Dr. Pangambam Sendash S.

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About me

Hello everyone!!! I'm Dr. Pangambam Sendash Singh (Ph.D.), currently serving as Assistant Professor (Senior Scale) at School of Computer Science, University of Petroleum & Energy Studies since August 2024. Prior to this, I worked as an Assistant Professor at Manipal University Jaipur from January 2024 to August 2024. I also had worked as a Postdoctoral Researcher at Institut Català d’Arqueologia Clàssica (ICAC), Tarragona, Spain, from August 2022 to January 2024, where I was hosted by Prof. Héctor A. Orengo Romeu under the project MAHSA.

I completed my Ph.D. in Computer Science from Banaras Hindu University (BHU) under the supervision of Prof. S. Karthikeyan. My Ph.D. research work was fully supported by UGC's Junior/Senior Research Fellowship Scheme. My Ph.D. research area lies in the fields of Computational Intelligence, Deep Learning and its applications in Multispectral and Hyperspectral Image Analysis. Before that, I earned my Master of Science degree in Computer Science from Banaras Hindu University (BHU) and Bachelor of Science (Hons.) in Physics from D.M. College of Science, Imphal (under Manipur University).

My research studies aim to enable innovative solutions to problems of broad societal relevance through advances in Machine Learning. Particularly, I love developing new foundational methods motivated by concrete real-world applications, focusing on new areas that bridge computer science with other disciplines.

Apart from my academic pursuits, I have a keen interest in writing poems, listening to music, singing, and playing musical instruments.

Profile Image

Pangambam Sendash Singh

Assistant Professor (Senior Scale) at University of Petroleum & Energy Studies, Dehradun

  • Birthplace: Manipur, India
  • Website: https://pangambam.in/
  • Mobile: +91-8014391934
  • Current City: Dehradun, India
  • Linguistic Ability: Manipuri, Hindi, English
  • Highest Degree: Ph.D.
  • Email: info@pangambam.in sendashpangambam@gmail.com pangambam.singh@ddn.upes.ac.in

Prospective collaborators or students interested in exploring applied machine learning, deep learning, specifically in multispectral and hyperspectral imaging applications, are welcome to reach out. Feel free to contact me with your inquiries or ideas.

Skills

Teaching & Research 90%
Programming in C, C++, Matlab, Python 80%
Document Preparation Systems: LaTex, MS-Office 100%
Web Design Language: HTML, CSS 65%
Photoshop 80%
Other Skills: Music, Singing 45%

Credentials

Educational Qualifications

Doctor of Philosophy (Computer Science)

2022

Banaras Hindu University, Varanasi, India

Thesis title: Machine Learning Based Efficient Approaches for Improving the Performance of Multi-faceted Hyperspectral Imaging Applications

NET-JRF (Computer Science and Applications)

2015

GATE (Computer Science and Information Technology)

2015

Master of Science (Computer Science)

2015

Banaras Hindu University, Varanasi, India

Bachelor of Science Hons. (Physics)

2012

D.M. College of Science, Manipur University, Imphal, India

Professional Experience

Assistant Professor (Senior Scale)

August 2024 - Present

University of Petroleum & Energy Studies, Dehradun, India

Assistant Professor

January 2024 - August 2024

Manipal University Jaipur, Rajasthan, India

  • Engaged in teaching university undergraduates and postgraduates.
  • Supervising PG students in all aspects of students projects.
  • Faculty Lab Co-ordinator.

Postdoctoral Researcher

August 2022 - January 2024

Institut Català d’Arqueologia Clàssica (ICAC), Tarragona, Spain

  • Worked in an international project "Mapping of Archaeological Heritage in South Asia (MAHSA)" at Landscape Archaeology Research Group, ICAC, Tarragona, Spain.
  • Responsible for investigating novel machine learning algorithms to automatically detect archaeological heritage sites using data obtained from multiple satellite imageries.

Here is a link to my resume. It was last updated in August, 2024.

Awards/Achievements

Secured the 20th rank, achieving the top position statewide, in Higher Secondary Examination (XII-Science) conducted by Council of Higher Secondary Education, Manipur (2009)

State Topper in Computer Science securing 97% marks in Higher Secondary Examination conducted by Council of Higher Secondary Education, Manipur (2009)

Awarded INSPIRE Scholarship for Higher Education (2009-2013) by Department of Science & Technology, Government of India for outstanding performance in Higher Secondary Examination (2009)

Awarded State Merit Scholarship (2009-2010) by Department of Education (S), Government of Manipur, for outstanding performance in Higher Secondary Examination (2009)

Awarded (Late) N. Lakhi Devi Memorial Gold Medal for achieving the highest marks in Computer Science in B.Sc. Degree at D.M. College of Science (2012)

Awarded Junior & Senior Research Fellowship (UGC NET-JRF & SRF) by University Grants Commission (UGC), New Delhi (December 2015)

Qualified UGC-National Eligibility Test (NET) for Assistant Professor in Computer Science and Applications nationwide (June 2015)

Qualified GATE in Computer Science and Information Technology (March 2015).

Research

  • Publications
  • Research Interest
  • Professional Activities

Journal Publications

Major publications:
  • Singh, Pangambam Sendash and Subbiah Karthikeyan. “Salient object detection in hyperspectral images using deep background reconstruction based anomaly detection”, Remote Sensing Letters (2022). doi: 10.1080/2150704X.2021.2005270 (SCIE IF: 2.3)
  • Singh, Pangambam Sendash and Subbiah Karthikeyan. “Enhanced classification of remotely sensed hyperspectral images through efficient band selection using autoencoders and genetic algorithm”, Neural Computing and Applications (2021). doi: 10.1007/s00521-021-06121-4 (SCIE IF: 6.0)
  • Singh, Pangambam Sendash, Vijendra Pratap Singh, Manish Kumar Pandey, and Subbiah Karthikeyan. “Enhanced classification of hyperspectral images using improvised oversampling and undersampling techniques”, International Journal of Information Technology (2021). doi: 10.1007/s41870-021-00676-0 (Scopus indexed)
  • Singh, Pangambam Sendash, Vijendra Pratap Singh, Manish Kumar Pandey, and Subbiah Karthikeyan. “Local Binary Ensemble Based Self-Training for Semi-Supervised Classification of Hyperspectral Remote Sensing Images”, Computación y Sistemas 24, no. 2 (2020): 497–509. doi: 10.13053/CyS-24-2-3374 (Scopus, ESCI IF: 0.6)
Collaborations:
  • Nath, Abhigyan, Rathore, Sudama, and Singh, Pangambam Sendash. “Exploiting ensemble learning and negative sample space for predicting extracellular matrix receptor interactions”, Mathematical Biology and Bioinformatics 18, no. 1 (2023): 113–127. doi: 10.17537/2023.18.113 (Scopus indexed)
  • Singh, Vijendra Pratap, Manish Kumar Pandey, Pangambam Sendash Singh, and Subbiah Karthikeyan. “An LSTM Based Time Series Forecasting Framework for Web Services Recommendation”, Computación y Sistemas 24, no. 2 (2020): 687–702. doi: 10.13053/CyS-24-2-3402 (Scopus, ESCI IF: 0.6)

Conference Proceedings

  • Singh, Pangambam Sendash, Vijendra Pratap Singh, Manish Kumar Pandey, and Subbiah Karthikeyan. “One-Class Classifier Ensemble Based Enhanced Semisupervised Classification of Hyperspectral Remote Sensing Images”, IEEE Xplore (2020). doi: 10.1109/ESCI48226.2020.9167650
  • Singh, Vijendra Pratap, Manish Kumar Pandey, Pangambam Sendash Singh, and Subbiah Karthikeyan. “Neural Net Time Series Forecasting Framework for Time-Aware Web Services Recommendation”, Procedia Computer Science 171, no. 2019 (2020): 1313–22. doi: 10.1016/j.procs.2020.04.140
  • Singh, Vijendra Pratap, Manish Kumar Pandey, Pangambam Sendash Singh, and Subbiah Karthikeyan. “An Econometric Time Series Forecasting Framework for Web Services Recommendation”, Procedia Computer Science 167, no. ICCIDS 2019 (2020): 1615–25. doi: 10.1016/j.procs.2020.03.372

Book Chapters

  • Singh, Vijendra Pratap, Pandey Manish Kumar, Singh Pangambam Sendash and Karthikeyan Subbiah. “An Empirical Mode Decomposition (EMD) Enabled Long Short Term Memory (LSTM) Based Time Series Forecasting Framework for Web Services Recommendation”, FAIA 320 (2019), 715–723. doi: 10.3233/FAIA190241

Research Interest

  • Deep Learning
  • Computational Intelligence
  • High Dimensional Data Analysis
  • Multispectral and Hyperspectral Image Analysis

Professional Activities

Contact

Pangambam Sendash Singh

Location:

UPES Dehradun, P.O. Bidholi Via-Prem Nagar, Dehradun - 248007

Mobile:

+91-8014391934

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