Tejinder Singh Lakhwani | Healthcare | Best Researcher Award

Mr. Tejinder Singh Lakhwani | Healthcare | Best Researcher Award

Research Scholar at Indian Institute of Technology Jodhpur, India

Dr. Tejinder Singh Lakhwani is a researcher in Decision Sciences and Operations with expertise in healthcare logistics, drone delivery systems, IoT integration, and fuzzy systems. He is currently pursuing his Ph.D. at the School of Management and Entrepreneurship (SME), IIT Jodhpur, focusing on intelligent and sustainable healthcare logistics using IoT and drone-based technologies. His academic journey spans mechanical engineering, operations research, and decision sciences, with consistent academic excellence and contributions in interdisciplinary research. He is a prolific scholar with numerous journal articles, conference presentations, and book chapters to his name.

Publication ProfileΒ 

Scopus

Orcid

Educational Background πŸŽ“

  • Ph.D. in Decision Sciences and Operations
    SME, IIT Jodhpur (2020 – 2025)
    CGPA: 7.73
    Thesis: Mobility in Blood Supply Management using IoT paradigm

  • M.Tech. in Operations Research
    NIT Durgapur (2018 – 2020)
    CGPA: 7.92
    Thesis: An analysis on Dombi Neutrosophic and m-Polar Pythagorean Fuzzy Graphs with properties

  • B.Tech. in Mechanical Engineering
    RGPV University (2012 – 2016)
    CGPA: 7.92

Professional Experience πŸ’Ό

  • Participated in various workshops including:

    • Gender Bias and Stereotyping (TEQIP-III Workshop, NIT Durgapur, 2019)

    • Gender Equality and Women Rights (NIT Durgapur, 2019)

    • Navigating PhD and Beyond (ACS Society, IIT Jodhpur, 2025)

  • Proficient in academic research, teaching, LATEX typesetting, and consulting

  • Skills include Python, MATLAB, and LaTeX, with focus on Supply Chain Management

  • Involved in multiple international conferences with presentations on drone logistics, tokenization in supply chains, and multi-modal healthcare routing

Research Interests πŸ”¬

  • Drone-based healthcare logistics and optimization

  • IoT and AI integration in blood supply chain management

  • Fuzzy and neutrosophic graph theory applications

  • Multi-modal logistics, decision sciences, and supply chain modeling

  • Ant colony and hybrid metaheuristic algorithms

  • Sustainability and resilience in medical logistics systems

Awards and HonorsπŸ†βœ¨

  • Gold Medalist in B.E. (Mechanical Engineering), RGPV University (2016)

  • Gold Medalist in M.Tech. (Operations Research), NIT Durgapur (2020)

  • MHRD Fellowship for M.Tech. studies (2018)

  • MoE Doctoral Fellowship for Ph.D. studies (2020)

  • Junior Scientist Award from Madhya Pradesh Government (2006)

  • Qualified GATE in 2017 and 2018 with scores of 380 and 540 respectively

Conclusion🌟

Dr. Tejinder Singh Lakhwani is an emerging academic and research professional whose work integrates technology, healthcare, and operations research. His contributions to drone and IoT-based blood delivery systems demonstrate a commitment to real-world, impactful problem-solving. With multiple awards, gold medals, and a growing portfolio of high-impact publications and presentations, he stands out as a thought leader in the space of sustainable and intelligent logistics systems. His interdisciplinary expertise and ongoing Ph.D. research are shaping the future of smart healthcare supply chains.

Publications πŸ“š

1️⃣ πŸ›°οΈ Healthcare Logistics (IoT & Drone):

  • Beyond numbers: A novel IoT and drone framework for enhancing healthcare logistics
    πŸ“° Discover Health Systems, Vol. 4, 2025


2️⃣ 🚁 Blood Bag Deliveries & Emergencies:

  • Revolutionizing healthcare logistics: The strategic role of drone technology in blood bag deliveries for remote and emergency care
    πŸ“° Journal of Transport and Health, Vol. 42, 2025
    πŸ”— doi: 10.1016/j.jth.2025.102053


3️⃣ 🏦 Banking & Fuzzy Models:

  • Navigating uncertainty: Leveraging fuzzy queuing models to revolutionize customer experience in banking
    πŸ“° Fuzzy Economic Review, Vol. 29, No. 1, 2024
    πŸ”— doi: 10.25102/fer.2024.01.04


4️⃣ πŸ”— Fuzzy Graph Theory:

  • Some operations on Dombi neutrosophic graph
    πŸ“° Journal of Ambient Intelligence and Humanized Computing, Vol. 13, pp. 425–443, 2022


 

 

 

Jatinder Kumar | Health Care Services | Best Researcher Award

Dr. Jatinder Kumar | Health Care Services | Best Researcher Award

IT Professional at PGIMER, Chandigarh, India

Dynamic IT professional with over 25 years of experience in software development, network infrastructure, and IT solutions. Specializes in full-stack development, cloud computing (AWS, Azure), network security, and virtualization technologies. Experienced in integrating business strategy with technology to enhance IT operations. Holds extensive expertise in hospital information systems, data analytics, and artificial intelligence applications in healthcare.

Publication ProfileΒ 

Scopus

Educational Background πŸŽ“

  • PhD in Computer Science, Chitkara University (2024)
  • Master of Philosophy (Computer Science), MMU, Sadopur, Ambala, Haryana (2013)
  • Master of Business Administration (MBA), Panjab University, Chandigarh (2006)
  • Master of Computer Applications (MCA), Panjab University, Chandigarh (1997)
  • Bachelor of Science (B.Sc.), M.A.M. College, Jammu (1994)

Professional Experience πŸ’Ό

  • Software Engineer, Trident InfoTech Corporation Limited, Chandigarh
    • Developed software solutions and contributed to system design and deployment.
    • Worked on enterprise-level applications for various industries.
  • Computer Programmer, PGIMER, Chandigarh (Since 2001)
    • Key contributor to the implementation of the Hospital Information System (HIS) for a 2,500-bed hospital.
    • Designed and developed the inventory module using process flow diagrams and entity-relationship diagrams.
    • Enhanced patient care, reduced wait times, and streamlined administrative workflows.
    • Involved in system integration, cloud-based solutions, and data migration strategies.

Research Interests πŸ”¬

  • Artificial intelligence and deep learning applications in healthcare.
  • Medical imaging and thyroid nodule analysis using deep learning models.
  • Multi-agent system frameworks for efficient hospital administration.
  • Cloud computing and security solutions for healthcare IT systems.
  • e-Governance and digital transformation in public healthcare.

Awards and HonorsπŸ†βœ¨

  • Best Paper Presentation, TELEMEDICON 2024, PGIMER, Chandigarh.
  • Best Paper Presentation, ICAAIML 2024, Hyderabad, India.
  • First Prize in Yoga Competition, International Yoga Day 2024, PGIMER, Chandigarh.
  • Represented Chandigarh in National Yoga Competitions in Telangana and Rajasthan.
  • Conducting yoga classes and educational support for underprivileged children in Chandigarh.
  • Various professional certifications in hardware, Oracle, and MCSE.

Conclusion🌟

With an extensive background in IT, healthcare systems, and artificial intelligence, the author has made significant contributions to hospital information systems and deep learning applications in medical imaging. His research and professional work have enhanced patient care and operational efficiency in healthcare institutions. Recognized for academic excellence and community service, he continues to drive innovation in AI-driven healthcare solutions and IT infrastructure development.

Publications πŸ“š

πŸ“– Kumar, J., Panda, S.N., & Dayal, D. (2023, December). Deep Learning for Improved Thyroid Nodule Analysis in Ultrasound Images. INTERNATIONAL JOURNAL OF RESEARCH AND ANALYTICAL REVIEWS (IJRAR.ORG), Volume 10, Issue 4.


πŸ“– Kumar, J., Panda, S.N., & Dayal, D. (2023). Utilizing Deep Learning Models for the Classification of Thyroid Nodules in Ultrasound Images. The International Journal of Engineering and Science (IJES), Volume 12, Issue 11, Pages 18-31.


πŸ“– Kumar, J., Panda, S.N., & Dayal, D. (2023, December). An Overview of Deep Learning Methods for Segmenting Thyroid Ultrasound Images. International Journal of Advanced Engineering and Nano Technology (IJAENT), ISSN: 2347-6389 (Online), Volume 10, Issue 12.


πŸ“– Kumar, J., Panda, S.N., Dayal, D., & Sharma, M. (2024). Enhancing Thyroid Nodule Assessment with Deep Learning and Ultrasound Imaging. e-Prime – Advances in Electrical Engineering, Electronics, and Energy (Scopus). (Submitted after revision, awaiting acceptance letter.)


πŸŽ™οΈ Kumar, J., Panda, S.N., & Dayal, D. (2023, November). Deep learning routes to thyroid ultrasound image segmentation: A review. AIP Conference Proceedings, Vol. 2878, No. 1. AIP Publishing.


πŸŽ™οΈ Kumar, J., Panda, S.N., Dayal, D., & Sharma, M. (2023, September). Review of Deep Learning Techniques Over Thyroid Ultrasound Image Segmentation. 2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology (ICSEIET), pp. 320-326. IEEE.


πŸŽ™οΈ Kumar, J., Panda, S.N., & Dayal, D. (2023). Pediatric Thyroid Ultrasound Image Classification Using Deep Learning: A Review. Chitkara University Doctoral Consortium – CUDC 2023.


πŸŽ™οΈ Kumar, J., Panda, S.N., & Dayal, D. (2024). Improving Thyroid Nodule Evaluation Using Deep Learning and Ultrasound Imaging. National Telemedicine Conference – TELEMEDICON 2024, held in Chandigarh (November 28-30, 2024).