Neda Fatima | Cross-disciplinary Synthesis | Women Researcher Award

Neda Fatima | Cross-disciplinary Synthesis | Women Researcher Award

Dr Neda Fatima, Manav Rachna International Institute of Research and Studies, India

🌟 Dr. Neda Fatima, an accomplished Knowledge Engineer, aspires to innovate SMART devices in CSE and IT via IoT. With 6 years’ experience as an Assistant Professor, she’s adorned with accolades like NET and GATE qualifications, PhD, and numerous research papers. Adept in AI, ML, Data Science, and IoT, she’s mentored in hackathons and workshops, showcasing expertise in academia and industry. Passionate about education, she’s won awards, led cultural events, and demonstrated leadership as a Placement Coordinator. With a Ph.D. from JMI, she’s a dynamic professional excelling in both academics and extracurriculars. πŸš€

Publication profile

google scholar


Dr Neda Fatima, a distinguished scholar, proudly holds a Ph.D. from Jamia Millia Islamia (JMI), an achievement recognized and awarded for its excellence. Their academic journey showcases a remarkable trajectory, marked by stellar accomplishments. With a Master’s in Technology from JMI, attained in 2019 with a remarkable CGPA of 9.52, and a Bachelor’s in Technology from the same esteemed institution in 2015, where they graduated with a notable CPI of 9.13. Their linguistic prowess is equally impressive, having completed an Advanced Diploma in Spanish, considered equivalent to a Spanish degree, from JMI in 2015, where they excelled as the course topper. Additionally, they showcased their linguistic flair by topping courses in Portuguese as well. Their academic brilliance traces back to their school days, where they consistently shone. In 2010, they secured a first division in their XII CBSE examinations from Delhi Public School, R.K. Puram, with a focus on Physics, Chemistry, Mathematics, Biology, and English. Even earlier, in 2008, they emerged as the school topper in X CBSE examinations from Father Agnel School, boasting an impressive aggregate of 96%. πŸ†πŸŽ“βœ¨


With a diverse portfolio spanning from faculty development programs πŸ“š to hackathons πŸ’», internships 🀝, and workshops πŸ› οΈ, my journey epitomizes a holistic engagement with cutting-edge technologies. From mentoring teams in cybersecurity and AI/ML hackathons to participating in national-level military hackathons πŸŽ–οΈ, my dedication to innovation is evident. Moreover, I’ve contributed as a resource person in research colloquia, showcasing expertise in integrating IoT with blockchain. With hands-on experience in diverse programming languages and technologies πŸ–₯️, coupled with a strong conceptual understanding, I’m poised to continue making impactful strides in the realms of AI, IoT, cybersecurity, and beyond.

Research focus

N Fatima’s research spans across various domains, primarily focusing on healthcare and environmental monitoring 🌿πŸ₯. Her work includes designing IoT-based systems for disease prediction in smart greenhouses and human health, such as dermatological disease prediction and stress detection systems. Additionally, she contributes to border security and vehicle recognition technologies. Fatima’s recent endeavors involve utilizing deep learning techniques for disease prediction, including SARS-CoV-2 variant detection and mortality prediction. Through her research, she aims to leverage machine learning and IoT technologies to address pressing challenges in healthcare, agriculture, and security sectors, showcasing a versatile and impactful research portfolio.

Publication top notes

IoT-based smart greenhouse with disease prediction using deep learning

Neural Network based Smart Weed Detection System

IoT-based disease prediction using machine learning

Chest X-ray and CT scan classification using ensemble learning through transfer learning

Iot based border security system using machine learning

Comparative analysis of propagation path loss models in lte networks

Comparative Performance Analysis of Digital Modulation Schemes with Digital Audio Transmission through AWGN Channel

Smart air pollution monitoring system with smog prediction model using machine learning

Design of driver alcohol detection system with automatic engine locking

SARS-CoV-2 virus variant detection and mortality prediction through symptom analysis using machine learning

Dermatological disease prediction and diagnosis system using deep learning

Design of Smart Heart Rate Monitoring and Stress Detection System with Cloud Data Storage and Privacy

COVID-19 Vaccination Progress in India and its Neighbors

Vehicle Number Plate Recognition via MATLAB

Detection and Segmentation of Brain Tumor using MRI images





Cross-disciplinary Excellence Award

Cross-disciplinary Excellence Award


Welcome to the Cross-disciplinary Excellence Award, honoring individuals who bridge the boundaries between disciplines to foster innovation, collaboration, and transformative breakthroughs. This prestigious award celebrates the power of interdisciplinary thinking in addressing complex challenges and driving progress across multiple fields.

Award Overview:

The Cross-disciplinary Excellence Award recognizes individuals who demonstrate outstanding achievements in integrating knowledge, methodologies, and perspectives from diverse disciplines to advance research, scholarship, and societal impact.


  • Open to researchers, scholars, and professionals across all disciplines
  • No age limits apply
  • Qualification: Demonstrated excellence in cross-disciplinary collaboration and innovation
  • Publications: Evidence of interdisciplinary research contributions in peer-reviewed journals or other scholarly outlets
  • Recurrements: Continued commitment to cross-disciplinary exploration and collaboration

Evaluation Criteria:

Candidates will be evaluated based on the following criteria:

  1. Depth and breadth of cross-disciplinary contributions
  2. Impact and significance of interdisciplinary research outcomes
  3. Creativity and innovation in integrating diverse perspectives and methodologies
  4. Potential for future cross-disciplinary collaboration and impact

Submission Guidelines:

  • Submit a comprehensive biography highlighting cross-disciplinary achievements and collaborations
  • Include an abstract summarizing key cross-disciplinary contributions and their significance
  • Provide supporting files such as publications, collaborative projects, or interdisciplinary initiatives


Recipients of the Cross-disciplinary Excellence Award will receive:

  • A prestigious award certificate
  • Recognition at a special ceremony or event
  • Opportunities for networking and collaboration with cross-disciplinary experts and organizations

Community Impact:

Winners of the award are expected to serve as ambassadors for cross-disciplinary collaboration, inspiring others to embrace diverse perspectives and approaches in addressing complex challenges and driving innovation.


A detailed biography outlining the candidate's cross-disciplinary background, collaborative projects, and contributions to interdisciplinary research is required.

Abstract and Supporting Files:

Candidates must submit an abstract summarizing their cross-disciplinary contributions along with supporting files such as publications, collaborative projects, or interdisciplinary initiatives to showcase the depth and breadth of their work.