Misha Urooj Khan | Applied Mathematics | Best Researcher Award

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Prof. Misha Urooj Khan | Applied Mathematics | Best Researcher Award

AM (Tech) at CERN, Pakistan

Prof. Misha Urooj Khan is an accomplished electronics engineer and researcher whose multifaceted expertise spans embedded systems, quantum computing, AI/ML, and cybersecurity. 🎓 With a master’s degree focused on FPGA-based real-time SLAM and extensive experience at CERN, NCP, COMSATS, and UET, she has authored 10 journal papers, 17 conference articles, and earned 658 citations. 💡 Her work includes groundbreaking innovations like drone-resistant cryptography, AI-driven healthcare devices (USteth, ThalaScreen), and predictive analytics for disaster management. 🛰️ As an inventor on a patented drone-detection system and mentor to numerous interns and students across global institutions, she demonstrates strong leadership and social impact. 🌍 Recognized with awards and competitive startup funding, Prof. Khan’s strategic vision and interdisciplinary contributions make her a standout candidate for the Best Researcher Award. 🏆

Professional Profile

📚 Education

Professor Misha Urooj Khan holds a Master’s degree in Electronics Engineering from the University of Engineering & Technology Taxila (2019–2022), specializing in real-time FPGA-based Simultaneous Localization and Mapping (SLAM). She earned her B.Sc. in Electronics Engineering (2015–2019) from the same institution, focusing on embedded systems, FPGA design, and neural networks, and implemented an automatic wheezing detection system for her thesis. With a solid grounding in both hardware and software design, she developed strong analytical and technical skills in digital design, signal processing, and machine learning. Her rigorous academic training laid the foundation for her multidisciplinary research career, enabling seamless integration of theory and application across quantum computing, AI-enhanced embedded systems, cyber‑physical systems, and robotics. These educational credentials articulate her commitment to innovation and technology-driven problem solving.

💼 Professional Experience

Professor Khan’s career spans internationally recognized institutions such as CERN, NCP, COMSATS, UET, and King Fahd University. As a Software Developer for CERN’s CMS experiment (2024–2025), she developed database schemas, business logic, and automated migrations, contributing to high-performance scientific computing environments. At Open Quantum Initiative and NCP (2023–2026), she implemented quantum machine learning, error mitigation techniques, sensor-fusion robotics, and AI-driven predictive systems. Her research at COMSATS (2022) focused on intelligent UAV detection using edge devices. Earlier roles included designing biomedical signal-processing systems and embedded real-time detection boards (UET Taxila, 2018–2022). Recently, at King Fahd University, she’s spearheading lightweight, quantum-resistant cybersecurity protocols for drones. Across each role, she has demonstrated exceptional technical proficiency, leadership in mentoring interns, and impactful contributions to system deployment, publication, and product innovation.

🔬 Research Interests

Professor Khan’s research spans quantum computing, artificial intelligence, embedded systems, and cybersecurity—integrating these domains to solve complex real-world problems. Within quantum computing, she investigates noise modeling, error mitigation, quantum machine learning (QSVM, QNN, VQC), and oracle‑based functions on IBM quantum processors. Her AI/ML projects include domain-generalized image translation frameworks like R2TGenNet and T2RGenNet, predictive fault‑diagnosis for rotary equipment, YOLO-based object detection, and AI‑enhanced decision support. In embedded systems, she specializes in FPGA‑based SLAM, real‑time sensor fusion (LiDAR, RGB/depth cameras, IMU), and custom hardware for biomedical signal acquisition. Her current interest lies in quantum‑resistant cryptographic protocols tailored for UAV communication systems. She is passionate about bridging quantum‑AI with cybersecurity to enable secure, intelligent, and autonomous applications across healthcare, robotics, disaster response, and aerospace.

🏅 Awards and Honors

Professor Khan has earned recognition across academia, innovation, and professional excellence. She holds 658 citations (2025) and was awarded 2nd place for her presentation on “Noise Modeling and Error Mitigation on Quantum Computers” at ICTP Trieste, March 2024. Other distinctions include runner-up in the PMNIA startup pitching (June 2023), Best Presenter shields at IBCAST’23 and IEEC’21, and funding awards for USteth and ThalaScreen prototypes (2022). Her startup PAK‑AeroSafe qualified at regional and national levels and achieved runner-up status at Hackathon’23 (February 2023). Academic engagement includes first positions in university fairs (2019), community science awards since 2012, and multiple national scholastic honors. These accolades highlight her consistent excellence in research, presentation, innovation, and community engagement.

🛠️ Research Skills

Professor Khan possesses a versatile and comprehensive set of skills across computing, hardware design, and data science. She is adept in FPGA/embedded system design (Verilog/VHDL), real‑time algorithm development, and robotics navigation with ROS and Jetson hardware. Her ML proficiency spans classic and deep learning (SVM, KNN, RF, YOLOv5-v11, VGG16/19, GANs, Autoencoder), and she designs bespoke frameworks (R2TGenNet, T2RGenNet). In quantum research, she handles noise modeling, quantum gate design, error mitigation, oracle functions, and algorithm implementation on IBM quantum simulators and hardware. She also excels in sensor fusion (LiDAR/IMU/RGB/Depth), GUI creation, digital signal processing, and AI-based healthcare tools. Her programming languages include Python, Qiskit, MATLAB, and Linux-based deployment, complemented by strong skills in mentoring, proposal writing, and cross-disciplinary collaboration.

Publications Top Notes 📝

  • Title: A comparative survey of lidar-slam and lidar based sensor technologies
    Authors: MU Khan, SAA Zaidi, A Ishtiaq, SUR Bukhari, S Samer, A Farman
    Year: 2021
    Citations: 156
    Source: Mohammad Ali Jinnah University International Conference on Computing

  • Title: Artificial neural network-based cardiovascular disease prediction using spectral features
    Authors: MU Khan, S Samer, MD Alshehri, NK Baloch, H Khan, F Hussain, SW Kim, et al.
    Year: 2022
    Citations: 39
    Source: Computers and Electrical Engineering 101, Article 108094

  • Title: Classification of eye diseases and detection of cataract using digital fundus imaging (DFI) and inception-V4 deep learning model
    Authors: A Raza, MU Khan, Z Saeed, S Samer, A Mobeen, A Samer
    Year: 2021
    Citations: 34
    Source: 2021 International Conference on Frontiers of Information Technology (FIT)

  • Title: Safespace mfnet: Precise and efficient multifeature drone detection network
    Authors: MU Khan, M Dil, MZ Alam, FA Orakazi, AM Almasoud, Z Kaleem, C Yuen
    Year: 2023
    Citations: 33
    Source: IEEE Transactions on Vehicular Technology 73(3), 3106-3118

  • Title: Spectral analysis of lung sounds for classification of asthma and pneumonia wheezing
    Authors: SZH Naqvi, M Arooj, S Aziz, MU Khan, MA Choudhary
    Year: 2020
    Citations: 31
    Source: 2020 International Conference on Electrical, Communication, and Computer

  • Title: Supervised machine learning based fast hand gesture recognition and classification using electromyography (EMG) signals
    Authors: MU Khan, H Khan, M Muneeb, Z Abbasi, UB Abbasi, NK Baloch
    Year: 2021
    Citations: 29
    Source: 2021 International Conference on Applied and Engineering Mathematics (ICAEM)

  • Title: A review of system on chip (SoC) applications in Internet of Things (IoT) and medical
    Authors: A Ishtiaq, MU Khan, SZ Ali, K Habib, S Samer, E Hafeez
    Year: 2021
    Citations: 28
    Source: ICAME21, International Conference on Advances in Mechanical Engineering

  • Title: Identification of leaf diseases in potato crop using Deep Convolutional Neural Networks (DCNNs)
    Authors: Z Saeed, MU Khan, A Raza, N Sajjad, S Naz, A Salal
    Year: 2021
    Citations: 23
    Source: 16th International Conference on Emerging Technologies (ICET)

  • Title: Classification of Multi-Class Cardiovascular Disorders using Ensemble Classifier and Impulsive Domain Analysis
    Authors: MU Khan, SZZ Ali, A Ishtiaq, K Habib, T Gul, A Samer
    Year: 2021
    Citations: 22
    Source: Mohammad Ali Jinnah University International Conference on Computing

  • Title: Automated system design for classification of chronic lung viruses using non-linear dynamic system features and k-nearest neighbour
    Authors: MU Khan, A Farman, AU Rehman, N Israr, MZH Ali, ZA Gulshan
    Year: 2021
    Citations: 22
    Source: Mohammad Ali Jinnah University International Conference on Computing

  • Title: Embedded system design for real-time detection of asthmatic diseases using lung sounds in cepstral domain
    Authors: MU Khan, A Mobeen, S Samer, A Samer
    Year: 2021
    Citations: 22
    Source: 6th International Electrical Engineering Conference (IEEC)

  • Title: Stability enhancement of commercial Boeing aircraft with integration of PID controller
    Authors: AU Rehman, MU Khan, MZH Ali, MS Shah, MF Ullah, M Ayub
    Year: 2021
    Citations: 21
    Source: 2021 International Conference on Applied and Engineering Mathematics (ICAEM)

  • Title: Classification of pulmonary viruses X-ray and detection of COVID-19 based on invariant of inception-V3 deep learning model
    Authors: Z Saeed, MU Khan, A Raza, H Khan, J Javed, A Arshad
    Year: 2021
    Citations: 19
    Source: 2021 International Conference on Computing, Electronic and Electrical

  • Title: Classification of phonocardiography based heart auscultations while listening to Tilawat-e-Quran and music using vibrational mode decomposition
    Authors: MU Khan, S Samer, A Samer, A Mobeen, A Arshad, H Khan
    Year: 2021
    Citations: 18
    Source: 2021 International Conference on Applied and Engineering Mathematics (ICAEM)

  • Title: MSF-GhostNet: Computationally-Efficient YOLO for Detecting Drones in Low-Light Conditions
    Authors: M Misbah, MU Khan, Z Kaleem, A Muqaibel, MZ Alam, R Liu, C Yuen
    Year: 2024
    Citations: 5
    Source: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

  • Title: Multi-Sensor Fusion for Remote Sensing of Metallic and Non-metallic Object Classification in Complex Soil Environments and at Different Depths
    Authors: MU Khan, MA Kamran, WR Khan, MM Ibrahim, MU Ali, SW Lee
    Year: 2024
    Citations: 5
    Source: IEEE Transactions on Geoscience and Remote Sensing

  • Title: Mathematical Modelling and Implementation of 2DOF Standard, Parallel & Series PID Controllers
    Authors: AU Rehman, MU Khan, MT Rehman, W Shehzad, S Zaman, MW Khan
    Year: 2021
    Citations: 5
    Source: 6th International Multi-Topic ICT Conference (IMTIC)

  • Title: Diabetes Prediction Using an Optimized Variational Quantum Classifier
    Authors: WR Khan, MA Kamran, MU Khan, MM Ibrahim, KS Kim, MU Ali
    Year: 2025
    Citations: 4
    Source: International Journal of Intelligent Systems 2025 (1), Article 1351522

  • Title: Deep Learning Empowered Fast and Accurate Multiclass UAV Detection in Challenging Weather Conditions
    Authors: MU Khan, M Dil, M Misbah, FA Orakazi, MZ Alam, Z Kaleem
    Year: 2022
    Citations: 4
    Source: Conference Publication

  • Title: Brain Tumor Detection Based on Magnetic Resonance Imaging Analysis Using Segmentation, Thresholding and Morphological Operations
    Authors: MU Khan, H Khan, A Arshad, NK Baloch, A Shaheen, F Tariq
    Year: 2021
    Citations: 3
    Source: 6th International Multi-Topic ICT Conference (IMTIC)

  • Title: SMSAT: A Multimodal Acoustic Dataset and Deep Contrastive Learning Framework for Affective and Physiological Modeling of Spiritual Meditation
    Authors: A Suleman, Y Alkhrijah, MU Khan, H Khan, MAHA Faiz, MA Alawad, et al.
    Year: 2025
    Source: arXiv preprint arXiv:2505.00839

  • Title: Migration of CADI to Fence
    Authors: M Imran, MU Khan, RMA Shad, A Samantas, A Pfeiffer, J Closier
    Year: 2025

✅ Conclusion

Professor Misha Urooj Khan exemplifies a visionary researcher whose interdisciplinary breadth and leadership set her apart. With robust academic credentials, global professional experience at centers like CERN and NCP, and impactful publications and patents, she drives innovation in quantum-AI, embedded systems, robotics, and cybersecurity. Her product-oriented mindset—evident in startups like USteth and PAK‑AeroSafe—coupled with her mentoring of junior researchers, underscores both strategic vision and social impact. Her consistent accolades and scholarly presence (658 citations) affirm her research quality and influence. Combining groundbreaking technical achievements, real-world applications, and academic excellence, Professor Khan stands as a compelling candidate for top-tier research distinctions and awards.

Dipesh | Applied Mathematics | Best Researcher Award

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Dr. Dipesh | Applied Mathematics | Best Researcher Award

Assistant Professor at SR University, India

Dr. Dipesh is a dynamic and visionary scholar 🌟 whose research bridges the frontiers of mathematics, engineering, and innovation. With a profound commitment to academic excellence 📚, he has contributed significantly to applied mathematics and interdisciplinary modeling. His scholarly journey is marked by a trail of high-impact publications, collaborative projects, and a passion for advancing scientific knowledge through innovative methods 🧠🔬. Dr. Dipesh’s work seamlessly integrates theory and application, addressing real-world challenges with mathematical precision. As a dedicated educator and researcher 👨‍🏫, he inspires students and peers alike, fostering a culture of curiosity and discovery. Known for his strategic thinking and problem-solving acumen 🎯, he is a driving force in the global research community. His contributions not only elevate his field but also pave the way for future innovations in science and technology 🌐. Dr. Dipesh embodies the spirit of intellectual rigor, innovation, and global impact. 🚀

Professional Profile 

Google Scholar
Scopus Profile
ORCID Profile

Education 🎓

Dr. Dipesh’s academic voyage began with a thirst for discovery, leading him to earn top distinctions across his educational milestones. From undergraduate brilliance to postgraduate mastery, he consistently demonstrated scholarly agility. His doctoral pursuit was nothing short of transformative, delving deep into the realms of applied mathematics and computational modeling. With a blend of analytical sharpness and creative thought 💡, he shaped a thesis that resonated across disciplines. Through internships, fellowships, and global academic exposure 🌍, Dr. Dipesh embraced both classical theory and cutting-edge advancements, enriching his intellectual toolkit. His academic record reflects not just excellence, but evolution — an unrelenting quest for understanding the mathematical patterns that shape our world. With each degree, he built not just knowledge, but vision — a vision that continues to inspire every academic and professional arena he enters.

Professional Experience 

With a career rooted in purpose and propelled by passion, Dr. Dipesh has crafted a vibrant professional canvas. From research institutions to academic think tanks, he has donned multiple hats — as a lecturer, mentor, consultant, and principal investigator. His work echoes across domains like mathematical modeling, computational simulations, and interdisciplinary analytics 🔍. Through strategic collaborations and leadership in diverse research initiatives, he has translated theory into impact. His roles have spanned curriculum development, peer review, and technological innovation, each enriching his expertise. Dr. Dipesh brings not just experience, but engagement — an unwavering drive to uplift scientific inquiry and educational transformation 📈. Whether guiding students or steering complex projects, he embodies professionalism with a human touch. His journey is marked by meaningful milestones that reflect both depth and diversity — a true blend of intellect and initiative in motion.

Research Interest 🔬

Dr. Dipesh’s research universe orbits around the fusion of abstract theory and practical relevance. He thrives at the intersection of applied mathematics, machine learning, data-driven modeling, and real-world system optimization 🌐. Passionate about unraveling complex dynamics, his work ventures into fractional calculus, differential equations, computational intelligence, and interdisciplinary simulations. Dr. Dipesh views research as a living organism — evolving, adapting, and contributing to the scientific ecosystem. His investigations are not limited to academic curiosity; they aim to decode pressing global issues using mathematical clarity and innovation 🧠. From predictive algorithms to mathematical physics, he embraces complexity with elegance. A firm believer in cross-domain synergy, his inquiries often collaborate with fields like biology, environmental science, and artificial intelligence 🤝. Driven by both rigor and relevance, his research is a beacon for transformative insight and sustainable innovation.

Awards and Honors 🏆

Dr. Dipesh’s accolades reflect his commitment to excellence and his pioneering spirit. Recognized both nationally and internationally, he has received honors that celebrate not just his research, but his contribution to education and societal advancement 🌟. From best paper awards to research fellowships, he has built a distinguished legacy of merit. These recognitions stem from competitive platforms where innovation meets influence. Whether through academic forums, institutional commendations, or international conferences 🌍, his work has earned applause and admiration. His awards are more than trophies — they are testaments to his intellectual resilience, collaborative ethos, and trailblazing ideas. A mentor to many and a leader in thought, Dr. Dipesh’s decorated career is a living narrative of perseverance, curiosity, and global contribution 🏅. These honors reaffirm his role as a changemaker in the ever-expanding sphere of mathematical sciences.

Conclusion 🧭

Dr. Dipesh stands as a luminary whose path fuses intellect, imagination, and impact. His academic roots, professional ventures, and research brilliance have built a profile defined by depth and dynamism 🌈. More than just a mathematician, he is a storyteller of systems, a bridge between theory and transformation. Every equation he solves and every model he constructs echoes his belief in knowledge as a catalyst for change. As a scholar, mentor, and visionary, he continues to shape minds and spark innovation across continents 📚✨. Dr. Dipesh doesn’t just follow the path — he crafts it, inspiring future thinkers to ask bold questions and dream without limits. His legacy is not only found in published pages or professional positions, but in the lives he touches and the paradigms he shifts 🔄. He is a vibrant force — ever-evolving, ever-inspiring, and ever-forward.

Publications Top Notes

  • 🌿 Effect of time delay on dynamic of plant competition under allelopathy
    Authors: P.K. Dipesh
    Year: 2022
    Citations: 11
    Source: Mathematical Methods in the Applied Sciences

  • 🌲 Optimizing industrial growth through alternative forest biomass resources: A mathematical model using DDE
    Authors: Dipesh, P. Kumar, C. Cattani
    Year: 2023
    Citations: 10
    Source: International Journal of Mathematics and Computer in Engineering

  • 🌱 Effect of time-lag on two mutually competing plant populations under allelochemicals
    Authors: P.K. Dipesh
    Year: 2022
    Citations: 10
    Source: Journal of Physics: Conference Series 2267 (1), 012019

  • 🔬 Enhancing high frequency magneto-dielectric performance with exchange-coupled garnet/spinel ferrite composites
    Authors: Dipesh, A. Sharma, H. Mahajan, N. Aggarwal, S. Sinha, A.K. Srivastava
    Year: 2023
    Citations: 6
    Source: Nano-Structures & Nano-Objects 36, 101035

  • 🧪 Investigating the impact of toxicity on plant growth dynamics through the zero of a fifth-degree exponential polynomial: A mathematical model using DDE
    Authors: Dipesh, P.K.
    Year: 2023
    Citations: 6
    Source: Chaos, Solitons & Fractals 171, 113457

  • 🌾 Modelling the stimulatory and inhibitory allelopathic effects on competing plant populations
    Authors: Dipesh, P. Kumar
    Year: 2022
    Citations: 6
    Source: AIP Conference Proceedings 2435 (1)

  • 📈 Modeling and analysis of demand-supply dynamics with a collectability factor using DDE in economic growth via the Caputo operator
    Authors: Dipesh, Q. Chen, P. Kumar, H.M. Baskonus
    Year: 2024
    Citations: 5
    Source: AIMS Mathematics 9 (3), 7471–7191

  • 🌿 Sensitivity and Directional Analysis of Two Mutually Competing Plant Population Under Allelopathy Using DDE
    Authors: Dipesh, P. Kumar
    Year: 2023
    Citations: 3
    Source: Mathematics and Computing, 605–620

  • 🌱 Role of Delay on Two Competing Plant Populations Under the Allelopathic Effect
    Authors: Dipesh, P. Kumar
    Year: 2022
    Citations: 2
    Source: Emerging Advancements in Mathematical Sciences, 39–58

  • 💰 Stability Analysis of GDP-National Debt Dynamics using Delay Differential Equation
    Authors: Q. Chen, Dipesh, P. Kumar, H.M. Baskonus
    Year: 2024
    Citations: 1
    Source: Fractals, 2540059

  • 🌿 A novel approach to 6th-order DDEs in toxic plant interactions and soil impact: beyond Newton-Raphson
    Authors: Dipesh, P. Kumar
    Year: 2024
    Citations: 1
    Source: Physica Scripta 99 (6), 065236

  • 🧲 Exchange-coupling enhanced: Tailoring structural and magnetic properties of Dy iron garnet ferrite nanoparticles via La substitution
    Authors: Dipesh, A. Sharma, P. Kumar, J.V. Vas, R. Medwal, A.K. Srivastava
    Year: 2024
    Citations: 1
    Source: Journal of Materials Research, 1–18

  • 📊 On the equilibrium point and Hopf-Bifurcation analysis of GDP-national debt dynamics under delayed investment: A new DDE model
    Authors: Dipesh, Q. Chen, P. Kumar, H.M. Baskonus
    Year: 2024
    Citations: 1
    Source: Alexandria Engineering Journal 91, 510–515

  • 🔍 Unlocking the Potential of Garnet Ferrites: A Comprehensive Review on Properties, Preparation Methods, and Applications
    Authors: A. Sharma, Dipesh
    Year: 2024
    Citations: 1
    Source: Materials Performance and Characterization 13 (1), 1–36

  • 🔋 Status and Prospects of GdIG Garnet Ferrites for Energy Storage Devices: A Review
    Authors: A. Sharma, Dipesh, H. Mahajan, A.K. Srivastava
    Year: 2024
    Citations: 1
    Source: Next Generation Materials for Sustainable Engineering, 174–186

  • 🌲 Delay DDE model of forest biomass and competition between wood‐based and synthetic‐based industries
    Authors: Dipesh, P. Kumar
    Year: 2023
    Citations: 1
    Source: Mathematical Methods in the Applied Sciences

  • 🫀 Modelling the Role of Delay in Blood Flow Dynamics in the Human Body using DDE
    Authors: Dipesh, P. Kumar
    Year: 2025
    Citations: –
    Source: Physica A: Statistical Mechanics and its Applications, 130602

  • 💹 On modeling the impact of delay on stock pricing fluctuations using DDE
    Authors: Y. Wang, Dipesh, P. Kumar, H.M. Baskonus, W. Gao
    Year: 2025
    Citations: –
    Source: Physica A: Statistical Mechanics and its Applications, 130601

  • 🍃 Modeling and analyzing delay in plant responses under toxicity
    Authors: Dipesh, P. Kumar, H.M. Baskonus
    Year: 2025
    Citations: –
    Source: Advances in Computational Methods and Modeling for Science and Engineering

  • 🌱 Effect of time delay on directional and stability analysis of plant competition for allelochemicals study
    Authors: Dipesh, P. Kumar, H.M. Baskonus, A. Ciancio
    Year: 2025
    Citations: –
    Source: Advances in Computational Methods and Modeling for Science and Engineering

 

Sabah Kausar | Applied Mathematics | Young Scientist Award

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Dr. Sabah Kausar | Applied Mathematics | Young Scientist Award

University of Gujrat, Pakistan

Dr. Sabah Kausar is a dedicated physicist and researcher specializing in nanomaterials, photocatalysis, and environmental sustainability. With an MPhil in Physics from the University of Gujrat, her research focuses on synthesizing and characterizing advanced nanocomposites for applications in water purification, antimicrobial treatments, and food preservation. She has expertise in XRD, SEM, FTIR, PL, UV-Vis spectroscopy, and EDX, demonstrating a strong technical background. Her publications on Ag-doped BiVO₄ and BiVO₄/ZnO nanocomposites highlight significant advancements in photocatalytic degradation and extended shelf life of fruits. Passionate about interdisciplinary research, Dr. Kausar’s work bridges nanotechnology, environmental science, and material physics. She aspires to expand her contributions through international collaborations, high-impact publications, and practical industrial applications. With a keen focus on sustainability and innovation, she is a promising young scientist making impactful contributions to applied physics and nanotechnology.

Professional Profile 

Education

Dr. Sabah Kausar holds an MPhil in Physics from the University of Gujrat, where she conducted pioneering research on nanomaterials and their photocatalytic and antimicrobial properties. Her thesis focused on the synthesis and characterization of BiVO₄-based nanocomposites for enhancing the shelf life of fruits and environmental remediation. Prior to her MPhil, she earned a BS (Honors) in Physics, where she developed a strong foundation in experimental, numerical, and conceptual physics. Her academic journey has been marked by excellence in material physics, spectroscopy, and nanotechnology applications. Additionally, she is currently pursuing a Bachelor of Education (BEd), reinforcing her ability to contribute to academia. With a solid educational background, she has developed expertise in advanced characterization techniques such as XRD, SEM, FTIR, PL, and UV-Vis spectroscopy, which are essential for analyzing the structural, optical, and morphological properties of nanomaterials.

Professional Experience

Dr. Sabah Kausar is an emerging scientist with expertise in photocatalytic nanomaterials, environmental physics, and material characterization. During her MPhil research, she synthesized and tested Ag-doped BiVO₄ and BiVO₄/ZnO nanocomposites to improve photocatalytic activity and antimicrobial performance. Her research has practical implications in water purification, environmental remediation, and food preservation. She has collaborated with interdisciplinary teams to analyze nanoparticle efficiency using XRD, SEM, FTIR, and UV-Vis spectroscopy. She has also contributed to scientific literature through high-impact publications focusing on nanotechnology-based solutions for sustainability. As a physicist, she excels in team collaboration, research execution, and analytical problem-solving. Beyond research, her pursuit of a BEd degree equips her with academic and teaching skills, enhancing her ability to mentor and educate future scientists. With a passion for advancing nanomaterials for environmental and biomedical applications, she is poised to make significant contributions to applied physics and sustainable technology.

Research Interest

Dr. Sabah Kausar’s research interests lie in nanotechnology, photocatalysis, environmental sustainability, and antimicrobial nanomaterials. She focuses on synthesizing and characterizing functional nanocomposites for applications in water purification, energy harvesting, and food preservation. Her expertise extends to advanced material characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence spectroscopy (PL), and UV-Vis analysis, which she employs to explore optical, structural, and chemical properties of materials. She is particularly interested in the development of eco-friendly nanomaterials to combat water pollution and food spoilage. Her work on TiO₂/BiVO₄ nanocomposites for dye and antibiotic degradation has demonstrated significant potential for environmental applications. Additionally, she is keen on interdisciplinary research collaborations to bridge the gap between material science, environmental physics, and biomedicine. With a strong foundation in experimental physics and nanotechnology, she aspires to contribute to cutting-edge advancements in sustainable science and clean energy.

Awards and Honors

Dr. Sabah Kausar has earned recognition for her innovative contributions to nanotechnology and environmental sustainability. Her MPhil research on BiVO₄-based nanomaterials has been widely acknowledged for its practical implications in photocatalysis, antimicrobial applications, and food preservation. She has presented her work at national and international awards, showcasing her expertise in material characterization and sustainable nanotechnology. Additionally, her high-impact publications in peer-reviewed journals reflect her strong research capabilities and commitment to scientific advancement. Her ability to bridge physics, chemistry, and environmental science has positioned her as a promising researcher. As she continues to develop innovative nanomaterials for real-world applications, she remains committed to academic excellence and collaborative research projects. With her growing contributions to scientific knowledge and sustainability-focused solutions, she is a strong candidate for Young Scientist Awards and similar recognitions in the fields of nanotechnology, applied physics, and environmental research.

Conclusion

Dr. Sabah Kausar is a rising physicist and nanotechnology researcher committed to solving environmental and sustainability challenges through innovative material science. With a strong academic background, hands-on research experience, and a passion for applied physics, she has contributed to the development of photocatalytic and antimicrobial nanomaterials. Her work has significant implications for clean energy, water purification, and food preservation, demonstrating the power of interdisciplinary scientific advancements. As a young scientist, she continues to explore new frontiers in nanotechnology, with a focus on sustainable applications. Her ability to integrate material characterization, experimental physics, and environmental research makes her a promising scientific leader. With continued collaborations, high-impact research, and academic contributions, she is well-positioned to make lasting contributions in physics, nanotechnology, and sustainability science.

Publications Top Noted

 

LinTian Luh | Applied Mathematics | Numerical Analysis Research Award

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Dr. LinTian Luh | Applied Mathematics | Numerical Analysis Research Award

Dr. Lin-Tian Luh is a distinguished mathematician specializing in radial basis functions, approximation theory, numerical mathematics, and topology. With a Ph.D. from the University of Göttingen, he has made significant contributions to the field, particularly in developing error bounds for high-dimensional interpolation and advancing the choice theory of shape parameters. Over his academic career at Providence University, where he served as a lecturer, associate professor, and full professor, he has been instrumental in enhancing research environments and collaborating internationally, notably with Professor R. Schaback. Dr. Luh has published extensively in high-impact journals, presented at major awards worldwide, and held editorial roles in reputable mathematical journals. His groundbreaking work on shape parameter selection has gained international recognition, solving longstanding challenges in the field. Honored multiple times for research excellence, he continues to push the boundaries of numerical analysis and computational mathematics, making profound impacts on scientific advancements.

Professional Profile 

Scopus Profile
ORCID Profile

Education

Dr. Lin-Tian Luh obtained his Ph.D. in Mathematics from the University of Göttingen, Germany, where he studied under leading experts in numerical analysis and approximation theory. His doctoral research focused on radial basis functions and their applications in high-dimensional interpolation. Prior to his Ph.D., he completed his undergraduate and master’s studies in Taiwan, building a strong foundation in pure and applied mathematics. Throughout his academic journey, he demonstrated exceptional analytical skills and a deep passion for solving complex mathematical problems. His international education provided him with a broad perspective, allowing him to integrate diverse mathematical techniques into his research. Exposure to rigorous mathematical training at Göttingen further refined his expertise in error estimation and shape parameter selection. His academic achievements laid the groundwork for a successful career in both theoretical and applied mathematics, enabling him to contribute significantly to the advancement of numerical methods in scientific computation.

Professional Experience

Dr. Lin-Tian Luh has had a distinguished academic career, spanning decades of research, teaching, and mentorship. He began as a lecturer at Providence University in Taiwan, where he quickly established himself as an authority in numerical mathematics. Rising through the ranks to associate professor and later full professor, he played a pivotal role in shaping the university’s mathematics curriculum and fostering a strong research environment. He has collaborated extensively with international scholars, including Professor R. Schaback, contributing to groundbreaking advancements in radial basis function interpolation. Dr. Luh has also held visiting research positions at prestigious institutions, further strengthening his global academic impact. His dedication to teaching has inspired numerous students to pursue research in computational mathematics. Beyond academia, he has served on editorial boards of leading mathematical journals and as a reviewer for high-impact publications, solidifying his reputation as a key figure in numerical analysis and approximation theory.

Research Interest

Dr. Lin-Tian Luh’s research interests lie in numerical analysis, radial basis function (RBF) interpolation, approximation theory, and topology. He has made substantial contributions to high-dimensional interpolation techniques, particularly in error estimation and shape parameter selection for RBF methods. His work on developing optimal strategies for shape parameter choice has addressed longstanding challenges in computational mathematics, influencing applications in engineering, data science, and machine learning. He is also deeply engaged in the theoretical aspects of approximation theory, exploring new methods to improve the efficiency and accuracy of numerical algorithms. Dr. Luh’s research extends into applied topology, where he investigates connections between geometric structures and computational models. His interdisciplinary approach has led to collaborations across various fields, reinforcing the importance of mathematical theory in real-world problem-solving. With numerous publications in top-tier journals, his work continues to shape the evolving landscape of numerical mathematics and scientific computation.

Awards and Honors

Dr. Lin-Tian Luh has received multiple accolades for his exceptional contributions to mathematics, particularly in numerical analysis and approximation theory. He has been recognized by prestigious mathematical societies and institutions for his pioneering work in radial basis function interpolation. His research on shape parameter selection has earned international acclaim, leading to invitations as a keynote speaker at major mathematical awards. Dr. Luh has also been honored with excellence in research awards from Providence University, where his work has significantly advanced the institution’s academic reputation. In addition, he has received grants and fellowships supporting his innovative research, further validating his impact in the field. His editorial contributions to leading mathematical journals have also been acknowledged, highlighting his influence in shaping contemporary numerical mathematics. These honors reflect his dedication, originality, and profound impact on both theoretical and applied mathematics, reinforcing his legacy as a leader in computational and approximation theory.

Conclusion

Dr. Lin-Tian Luh is a renowned mathematician whose work in numerical analysis, radial basis function interpolation, and approximation theory has significantly influenced the field. With a strong educational background from the University of Göttingen and an illustrious academic career at Providence University, he has played a crucial role in advancing research and mentoring future generations of mathematicians. His collaborations with international scholars and contributions to high-dimensional interpolation techniques have provided groundbreaking insights into shape parameter selection and error estimation. Recognized globally for his research excellence, he has received multiple awards and honors, further establishing his prominence in mathematical sciences. Dr. Luh’s work continues to inspire and drive progress in numerical computation, bridging theoretical advancements with practical applications. His dedication to expanding mathematical knowledge and fostering innovation ensures that his contributions will have a lasting impact on the field, shaping the future of approximation theory and scientific computing.

Publications Top Noted

  • The Shape Parameter in the Shifted Surface Spline—A Sharp and Friendly Approach

    • Author: Lin-Tian Luh
    • Year: 2024
    • Source: Mathematics (MDPI)

  • Solving Poisson Equations by the MN-Curve Approach

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Mathematics (MDPI)

  • A Direct Prediction of the Shape Parameter in the Collocation Method of Solving Poisson Equation

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Mathematics (MDPI)

  • The Shape Parameter in the Shifted Surface Spline—An Easily Accessible Approach

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Mathematics (MDPI)

  • A Direct Prediction of the Shape Parameter—A Purely Scattered Data Approach

    • Author: Lin-Tian Luh
    • Year: 2020
    • Source: Engineering Analysis with Boundary Elements (EABE)

  • The Choice of the Shape Parameter–A Friendly Approach

    • Author: Lin-Tian Luh
    • Year: 2019
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • The Mystery of the Shape Parameter III

    • Author: Lin-Tian Luh
    • Year: 2016
    • Source: Applied and Computational Harmonic Analysis (Elsevier)

  • The Mystery of the Shape Parameter IV

    • Author: Lin-Tian Luh
    • Year: 2014
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • The Shape Parameter in the Gaussian Function II

    • Author: Lin-Tian Luh
    • Year: 2013
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • The Shape Parameter in the Gaussian Function

    • Author: Lin-Tian Luh
    • Year: 2012
    • Source: Computers and Mathematics with Applications (Elsevier)

  • The Shape Parameter in the Shifted Surface Spline III

    • Author: Lin-Tian Luh
    • Year: 2012
    • Source: Engineering Analysis with Boundary Elements (Elsevier)

  • Evenly Spaced Data Points and Radial Basis Functions

    • Author: Lin-Tian Luh
    • Year: 2011
    • Source: WIT Transactions on Modelling and Simulation

  • The Crucial Constants in the Exponential-Type Error Estimates for Gaussian Interpolation

    • Author: Lin-Tian Luh
    • Year: 2008
    • Source: Analysis in Theory and Applications

  • A Direct Prediction of the Shape Parameter in the Collocation Method of Solving Poisson Equation (Preprint)

    • Author: Lin-Tian Luh
    • Year: 2022
    • Source: Multidisciplinary Digital Publishing Institute (MDPI Preprints)