Kshetrimayum Robert Singh | Rice | Best Researcher Award

Assist. Prof. Dr. Kshetrimayum Robert Singh | Rice | Best Researcher Award

Assistant Professor at Mizoram University, India

Dr. Kshetrimayum Robert Singh is an Assistant Professor in the Department of Electrical Engineering at Mizoram University, where he has served since 2011. He holds a Ph.D. from NIT Silchar with research focusing on image processing and neural networks for rice grain classification. With over 20 research papers, a book, two patents, and five ongoing research projects—two of which he leads as Principal Investigator—Dr. Singh has made significant contributions in the areas of digital image processing and pattern recognition. His notable innovations include the development of various texture feature extraction techniques for cereal grain classification. He is a member of IETE, ISTE, and NEAST, and currently supervises three Ph.D. scholars.

Profile:

🎓 Academic & Professional Journey:

Dr. Robert Singh holds a Ph.D. in Electrical Engineering from NIT Silchar, where his research focused on rice grain recognition using image processing and neural networks. He also earned his M.E. in Applied Electronics and B.E. in Electrical and Electronics Engineering. He has served as a Lecturer at KSR College of Technology, Guest Faculty at DOEACC Imphal, and Assistant Engineer at Mizoram University before joining his current post in 2011.

🔬 Research & Innovation:

His research interests lie in Digital Image Processing, Pattern Recognition, and Artificial Neural Networks. He has published 20+ research papers, holds 2 patents, and authored a book (ISBN: 978-3-659-69371-7). With a citation index of 217, h-index of 6, and 5 ongoing projects (PI in 2), his contributions are recognized nationally. One of his notable works includes cereal grain classification using advanced texture feature techniques, which also led to a German patent.

🏅 Awards & Memberships:

  • 🏆 Award Preference: Best Researcher Award

  • 👥 Member of professional bodies:

    • IETE (ID: AM-221226)

    • ISTE (ID: LM 54076)

    • NEAST (ID: 157362)

📚 Academic Engagement:

  • Former Head In-Charge, Department of Electrical Engineering

  • Member of several academic and administrative committees including the Board of Professional Studies and Teachers’ Grievance Redressal Committee

  • Currently guiding 3 Ph.D. scholars

💡 Specializations:

  • Texture feature extraction for image classification

  • Low-complexity feature selection methods

  • Microcontroller-based system design

  • Neural network applications in digital design

📊 Citation Metrics:

  • All Time Citations: 217

  • Citations Since 2020: 178

  • h-index: 6 (overall and since 2020)

  • i10-index: 5 (overall and since 2020)

Publication Top Notes:

  • Efficient Technique for Rice Grain Classification Using Back‐Propagation Neural Network and Wavelet Decomposition

  • A Comparison of Gray-Level Run Length Matrix and Gray-Level Co-Occurrence Matrix Towards Cereal Grain Classification

  • A Cascade Network for the Classification of Rice Grain Based on Single Rice Kernel

  • Comparative Analysis of Texture Feature Extraction Techniques for Rice Grain Classification

  • Medicinal Plant Species Classification Using Neural Network Classifier

  • Gray Level Size Zone Matrix for Rice Grain Classification Using Back Propagation Neural Network: A Comparative Study

  • Reviewing Demand Response for Energy Management With Consideration of Renewable Energy Sources and Electric Vehicles

  • Congestion Management by Generator Real Power Rescheduling Using Hybrid Grey Wolf Optimizer and Cuckoo Search Algorithm

  • Performance Analysis of a Grid Connected Solar-PV and PMSG-Wind Energy Based Hybrid System

  • Enhanced Harris Hawks Optimization Based Load Frequency Control of Multi Area Microgrid Based Water Treatment Plant With Consideration of 3DOF-(FO-PIDN)/(TIDN) Controller

  • Real Power Rescheduling of Generator for Transmission Line Congestion Management Using Atom Search Algorithm

  • Performance Analysis of a Standalone Inverter System Under Variable Loading Conditions

  • Study on Mutual Funds Trading Strategy Using TPSO and MACD

  • Fingerprint Indexing and Verification

  • Multi-Objective-Based Economic and Emission Dispatch With Integration of Wind Energy Sources Using Different Optimization Algorithms

  • Short-Term Load Forecasting for IEEE 33 Bus Test System Using SARIMAX

  • GSM Based Smart Irrigation System With Arduino UNO Powered by Solar Panel

  • Classification of Medicinal Plant Species Using Neural Network Classifier: A Comparative Study

  • Smart Three Layer Anti-Theft Vehicle Security System Based on Arduino Microcontroller

  • Texture Analysis for Rice Grain Classification Using Wavelet Decomposition and Back Propagation Neural Network

 

Houda Orchi |  Crop Diseases | FutureFarming Leadership Award

Ms  Houda Orchi |  Crop Diseases | FutureFarming Leadership Award

Phd Student |  ENSEM |  Morocco

ORCHI Houda, born on May 22, 1994, is a Moroccan PhD student specializing in Artificial Intelligence and Computer Vision at The National School of Electricity and Mechanics, University of Hassan II Casablanca. Supervised by Dr. Mohamed Sadik and Dr. Mohammed Khaldoun, her research focuses on developing a platform for detecting and identifying crop diseases. She holds an Engineer degree in Mechatronics Engineering from the National School of Applied Sciences of Tetouan and a B2 German certificate from the Goethe Institute. Houda has diverse professional experience, including a full-time role as a Research Assistant at UQAM’s computer science laboratory and various internships with notable organizations such as OCP, Renault Nissan, and Peugeot-Citroën. Her technical expertise spans AI, computer vision, mechatronics, robotics, automotive technology, and embedded systems. Houda is proficient in managing multiple tasks under pressure and excels in manufacturing and product development environments.

Profile:

🎓 Academic Qualification:

2019 – Present: PhD student in Artificial Intelligence and Computer Vision at The National School of Electricity and Mechanics, University of Hassan II Casablanca, supervised by Dr. Mohamed Sadik and Dr. Mohammed Khaldoun. Thesis Title: Development of Detection and Identification of Crop Diseases Platform. 2018 – 2019: German Certificate B2 from the Goethe Institute. 2014 – 2018: Engineer Degree in Mechatronics Engineering at the National School of Applied Sciences of Tetouan. 2012 – 2014: Preparatory Cycle at the National School of Applied Sciences. 2011 – 2012: High School Diploma in Mathematical Sciences A.

💼 Professional Experience:

31 October 2023 – Present: Research Assistant at Computer Science Laboratory, UQAM. 01 February – 30 June 2018: Mechatronics Engineer at OCP Jorf Lasfar – worked on clock synchronization and data exchange automation. 01 July – 01 September 2017: Internship at Renault Nissan – responsible for the design and installation of a conveyor in the assembly department. 02 August – 02 September 2016: Initiation internship at Savola Maroc – focused on repair and maintenance of engines and pumps. 01 July – 01 August 2016: Observation internship at Sopriam Peugeot – engaged in automotive diagnostics and engine repair.

🔧 Skills and Technical Knowledge:

Technical Skills: Artificial Intelligence, Computer Vision, Internet of Things, Mechanical Production, Machine Design, Mechatronics Systems, Robotics, Theory of Mechanisms, Industrial Design, General Technology, Automotive Technology, Automation, and Instrumentation. Additional Knowledge: Embedded Systems, Electrical Networks, Signals, Project and Quality Management, Production Management, Electrical Engineering, Power Electronics, Economy, Relational Database, General Accounting.

Research Focus: Crop Diseases

Houda’s current research is centered on the development of a platform for the detection and identification of crop diseases using artificial intelligence and computer vision technologies. This innovative work aims to enhance agricultural productivity and sustainability by providing precise and timely identification of various crop diseases, thereby enabling better management and treatment strategies. 🌱📊

 

Publication Top Notes:

  • On Using Artificial Intelligence and the Internet of Things for Crop Disease Detection: A Contemporary Survey
    • Authors: H. Orchi, M. Sadik, M. Khaldoun
    • Journal: Agriculture, Volume 12, Issue 1, Article 9, 2021
    • Citations: 98
  • Real-Time Detection of Crop Leaf Diseases Using Enhanced YOLOv8 Algorithm
    • Authors: H. Orchi, M. Sadik, M. Khaldoun, E. Sabir
    • Conference: 2023 International Wireless Communications and Mobile Computing (IWCMC)
    • Citations: 10
  • Automation of Crop Disease Detection Through Conventional Machine Learning and Deep Transfer Learning Approaches
    • Authors: H. Orchi, M. Sadik, M. Khaldoun, E. Sabir
    • Journal: Agriculture, Volume 13, Issue 2, Article 352, 2023
    • Citations: 9
  • A General Survey on Plants Disease Detection Using Image Processing, Deep Transfer Learning, and Machine Learning Techniques
    • Authors: H. Orchi, M. Sadik, M. Khaldoun
    • Conference: Ubiquitous Networking: 7th International Symposium, UNet 2021, Virtual Event
    • Citations: 4
  • A Novel Hybrid Deep Learning Model for Crop Disease Detection Using BEGAN
    • Authors: H. Orchi, M. Sadik, M. Khaldoun
    • Conference: International Symposium on Ubiquitous Networking, 267-283, 2022
    • Citations: 2