Profile Details

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USD 40 /hr

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Hire Dr. Amar Kumar V.

India

USD 40 /hr

Data Scientist and Machine Learnin Engineer

Profile Summary

I have expertise in Autonomous Vehicles, Deep Learning Techniques, Machine Condition Monitoring

Subject Matter Expertise

• ☆ Data Analysis
• ☆ Machine Learning
• ☆ Deep Learning
• ☆ Python
• ☆ Matlab
• ☆ Tensorflow
• ☆ LaTex
• ☆ R
• ☆ Tableau
• ☆ Scikit-learn

Services

• Writing
• Research
• Data & AI
• Product Development

Writing Technical Writing

Research Feasibility Study, Gap Analysis, Scientific and Technical Research, Systematic Literature Review

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-ML, Data Visualization, Big Data Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

Product Development Concept Development, Prototyping

Work Experience

Research Scientist

IIT Delhi

October 2022 - Present

PhD Research Scholar

Birla Institute of Technology and Science - Hyderabad Campus

January 2018 - Present

Education

PhD

BITS Pilani Hyderabad Campus

January 2018 - July 2021

Certifications

• Certification details not provided.

Publications

JOURNAL ARTICLE

Amar Kumar Verma, Pallav Devang Raval, Neha Rajagopalan, Vaishnavi Khariya, Radhika Sudha(2022). Development of an AI-based FSA for real-time condition monitoring for industrial machine . Neural Computing and Applications. 34. (11). p. 8597--8615. Springer Science and Business Media {LLC}

Amar Kumar Verma, Inturi Vamsi, Prerna Saurabh, Radhika Sudha, Sabareesh G.R., Rajkumar S.(2021). Wavelet and deep learning-based detection of SARS-nCoV from thoracic X-ray images for rapid and efficient testing . Expert Systems with Applications. 185. p. 115650. Elsevier {BV}

Amar Kumar Verma, Shivika Nagpal, Aditya Desai, Radhika Sudha(2021). An efficient neural-network model for real-time fault detection in industrial machine . Neural Computing and Applications. 33. (4). p. 1297--1310. Springer Science and Business Media {LLC}

Amar Kumar Verma, Pragnya Akkulu, Shravvan V. Padmanabhan, Sudha Radhika(2021). Automatic Condition Monitoring of Industrial Machines Using FSA-Based Hall-Effect Transducer . IEEE Sensors Journal. 21. (2). p. 1072--1081. Institute of Electrical and Electronics Engineers ({IEEE})

(2020). An efficient neural-network model for real-time fault detection in industrial machine . Neural Computing and Applications.

(2020). Automatic condition monitoring of industrial machines using FSA-based hall-effect transducer . IEEE Sensors Journal.

BOOK CHAPTER

Amar Kumar Verma, Aakruti Jain, Sudha Radhika(2020). Neuro-fuzzy Classifier for Identification of Stator Winding Inter-turn Fault for Industrial Machine . 101--110Springer Singapore

(2020). Quantitative Modeling and Simulation for Stator Inter-turn Fault Detection in Industrial Machine . Intelligent Computing and Communication.

CONFERENCE PAPER

(2019). K-Nearest Neighbors and Grid Search CV Based Real Time Fault Monitoring System for Industries . 2019 IEEE 5th International Conference for Convergence in Technology (I2CT).

(2019). Wavelet Based Fault Detection and Diagnosis Using Online MCSA of Stator Winding Faults Due to Insulation Failure in Industrial Induction Machine . 2018 IEEE Recent Advances in Intelligent Computational Systems (RAICS).

(2018). Random Forest Based Real Time Fault Monitoring System for Industries . 2018 4th International Conference on Computing Communication and Automation (ICCCA).