Manjunath Thindlu Rudrappa | Engineering | Best Researcher Award

Mr. Manjunath Thindlu Rudrappa | Engineering | Best Researcher Award

Mr. Manjunath Thindlu Rudrappa, Fraunhofer Institute for High Frequency Physics and Radar Techniques, Germany

Manjunath Thindlu Rudrappa is an accomplished researcher specializing in radar signal processing, object tracking, and space object characterization. He is currently a Doctoral Researcher at Fraunhofer FHR, Germany, focusing on phased array radar networks. With a strong academic background from RWTH Aachen University and Visvesvaraya Technological University, his expertise spans ISAR imaging, interferometry, and machine learning applications in radar technology. He has contributed significantly to the field through high-impact publications and innovative research in MIMO radar systems. Manjunath has also worked with industry leaders such as Bosch and Fraunhofer, gaining extensive experience in embedded systems and radar post-processing. His research excellence has been recognized with prestigious awards, including the Young Scientist Award and the Argus Science Award. Passionate about advancing radar and space technology, he continues to drive innovation in signal processing and object detection methodologies. 🚀📡

Publication Profile

Google Scholar

📚 Education

Manjunath earned his Bachelor of Engineering (B.E.) in Electronics and Communication from Visvesvaraya Technological University, India, graduating with an impressive 86.41% aggregate. His bachelor thesis focused on developing an intelligent paradigm for electric vehicles using buck-boost converters, super-capacitors, and regenerative braking, under the guidance of Dr. Bhakthavatsalam and Mr. Gowranga K.H from IISc Bangalore. He pursued his Master of Science (M.Sc.) in Communication Engineering at RWTH Aachen University, Germany, achieving a 1.5 aggregate. His master thesis at Fraunhofer FHR was on vital parameter detection of moving persons using MIMO radar, supervised by Prof. Dr.-Ing Peter Knott and Dr.-Ing Reinhold Herschel. Currently, he is a PhD researcher at RWTH Aachen University, working on the characterization of resident space objects using phased array radar networks, pushing the boundaries of radar and space object detection technology. 🎓📡

💼 Experience

Manjunath began his career as an Embedded Software Engineer at Robert Bosch Engineering and Business Solutions Limited (2014–2017) in India, working on software development for automotive systems. Moving to Bosch Engineering GmbH, Germany, he served as an Embedded Application Software Developer (2018–2019), specializing in software solutions for automotive applications. His transition to Fraunhofer FHR in Germany marked his entry into radar research, where he worked as a Work Student (2019–2020) on vital parameter estimation, detection, tracking, and clustering. Since 2020, he has been a Doctoral Researcher and Wissenschaftlicher Mitarbeiter at Fraunhofer FHR, contributing to advanced radar signal processing, ISAR imaging, interferometry, and object tracking. His research spans both defense and space applications, making significant contributions to radar-based object detection and feature extraction techniques. 🔬🚀

🏆 Awards & Honors

Manjunath has received prestigious recognitions for his contributions to radar signal processing and communication technology. In October 2020, he won the Young Scientist Award at the International Radar Symposium in Warsaw, Poland, for his research on vital parameter detection of non-stationary human subjects using MIMO Radar. His master thesis on signal processing and microwave technology earned him the Argus Science Award 2020 from Hensoldt, Germany, recognizing his exceptional contributions to the field. His work has been highly regarded in the academic and industrial research community, reinforcing his status as a leading researcher in radar technology, space object tracking, and embedded systems. 🏅📡

🔬 Research Focus

Manjunath’s research is centered on radar signal processing, object tracking, and space object characterization. His expertise includes ISAR imaging, interferometry, feature extraction, machine learning, and deep learning for radar applications. He has worked extensively with MIMO radar systems, contributing to human vital sign detection, tracking, and clustering. His PhD research explores phased array radar networks for resident space object characterization, a crucial area in space surveillance and satellite tracking. Additionally, he has experience in embedded systems, automotive radar applications, and defense technology, making significant contributions to intelligent sensing and radar post-processing methodologies. His work bridges the gap between academic research and industrial innovation, shaping the future of radar and communication engineering. 🌍📡🚀

Publication Top Notes

1️⃣ Moving human respiration sign detection using mm-wave radar via motion path reconstructionCited by: 17 | Year: 2021 📡👤💨
2️⃣ Vital parameters detection of non-stationary human subject using MIMO radarCited by: 11 | Year: 2020 📡🔬🧍
3️⃣ Distinguishing living and non-living subjects in a scene based on vital parameter estimationCited by: 8 | Year: 2021 🔍👤🏠
4️⃣ Characterisation of resident space objects using multistatic interferometric inverse synthetic aperture radar imagingCited by: 4 | Year: 2024 🛰️📡📊
5️⃣ 3D reconstruction of resident space objects using radar interferometry and nonuniform fast Fourier transform from sparse dataCited by: 4 | Year: 2022 🌍📡📉
6️⃣ Improvements of GESTRA—A phased-array radar network for the surveillance of resident space objects in low-Earth orbitCited by: 2 | Year: 2023 🚀🛰️📶
7️⃣ RSO feature extraction using Super Resolution Wavelets and Inverse Radon TransformCited by: 1 | Year: 2022 📡📊📉
8️⃣ High-resolution human clustering based on complex signal correlation coefficientsCited by: 1 | Year: 2022 🏠📡📊
9️⃣ Characterisation of Resident Space Objects and Synchronisation Error Compensation in Multistatic Interferometric Inverse Synthetic Aperture Radar ImagingYear: 2025 🛰️📡📊
🔟 Clusterung von DetektionenYear: 2022 📡📍🔍

Conclusion

Mr. Manjunath Thindlu Rudrappa has a strong research profile, with high-impact contributions in radar signal processing, object tracking, and communication engineering. His awards, affiliations, and research publications make him a highly suitable candidate for the Research for Best Researcher Award. His expertise in machine learning applications in radar, feature extraction, and interferometry aligns with modern advancements in the field, further strengthening his candidacy.

NIMET YILDIRIM TİRGİL | Engineering | Best Researcher Award

Assoc. Prof. Dr. NIMET YILDIRIM TİRGİL | Engineering | Best Researcher Award 

Associate Professor, at Ankara Yildirim Beyazit University, Turkey.

Dr. Nimet Yildirim Tirgil is an Assistant Professor in Biomedical Engineering at Ankara Yıldırım Beyazıt University. She specializes in biosensor technology, nanomaterials, and electrochemical analysis for environmental and medical applications. With a strong background in bioengineering and biochemistry, Dr. Yildirim Tirgil has led multiple research projects funded by TÜBİTAK and TÜSEB, focusing on biosensing platforms for rapid diagnostics, including COVID-19 antibody detection, tumor DNA analysis, and neurotransmitter monitoring. Her work has led to several patents, high-impact publications, and collaborations in the field of biosensor innovation. Dr. Yildirim Tirgil is committed to advancing analytical chemistry and nanotechnology to develop cutting-edge biosensing solutions.

Professional Profile

Scopus

ORCID

Google Scholar

🎓 Education

Dr. Yildirim Tirgil holds a Ph.D. in Bioengineering from Northeastern University (2016), where she developed next-generation biosensor systems for environmental water quality monitoring under the supervision of Prof. April Z. Gu. She earned her M.Sc. in Biochemistry from Ege University (2009), focusing on bacterial sensors and nanomaterial-modified electrodes, and completed her B.Sc. in Biochemistry (2007) from the same university. Her academic journey has equipped her with interdisciplinary expertise in bioengineering, nanotechnology, and analytical chemistry, enabling her to contribute significantly to biosensor research and development.

💼 Experience

Dr. Yildirim Tirgil has been an Associate Professor at Ankara Yıldırım Beyazıt University since 2018, leading research in biomedical engineering. She has extensive experience in supervising graduate theses, mentoring students in biosensor technology, and developing nanomaterial-based detection systems. She has served as Principal Investigator on numerous national and international research projects, including the development of electrochemical biosensors for detecting environmental pollutants, disease biomarkers, and bioterrorism agents. Her collaborations extend to government-funded research programs and industrial partnerships, advancing biosensing technologies for healthcare, food safety, and environmental monitoring.

🔬 Research Interests

Dr. Yildirim Tirgil’s research focuses on biosensor development, nanotechnology, and electrochemical analysis for medical diagnostics and environmental applications. Her primary interests include:

  • Aptamer-based biosensors for disease biomarker detection.

  • Electrochemical sensing platforms for rapid pathogen and toxin identification.

  • Nanomaterial-modified electrodes for enhanced biosensing performance.

  • Wearable and paper-based biosensors for real-time health monitoring.

  • Smart biosensor integration for food safety and environmental protection.

Her interdisciplinary research integrates biotechnology, analytical chemistry, and materials science to develop innovative biosensing solutions with high sensitivity and specificity.

🏆 Awards & Recognitions

Dr. Yildirim Tirgil has received multiple awards for her groundbreaking work in biosensor technology, including:

  • Best Research Paper Award in Analytical Chemistry (2024).

  • TÜBİTAK Research Excellence Award for contributions to biosensor innovation (2023).

  • Outstanding Young Scientist Award in Biomedical Engineering (2022).

  • Top Cited Researcher Recognition in ACS Applied Polymer Materials (2025).

  • Innovation Award for the development of a smartphone-assisted biosensor system (2021).

Her achievements highlight her impact on sensor technology and analytical diagnostics, making her a leading figure in biosensing research.

📚 Top Noted Publications

Dr. Yildirim Tirgil has published extensively in high-impact journals. Some of her key publications include:

  • Sanattalab, E., Ayni, E., Kaya, K., & Yildirim‐Tirgil, N. (2025).
    Applications of Magnetic Nanocomposites in Lateral Flow Assays.
    Journal: ChemistrySelect
    Summary: This paper explores the use of magnetic nanocomposites in lateral flow assays, enhancing sensitivity and specificity for rapid diagnostic applications.

  • Yildirim-Tirgil, N., Ayni, E., & Kaya, K. (2025).
    Electrochemical Detection of SARS-CoV2 IgG Using Magnetic Nanocomplexes.
    Journal: Journal of Nanoparticle Research
    Summary: The study presents a novel electrochemical biosensor utilizing magnetic nanocomplexes for detecting SARS-CoV-2 IgG antibodies, providing a potential point-of-care diagnostic solution.

  • Avci, M. B., Kocer, F., Yildirim-Tirgil, N., et al. (2025).
    Optofluidic Guided-Mode Resonance Platform for Binding Kinetics.
    Journal: IEEE Sensors Journal
    Summary: This research introduces an optofluidic guided-mode resonance platform for real-time analysis of biomolecular interactions, focusing on binding kinetics measurements.

  • Yildirim-Tirgil, N., et al. (2025).
    Development of a Polypyrrole–Chitosan Nanofiber-Based Enzymatic Biosensor.
    Journal: ACS Applied Polymer Materials
    Summary: The paper discusses the fabrication and characterization of an enzymatic biosensor using polypyrrole–chitosan nanofibers for enhanced sensitivity in biochemical detection.

  • Didarian, R., Ozbek, H. K., Ozalp, V. C., Erel, O., & Yildirim-Tirgil, N. (2024).
    Enhanced SELEX Platforms for Aptamer Selection.
    Journal: Molecular Biotechnology
    Summary: The study proposes improvements in SELEX (Systematic Evolution of Ligands by EXponential Enrichment) methodologies for more efficient aptamer selection, applicable in biosensing and therapeutics.

  • Cuhadar, S. N., Durmaz, H., & Yildirim-Tirgil, N. (2024).
    Multi-Detection of Serotonin and Dopamine via Electrochemical Aptasensor.
    Journal: Chemical Papers
    Summary: This paper introduces an electrochemical aptasensor for the simultaneous detection of serotonin and dopamine, contributing to advancements in neurochemical monitoring.

  • Sahin, S., & Tirgil, N. Y. (2024).
    Circulating Tumor DNA (ctDNA) Detection via Electrochemical Biosensing.
    Journal: MANAS Journal of Engineering
    Summary: The study develops an electrochemical biosensor for detecting circulating tumor DNA (ctDNA), offering potential applications in early cancer diagnostics.

Conclusion

Dr. Nimet Yildirim Tirgil is a highly qualified and competitive candidate for the Best Researcher Award. Her groundbreaking work in biosensors, nanomaterials, and biomedical applications, along with strong project leadership and patent contributions, position her as a leader in her field. Enhancing international collaborations and industry partnerships could further elevate her candidacy.

Ravinesh Chand | Robotics | Best Researcher Award

Mr. Ravinesh Chand | Robotics | Best Researcher Award

Lecturer at Fiji National University, Fiji

Mr. Ravinesh Chand is a dedicated Lecturer in Mathematics with over 21 years of teaching experience in Fiji’s academic and secondary education sectors. He has taught students from diverse backgrounds and is highly skilled in delivering engaging lessons, fostering an interactive learning environment, and conducting research in applied mathematics. Currently pursuing a PhD in Mathematics at the University of the South Pacific (USP), his expertise spans digital signature schemes, mathematical problem-solving, and curriculum development. He has held leadership roles as Head of Department at multiple institutions, contributing to academic excellence. Passionate about student success, he emphasizes innovative teaching methods and collaborative learning. As a researcher, he is committed to generating new knowledge in mathematics. His contributions extend beyond teaching, as he actively mentors students and supports extracurricular activities like soccer coaching. His work is marked by precision, analytical thinking, and a commitment to excellence.

Publication Profile

Scopus

 Orcid

 Google Scholar

Education 🎓📚

Mr. Ravinesh Chand is pursuing a PhD in Mathematics at the University of the South Pacific (USP), focusing on advanced mathematical research. He holds a Master of Science in Mathematics from USP, where he completed a thesis on “Digital Signature Scheme Over Lattices” under the supervision of Dr. M.G.M. Khan and Dr. Maheswara Rao Valluri. He earned a Postgraduate Diploma in Applied Mathematics from USP in 2013, further strengthening his expertise in mathematical modeling and cryptographic systems. His academic foundation was laid with a Bachelor of Education in Mathematics from USP in 2001, equipping him with strong pedagogical skills and mathematical proficiency. Throughout his educational journey, he has demonstrated a commitment to academic excellence, research, and innovative problem-solving. His education has been instrumental in shaping his career as a lecturer and researcher, allowing him to contribute meaningfully to the field of applied mathematics and mathematical education.

Experience 📖👨‍🏫

Mr. Ravinesh Chand has served as a Lecturer in Mathematics at Fiji National University since 2015. Previously, he held leadership roles as Head of the Mathematics and Physics Department at Dudley High School (2014-2015), Suva Grammar School (2013-2014), and Assemblies of God High School (2007-2013). His teaching career began at Waidina Secondary School (2002-2006) as an Acting Head of Department and Mathematics & Physics teacher. Throughout his career, he has led curriculum planning, student engagement, and performance evaluations while mentoring both students and teachers. As a leader, he ensured high-quality teaching standards, facilitated staff development, and implemented intervention strategies for student success. He has also promoted extracurricular activities, including coaching school soccer teams. His extensive experience in academia and secondary education showcases his expertise in mathematical instruction, research, and academic leadership, significantly impacting student learning and institutional development.

Awards and Honors 🏆🎖️

Mr. Ravinesh Chand has been recognized for his outstanding contributions to mathematics education and research. His commitment to academic excellence earned him accolades from Fiji’s leading educational institutions. As Head of Department, he received multiple commendations for his leadership in improving student performance in mathematics and physics. His research on digital signature schemes and applied mathematics has been acknowledged in academic circles, leading to invitations to present his work at conferences. His dedication to mentorship and student development has also been honored through appreciation awards from schools and tertiary institutions. In addition, his extracurricular involvement as a soccer coach has been recognized for fostering teamwork and discipline among students. His excellence in curriculum development, innovative teaching methods, and mathematical research continues to be celebrated, reinforcing his reputation as a distinguished educator and scholar in Fiji’s academic community.

Research Focus 🔬📊

Mr. Ravinesh Chand’s research primarily focuses on applied mathematics, digital signature schemes, cryptography, and mathematical modeling. His Master’s thesis explored “Digital Signature Scheme Over Lattices,” contributing to secure cryptographic protocols. His work involves analyzing the efficiency of mathematical structures in cybersecurity, aiming to enhance encryption techniques. His doctoral research further delves into computational mathematics and algorithmic problem-solving. His academic interests extend to mathematical pedagogy, exploring innovative methods to enhance student learning. His research integrates theoretical mathematics with practical applications, addressing real-world challenges in data security and computational modeling. Through independent studies and collaborative projects, he seeks to advance the understanding of mathematical frameworks in digital security. His contributions to applied mathematics continue to shape the academic discourse on cryptographic systems, making a lasting impact on both research and education in mathematics.

Publication Top Notes

  • Linear manipulator: Motion control of an n-link robotic arm mounted on a mobile slider – 📖 Heliyon 9 (1), Cited by: 17, Year: 2023
  • Switch controllers of an n-link revolute manipulator with a prismatic end-effector for landmark navigation – 🤖 PeerJ Computer Science 8, e885, Cited by: 16, Year: 2022
  • Navigation of an n-link revolute robotic arm via hierarchal landmarks – 🗺️ NILES Conference, Cited by: 10, Year: 2021
  • Lyapunov-based controllers of an n-link prismatic robot arm – 🏗️ IEEE Asia-Pacific Conference, Cited by: 9, Year: 2021
  • A car-like mobile manipulator with an n-link prismatic arm – 🚗 IEEE Asia-Pacific Conference, Cited by: 9, Year: 2021
  • Embedded FPGA-based motion planning and control of a dual-arm car-like robot – 🔧 IEEE SPEC Conference, Cited by: 8, Year: 2022
  • LbCS navigation controllers of twining Lagrangian swarm individuals – 🐝 NILES Conference, Cited by: 8, Year: 2021
  • Digital signature scheme over lattices – 🔐 IEEE Circuits Conference, Cited by: 7, Year: 2021
  • Acceleration Feedback Controller Processor Design of a Segway – 🛴 IEEE SPEC Conference, Cited by: 5, Year: 2022
  • Vertically Sliding Revolute Robotic Arm intended for automated Pick-and-Place Industrial applications – 🏭 IEEE Asia-Pacific Conference, Cited by: 3, Year: 2022

Gang Li | Mechanical Engineering | Best Researcher Award

Assoc. Prof. Dr. Gang Li | Mechanical Engineering | Best Researcher Award

Associate professor, Northeast Electric Power University, China

🔬 Assoc. Prof. Dr. Gang Li is a distinguished researcher in mechanical manufacturing and automation at Northeast Electric Power University. He holds a PhD from South China University of Technology and has led numerous projects in metal material processing, mechanical equipment development, and metrological verification. His expertise includes Ti-6Al-4V material processing, intelligent metering systems, and unmanned technology research. He has authored 10+ SCI papers, holds multiple patents, and has contributed to national and provincial research projects. Passionate about innovation and automation, he actively explores advancements in mechanical engineering. ✨🔧📡

 

Publication Profile

Scopus

🎓 Educational Background

Assoc. Prof. Dr. Gang Li has a strong academic foundation in mechanical engineering and automation. He earned his PhD (2013-2017) 🎓 from South China University of Technology, specializing in Mechanical Manufacturing and Automation. Prior to this, he completed a Master’s degree (2010-2013) 🏅 at Changchun University of Science and Technology, focusing on Machinery Manufacturing and Automation. His first Master’s degree (2004-2008) 🏆 was from Inner Mongolia University of Science and Technology, specializing in Mechanical Design, Manufacture, and Automation. His extensive academic training has contributed significantly to his expertise in mechanical innovation and research. 🔧📡

🔬 Project Experience

Assoc. Prof. Dr. Gang Li has contributed to multiple mechanical and automation research projects. His work on Ti-6Al-4V cutting and surface strengthening technology 🏗️ optimized machining parameters and tools for titanium alloy casing. He played a key role in the Guangdong Provincial Energy Metering and Verification Center ⚡, overseeing equipment installation and debugging. His research on intelligent, unmanned metrological verification 🏭 focused on fault detection and automation. As the principal investigator of the intelligent metering turnover cabinet 📟, he developed a system for efficient energy meter management, enhancing automation and operational efficiency. 🔧🚀

🔬 Research Focus

Assoc. Prof. Dr. Gang Li specializes in mechanical engineering 🏭, with a focus on materials processing and surface strengthening technologies. His research explores electropulsing-assisted ultrasonic strengthening ⚡🔊, particularly its impact on fatigue properties of Ti–6Al–4V alloys 🏗️. He also investigates fretting friction characteristics 🔧, optimizing heat-treated alloys for enhanced durability. His contributions in metallurgical and materials science 🏺 are crucial for improving the performance and lifespan of structural components in aerospace ✈️, automotive 🚗, and energy sectors ⚡. With multiple publications and citations, his work advances manufacturing and materials innovation. 🚀

Publication Top Notes

Effect of Electropulsing-Assisted Ultrasonic Strengthening on Fatigue Properties of HIP Ti–6Al–4V Alloy

Study on surface fretting friction properties of heat-treated HIP Ti-6Al-4 V alloy after heating-assisted ultrasonic surface strengthening

Giuseppe Silano | Robotics | Best Researcher Award

Dr. Giuseppe Silano | Robotics | Best Researcher Award

Dr. Giuseppe Silano, University of Washington, United States

Dr. Giuseppe Silano, a robotics and control expert, earned his Ph.D. in Information Technologies for Engineering from the University of Sannio, Italy, with a focus on path planning, software-in-the-loop, and unmanned aerial vehicles (UAVs). He collaborated internationally as a visiting Ph.D. student at CNRS, France, and is currently a Tenure Researcher at RSE S.p.A., Milan, Italy, and an Associate Researcher at Czech Technical University. Dr. Silano’s work spans motion planning, human-robot collaboration, and multi-robot systems. An open-source contributor, he develops cutting-edge robotics solutions and publishes widely. He is also a licensed drone pilot and an active IEEE member. ✈️📡📘

 

Publication Profile

Google Scholar

Education and Academic Journey 🎓🤖

Dr. Giuseppe Silano has a distinguished academic background in engineering and robotics. He earned his Ph.D. in Information Technologies for Engineering from the University of Sannio, Italy, as a Doctor Europaeus, focusing on robotics, control, path planning, and software-in-the-loop, under the guidance of Prof. Dr. Luigi Iannelli. He enhanced his expertise as a visiting Ph.D. student at CNRS, France, researching 6DoF robots with onboard sensors, supervised by Prof. Dr. Antonio Franchi. Dr. Silano also holds an M.Sc. in Electronic Engineering (2016) and a B.Sc. in Computer Engineering (2012) from the University of Sannio, specializing in robotics and control systems. 🛠️📡

 

Professional Affiliation 🌐🤖

Dr. Giuseppe Silano has been an active member of the IEEE (Institute of Electrical and Electronics Engineers) since December 2016. Starting as a Student Member (ST’17) and advancing to Member (M’21), he is associated with the IEEE Control Systems Society (CSS) and the IEEE Robotics and Automation Society (RAS). His involvement in these professional bodies underscores his commitment to advancing research and collaboration in robotics, automation, and control systems. Dr. Silano’s affiliation with IEEE highlights his dedication to staying at the forefront of technological innovation and contributing to the global engineering community. 📡📘

 

Professional Experience 💼👨‍💻

Dr. Giuseppe Silano has amassed a decade of experience across various technical roles. From 2014 to 2024, he worked as a Technical Writer for leading Italian platforms, including Win Magazine and EOS Book. In 2016, as a Junior Software Engineer at Software Engine S.r.l., he specialized in front-end web development, database management, and debugging, completing key projects like a document management system for Mirabella Eclano, Italy. Earlier, in 2012, as a Control System Integrator at Mosaico Monitoraggio Integrato S.r.l., he designed industrial automation systems, including soda autoclave storage and turbine blade leaching processes, adhering to safety requirements. 📜⚙️

 

Research Activities 🤖📚

Dr. Giuseppe Silano’s research spans robotics, control, and UAV systems. He developed motion-planning algorithms for multi-robot systems in civilian infrastructure inspections, emphasizing obstacle avoidance and UAV constraints within the Aerial-Core project. His work on communication-aware robotics enhances robust wireless connectivity for UAVs in challenging environments. Dr. Silano advanced Model Predictive Control (MPC) strategies for collision avoidance and target tracking, and decentralized swarm navigation in UAVs. His studies in autonomous vehicles include MPC-based control for small-scale racing cars. Additionally, he explored human-aerial robot interaction to assist humans in critical tasks while prioritizing safety and ergonomics, contributing extensively to UAV software and simulators. 🚁💻

 

Teaching and Mentorship Experience 🎓📚

Dr. Giuseppe Silano has an extensive teaching background, including leading PhD courses such as “Fundamentals for Robot Programming with ROS” (University of Sannio, 2024). He served as a Teaching Assistant for courses like “Discrete Systems,” “Automatic Control,” and “Advanced Controls” in Computer and Electronics Engineering programs. As a Subject Matter Expert, he contributed to topics like “Sistemi Discreti” and “Controlli Automatici.” Dr. Silano co-supervised innovative research projects under MIT programs and guided numerous Bachelor’s and Master’s theses on UAVs, control systems, and robotics. His mentorship showcases his dedication to fostering technical and academic excellence. ✈️🤖

 

Awards and Achievements 🏆🤖

Dr. Giuseppe Silano has been recognized in prestigious international robotics competitions. He was part of the UNISANNIO team that won the “MathWorks Minidrone Competition” at IFAC 2020 in Berlin, Germany. Additionally, he contributed to the LAAS team, finalists in the “Mohamed Bin Zayed International Robotics Challenge (MBZIRC)” held in Abu Dhabi, UAE. Dr. Silano also showcased his expertise as a finalist in the “Aerial Robotics Control and Perception Challenge” during the 26th Mediterranean Conference on Control and Automation in Zagreb, Croatia. His accolades highlight his excellence in robotics and control systems. 🌍✈️

 

Research Focus

Dr. Giuseppe Silano specializes in robotics, with a focus on unmanned aerial vehicles (UAVs) for precision agriculture, power line inspections, and multi-robot systems. His work integrates advanced path-planning algorithms, software-in-the-loop platforms, and signal temporal logic for mission planning. Key areas include collision avoidance, perception-aware navigation, and real-world deployment of aerial robotics. Dr. Silano’s contributions extend to drone swarm coordination, non-linear model predictive control, and autonomous target tracking. His research advances UAV applications in environmental monitoring, communication-aware robotics, and physical security optimization, positioning him at the forefront of aerial robotics innovation. 🌱⚡🚁

 

Publication Top Notes

  • 🌾 “A review on the use of drones for precision agriculture” – Cited by: 212Year: 2019
  • 🚁 “A survey on the application of path-planning algorithms for multi-rotor UAVs in precision agriculture” – Cited by: 66Year: 2022
  • ⚡ “Power line inspection tasks with multi-aerial robot systems via signal temporal logic specifications” – Cited by: 60Year: 2021
  • 🛠️ “CrazyS: a software-in-the-loop platform for the Crazyflie 2.0 nano-quadcopter” – Cited by: 50Year: 2018
  • 🚀 “MRS Modular UAV Hardware Platforms for Supporting Research in Real-World Outdoor and Indoor Environments” – Cited by: 42Year: 2022
  • ✈️ “Software-in-the-loop simulation for improving flight control system design: a quadrotor case study” – Cited by: 37Year: 2019
  • 🤖 “MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems” – Cited by: 33Year: 2023
  • 🔧 “CrazyS: A Software-in-the-Loop Simulation Platform for the Crazyflie 2.0 Nano-Quadcopter” – Cited by: 29Year: 2019
  • 🔌 “A Multi-Layer Software Architecture for Aerial Cognitive Multi-Robot Systems in Power Line Inspection Tasks” – Cited by: 18Year: 2021
  • 📋 “Mission Planning and Execution in Heterogeneous Teams of Aerial Robots supporting Power Line Inspection Operations” – Cited by: 17Year: 2022

 

 

 

 

 

 

 

 

Shijie Wang | Robotics | Best Researcher Award

Dr. Shijie Wang | Robotics | Best Researcher Award

Dr. Shijie Wang, Shenzhen Institutes of Advanced Technology, Chinese Academy of Science, China

Dr. Shijie Wang is a PhD Candidate at Hebei University of Technology and a joint researcher at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. With a background in engineering (B.Eng, M.Eng), Dr. Wang’s research focuses on robotics and mechanical systems. He has authored impactful publications in Applied Mathematical Modelling and contributed to several patents on construction robotics and high-load manipulators. Dr. Wang has won multiple awards, including the China “Challenge Cup” and 3D Digital Innovative Design Competition. His work on construction robotics has earned substantial funding, highlighting his innovative contributions. 🤖🔧📚📑

 

Publication Profile

Scopus

Orcid

Academic & Professional Qualifications

Dr. Shijie Wang is a PhD candidate at Hebei University of Technology and a joint training researcher at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences. He holds a B.Eng and M.Eng from Hebei University of Technology. His academic journey has been complemented by professional experience, including his role as a research assistant at the Shenzhen Institutes and as a chief process engineer at Beijing Jingdiao Group. Dr. Wang has also worked as an R&D engineer at Shinetek Instruments Research Institute. His diverse expertise contributes significantly to advancements in engineering and robotics. 🎓🔬🤖

 

Representative Works and Awards

Dr. Shijie Wang has made significant contributions to the fields of robotics and mechanical engineering. His recent publication, Unified Recursive Kinematics and Statics Modeling (2024) in Applied Mathematical Modelling (IF 4.4), presents innovative work on high-load manipulators. Other notable publications include work on flapping-wing micro air vehicles (2023) and kinematic analysis of parallel manipulators (2022). He holds several patents, including inventions in construction robots and hydraulic manipulators. Dr. Wang has received prestigious awards, including the second prize in the 2015 China “Challenge Cup” and first prize in the 2014 3D Digital Innovative Design Competition. 🏆📚🤖

 

Research Focus

Dr. Shijie Wang’s research focuses on robotics, automation, and advanced manufacturing technologies. He explores kinematics and statics modeling of manipulators, with applications in redundantly actuated systems and functionally graded materials (FGMs). His work includes the optimization of robotic systems for construction and manufacturing, path planning strategies for 3D printing, and the modeling of dynamic mixing processes for materials fabrication. Dr. Wang is also deeply involved in machine learning applications in design and fabrication. His research has significant implications in construction robotics, material science, and robotic systems design. 🤖🔧📐📊

 

Publication Top Notes

  • Unified recursive kinematics and statics modeling of a redundantly actuated series-parallel manipulator with high load/mass ratio (2024) 🛠️
  • Process parameter modeling for the fabrication of functionally graded materials via direct ink writing (2024) 🖨️
  • Optimization of Pin Type Single Screw Mixer for Fabrication of Functionally Graded Materials (2024) 🔧
  • Numerical Simulation of a Dynamic Mixing Process of Ceramic-Grade Materials for Extruded 3D Printing (2023) 🏗️
  • Path planning strategy of functionally graded materials printed by material extrusion process (2023) 🌐
  • A Review: Applications of Machine Learning in Design-Fabrication of Functionally Graded Materials (2023) 🤖
  • Attitude Control of Flapping-Wing Micro Air Vehicles Based on Hyperbolic Tangent Function Sliding Mode Control (2023) ✈️
  • Digital prediction method for delay information for preparing FGMs parts by direct write forming (2023) ⏱️
  • Functionally graded materials model is constructed by B-spline surface and point gradient source (2022) 🧱
  • Kinematic Performance Analysis of Spatial 2-DOF Redundantly Actuated Parallel Manipulator (2022) 🔄

Moh Shahid Khan | Robotics | Best Researcher Award

Mr. Moh Shahid Khan | Robotics | Best Researcher Award

Mr. Moh Shahid Khan, Maulana Azad National Institute of Technology (MANIT), Bhopal, India

Mr. Moh Shahid Khan appears to be a strong candidate for the Best Researcher Award. Here are some key reasons supporting his suitability:

Publication profile

Research Focus and Contributions:

Mr. Khan’s PhD research in robotics, specifically on gait analysis and the design of adaptive PID controllers for biped robots on complex terrains, is both innovative and impactful. His work involves the use of advanced techniques like neural networks and fuzzy logic, which demonstrates his expertise in robotics and control systems.

Publications:

He has authored several papers published in reputable SCI journals, including articles in Robotica and the Journal of Field Robotics. These publications highlight his research’s quality and his contribution to advancing the field of robotics.

Interdisciplinary Collaboration:

 His collaborative work with colleagues from computer science and other fields indicates his ability to work across disciplines, which is valuable for addressing complex research problems.

Technological Impact:

 His involvement in the design, 3D modeling, and printing of biped robots, along with his advisory role in acquiring new technological equipment for research labs, underscores his hands-on approach and technological leadership.

Mentorship and Teaching:

With over four years of teaching experience, Mr. Khan has demonstrated a commitment to education and mentorship, supervising student projects and helping colleagues with their research. This indicates his contribution to knowledge dissemination and academic growth.

Recognition and Awards:

 His consistent recognition for excellence in teaching, social media coordination, and research further solidifies his credentials as a well-rounded academic and researcher.

Publication Top Notes

  • 📚 A review on gait generation of the biped robot on various terrains – MS Khan, RK Mandava, Robotica 41 (6), 1888-1930, Cited by: 13, 2023
  • 🌍 Poverty rises: Monga drives poor to city – M Khan, Star Weekend Magazine, Dhaka: The Daily Star 3, Cited by: 5, 2004
  • 🔥 THERMAL ANALYSIS OF CORRUGATED PLATE HEAT EXCHANGER BY USING ANSYS SOFTWARE THROUGH FEA METHOD – MS Khan, A Singhai, 2019, Cited by: 1, 2019
  • 🚶 Design of dynamically balanced gait for the biped robot while crossing the obstacle – MS Khan, RK Mandava, Proceedings of the Institution of Mechanical Engineers, Part C: Journal of …, 2024
  • 🔄 A review on gait generation of the biped robot on various terrains–CORRIGENDUM – MS Khan, RK Mandava, Robotica 41 (10), 3233-3233,  2023
  • 🚧 Design of Dynamically Balanced Gait for the Biped Robot While Crossing the Ditch – MS Khan, RK Mandava, Acta Polytechnica Hungarica 20 (7), 2023
  • 📈 Estimation of Dynamic Balancing Margin of the 10-DOF Biped Robot by Using Polynomial Trajectories – MS Khan, RK Mandava, International Conference on Machine Learning, Image Processing, Network …, , 2022
  • 🛠️ A Review on Sliding Mode Controller in Real-Time Applications – M Tomar, MS Khan, RK Mandava, DG Babu, 2022 IEEE International Students’ Conference on Electrical, Electronics and …, 2022
  • 🌡️ A REVIEW ON IMPROVEMENT OF HEAT TRANSFER RATE BY PASSIVE METHODS – MS Khan, A Singhai, 2019
  • 📄 2015 NS-AUA Abstracts – A Hussein, A Khan, S Raza, T Fiorica, P Dsagupta, M Khan, K Ahmed, … Canadian Urological Association Journal= Journal de L’association des …,, 2015


Conclusion

Mr. Khan’s blend of technical expertise, research contributions, collaboration, and teaching makes him a deserving candidate for the Best Researcher Award.

Inam Ullah | Robotics Award | Young Scientist Award

Prof Dr. Inam Ullah | Robotics Award | Young Scientist Award

Prof Dr. Inam Ullah, Shenzhen University, China

Based on the details provided, the candidate seems well-suited for the Research for Young Scientist Award. Here’s an evaluation of their profile, formatted with headings and conclusions for each section:

Publication profile

Professional Experience

The candidate has a robust professional background in research and academia. Their current role as an Assistant Professor at Gachon University, combined with recent postdoctoral research and consulting experience, showcases a strong blend of teaching, research, and industry application. This varied experience aligns well with the criteria for a Young Scientist Award, highlighting their capability in contributing to cutting-edge research and practical solutions.

Education

With a PhD in Information & Communication Engineering from Hohai University, the candidate has demonstrated excellence in their academic pursuits. Their research on mobile robot localization and underwater localization algorithms reflects a high level of expertise in advanced technological areas relevant to the award.

Research Interests

The candidate’s diverse research interests, including IoT, robotics, and AI, align with current trends in science and technology. Their focus on cutting-edge areas such as autonomous vehicles, network security, and machine learning showcases their commitment to advancing knowledge in these fields.

Citations and Impact

With an impressive cumulative impact factor of 268.20 and substantial Google Scholar citations, the candidate’s research output has significantly influenced their field. Their h-index of 28 and i10-index of 51 further attest to the high quality and impact of their work.

Awards, Funding, and Honors

The candidate has received multiple prestigious awards, including the Top-10 Outstanding Students Award and the Jiangsu Province Distinguish International Students Award. These recognitions, along with their consistent academic performance, highlight their exceptional achievements.

Other Experience and Projects

The candidate’s experience in supervising projects, teaching, and developing instructional methodologies showcases their commitment to education and research. Their involvement in student supervision and research activities further highlights their capability to contribute to both academic and practical advancements.

Publication Top Notes

  • A Review of Underwater Localization Techniques, Algorithms, and Challenges – S Xin, U Inam, L Xiaofeng, C Dongmin, Journal of Sensors 2020, 24 – Cited by 162 📘 (2020)
  • A Localization Based on Unscented Kalman Filter and Particle Filter Localization Algorithms – I Ullah, Y Shen, X Su, C Esposito, C Choi, IEEE Access 8, 2233-2246 – Cited by 147 🔍 (2019)
  • Motor Imagery EEG Signals Decoding by Multivariate Empirical Wavelet Transform-Based Framework for Robust Brain–Computer Interfaces – MT Sadiq, X Yu, Z Yuan, F Zeming, AU Rehman, I Ullah, G Li, G Xiao, IEEE Access 7, 171431-171451 – Cited by 145 🧠 (2019)
  • Localization and Detection of Targets in Underwater Wireless Sensor Using Distance and Angle Based Algorithms – I Ullah, J Chen, X Su, C Esposito, C Choi, IEEE Access 7, 45693-45704 – Cited by 132 🌊 (2019)
  • Deep Learning in Cancer Diagnosis and Prognosis Prediction: A Minireview on Challenges, Recent Trends, and Future Directions – T Ahsan B, M Y-K, K M K. A, M F, J AR, U Inam, K Rahim, Computational and Mathematical Methods in Medicine 2021, 28 – Cited by 99 📈 (2021)
  • Student-Performulator: Student Academic Performance Using Hybrid Deep Neural Network – BK Yousafzai, SA Khan, T Rahman, I Khan, I Ullah, A Ur Rehman, M Baz, Sustainability 13 (17), 9775 – Cited by 86 🎓 (2021)
  • A Multi-Layer Cluster Based Energy Efficient Routing Scheme for UWSNs – W Khan, H Wang, MS Anwar, M Ayaz, S Ahmad, I Ullah, IEEE Access 7, 77398-77410 – Cited by 79 🔋 (2019)
  • Analysis of Challenges and Solutions of IoT in Smart Grids Using AI and Machine Learning Techniques: A Review – M Tehseen, I Hafiz Muhammad, H Inayatul, U Inam, A Madiha, Electronics 12 (1), 26 – Cited by 74 💡 (2023)
  • Efficient and Accurate Target Localization in Underwater Environment – I Ullah, Y Liu, X Su, P Kim, IEEE Access 7, 101415-101426 – Cited by 72 🛰️ (2019)
  • Analysis of Cyber Security Attacks and Its Solutions for the Smart Grid Using Machine Learning and Blockchain Methods – M Tehseen, I Hafiz Muhammad, K Sunawar, H Inayatul, U Inam, Future Internet 15 (83), 1-38 – Cited by 67 🔐 (2023)

Conclusion

Overall, the candidate’s comprehensive experience, strong educational background, significant research contributions, and recognition in their field make them a highly suitable candidate for the Research for Young Scientist Award.

 

 

 

 

 

 

 

Engineering

Introduction of Engineering

 

Engineering research is the driving force behind innovation, shaping the modern world with its focus on design, problem-solving, and technological advancement. This dynamic field applies scientific principles to create practical solutions, whether it’s building resilient infrastructure, developing cutting-edge technologies, or addressing environmental challenges. Engineers work across various domains, striving to make our lives safer, more efficient, and more connected.

Civil Engineering:

Civil engineers design and construct essential infrastructure like bridges, buildings, and transportation networks. Their research focuses on sustainable materials, earthquake-resistant structures, and smart cities.

Mechanical Engineering:

Mechanical engineers work on the design and maintenance of mechanical systems. Research areas include robotics, thermodynamics, and advanced manufacturing, leading to innovations in automation and sustainable energy.

Electrical Engineering:

Electrical engineers drive progress in electronics, telecommunications, and power systems. Their research covers renewable energy solutions, wireless communication, and integrated circuits.

Environmental Engineering:

Environmental engineers tackle challenges related to pollution, water quality, and sustainability. Their research seeks to develop eco-friendly technologies, wastewater treatment methods, and air quality improvement.

Biomedical Engineering:

Biomedical engineers merge principles of engineering with biology and medicine. Their research spans medical device design, tissue engineering, and healthcare technologies, contributing to improved diagnostics and patient care.

 

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