Nagineni Sukumar
Ph.D. Electrical Engineering Department
PhD (V Year II Semester)

Student at IITR


Secured all India rank of 669 in GATE 2018
MHRD fellowship: for PG (2016-2018), Ph.D. (2018-present)
Awarded scholarship for higher education under INSPIRE scheme for having merit in Intermediate

Previous Education

M.Tech - Postgraduate (PG) in
Indian Institute of Information Technology, Design and Manufacturing, Jabalpur, 2018
CGPA: 7.700
B.Tech - Graduate (UG) in
Kakatiya Institute of Technology and Science, Warangal, 2015
Percentage: 80.74%
Intermediate - Intermediate (Class XII) in
Sri Vikas Jr. College, Warangal, 2011
Percentage: 96.20%
Matriculate - Matriculate (Class X) in
SV high school, Warangal, 2009
Percentage: 89.16%


Teaching Assistantship Experience, Indian Institute of Technology, Roorkee
Jun 2019 to Aug 2022

During my Ph.D., I have supervised the UG and PG students in the laboratory of basic electronics lab, digital electronics lab, digital signal and image processing lab, LabVIEW training as part of the Virtual Instrumentation Lab, and combinational & sequential circuit design in the course of FPGA based digital signal processing

PhD Placement coordinator, IIT Roorkee
Nov 2021 to Present

Initiated dialogues with over 15 plus companies, and responsible for managing their complete recruitment process Managing PhD team of associate coordinators & facilitating the smooth functioning of pre-processes and interviews


Identification of Premature Ventricular Cycles in ECG by using DCT in Identification of Premature Ventricular Cycles in ECG by using DCT
Jul 2014 to May 2015

The envelope of Discrete Cosine Transform (DCT) coefficients exhibits a faster decay rate in a PVC beat than that of a regular ECG beat. This algorithm clearly distinguishes PVC patterns under noisy conditions

Method based on variational mode decomposition for classification of electromyogram signals in Indian Institute of Information Technology, Design and Manufacturing, Jabalpur
Jul 2017 to May 2018

VMD-based spectral and entropy features are used to analyse and classify Amyotrophic lateral sclerosis (ALS), myopathy, and normal electromyogram (EMG) signals. VMD-based statistical feature for classifying physical actions using surface EMG signals These features are fed into the multiclass least squares support vector machine (MC-LS-SVM) classifier with the radial basis function to classify normal physical actions of surface EMG signals

Development of vision based advanced driver assistance system applications in Indian Institute of Technology, Roorkee
Jan 2018 to Present

A novel dataset consisting of road images for Indian road scenarios has been developed with various environmental conditions. Developed a robust algorithm for ego-lane detection with straight and curved lanes for adverse environmental conditions Generalized ego-lane detection and road marking detection for the Indian highway road. Developing a lane departure warning system based on the detected lane information. Hardware implementation of lane detection and departure warning system is developed. Two-dimensional Sliding discrete Fourier transform (2D-SDFT) kernels-based cellular neural network (CNN) for edge and lane features extraction. The feature-based lane detection algorithm is proposed and tested on the Caltech lane dataset. Design of driver state monitoring and assistance system using physiological, physical, and vision sensors Time-Frequency based continuous wave transform-synchrosqueezing transform (CWT-SST) proposed for detection of driver drowsiness state and stress level. Modified a road lane detection model that is capable of segmenting an image into the different road lanes present Used FCN architecture and pre-trained VGG-16 model without top layers for semantic segmentation


An Improved Lane Detection and Lane Departure Warning Framework for ADAS by N. Sukumar, and P. Sumathi

Published by IEEE in 2022

Journal: IEEE Transactions on Consumer Electronics (Under review)
A Robust Vision-based Lane Detection using RANSAC Algorithm by N. Sukumar and P. Sumathi

Published by IEEE in 2022

Journal: IEEE Global Conference on Computing, Power and Communication Technologies (GlobConPT).
FPGA based Adaptive Lock-in Amplifier by Aparna AV, N. Sukumar and P. Sumathi

Published by IEEE in 2022

Journal: IEEE 2022 19th India Council International Conference (INDICON)
Integration of Hough Transform and Inter-Frame Clustering for Road Lane Detection and Tracking by Sandeep Bisht, N. Sukumar, and P. Sumathi

Published by IEEE in 2022

Pages: 1-6
Journal: IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Dataset for Indian Road Scenarios (DIRS21) by Saurav Kumar, N. Sukumar, and P. Sumathi

Published by doi:10.21227/esy0-sm56 in 2021

Journal: IEEE DataPort
Two-Dimensional DFT with Sliding and Hopping Windows for Edge Map Generation of Road Images by A K Viswakarma, N. Sukumar, P. Sumathi

Published by IET in 2021

Pages: 1-13
Journal: IET Image Processing,
Vision-Based Estimation of Range and Direction of Preceding Vehicle for Advanced Driver Assistance Systems by R. K. Verma, N. Sukumar, and P. Sumathi

Published by IEEE in 2019

Pages: 1-4
Journal: In 2019 IEEE 16th India Council International Conference (INDICON)
Features based on variational mode decomposition for identification of neuromuscular disorder using EMG signals by N. Sukumar, Sachin Taran, and Varun Bajaj

Published by Springer in 2018

Pages: 13
Journal: Health information science and systems
Physical actions classification of surface EMG signals using VMD by N. Sukumar, Sachin Taran and Varun Bajaj

Published by IEEE in 2018

Journal: IEEE International Conference on Communication and Signal Processing, Chennai, India


Prof. P. Sumathi

Professor, Department of Electrical Engineering, Indian Institute of Technology Roorkee

Last Published on: 11 July 2023, 16:53:17