr. K. P. Soman,

Professor,

Amrita Center for Computational Engineering and Networking (CEN), Coimbatore.

E-mail: kp *****@******.***

2. Dr. M. Sabarimalai Manikandan,

Assistant Professor,

School of Electrical Sciences,

IIT Bhubaneswar.

Phone: +91-674-****-*** (O)

E-mail: ***@******.**.**

Personal Profile

Name : Karinki Manikanta

Date of Birth : 30-07-1994

Father’sName : Karinki Satyanarayana

Mother’sName : Karinki Sitharatnam

Marital Status : Bachelor

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Karinki Manikanta ****************@*****.***

Strengths : Optimism and Patience for good results. Hobbies : Reading Books, Playing Cricket, Watching movies. Languages Known : Telugu and English

I declare that the above details are true to the best of my knowledge and belief.. Date: (Karinki Manikanta)

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