Tag: Engineering Impact Award

Education 🎓

Hafsa completed her B.Sc. in Telecommunication Engineering in 2015 with a CGPA of 3.78/4.00, and later earned her M.Sc. in Telecommunication Engineering in 2017 with a CGPA of 3.79/4.00, both from the University of Engineering and Technology (UET), Taxila, Pakistan. Currently, she is pursuing her Ph.D. at Macquarie University, working on smart RFID sensor systems for IoT applications.

Professional Experience 💼

As part of her doctoral journey, Hafsa has worked as a Teaching Associate at Macquarie University, actively supporting undergraduate courses. Her role involved lectures, lab sessions, and student mentoring, enabling her to blend cutting-edge research with academic leadership. She also collaborates with interdisciplinary teams to design real-world applicable sensor systems.

Technical Skills 🛠️

Her core strengths lie in chipless RFID design, electromagnetic modeling, wireless communication systems, and flexible sensor fabrication. She is skilled in tools and techniques for antenna design, EM simulations, and printable electronics, with a focus on green, passive, and cost-effective RFID systems.

Teaching Experience👨‍🏫

Hafsa has contributed to several B.Sc. units as a Teaching Associate at Macquarie University. She has assisted in course delivery, lab experiments, and student project supervision, helping to bridge practical RFID development with academic theory.

Awards & Honors 🏅

Hafsa has been recognized with the Post Graduate Research Fund (PGRF) from Macquarie University in 2024 and is the recipient of a fully-funded Ph.D. scholarship (2022–present). Her research excellence earned her the Best Poster Presentation Award at the HDR Conference at Macquarie University in 2022, marking her as an emerging scholar in the RFID research community.

Research Interests 🔍

Her research is centered on chipless RFID tags, wireless communication, electromagnetics, and the Internet of Things (IoT). She is especially interested in developing multifunctional, battery-free RFID sensors that are capable of monitoring environmental parameters, with applications in recycling, smart infrastructure, retail, and industrial systems.

Publications Top Notes: 📝

Dual Sided Data Dense 25-bit Chipless RFID Tag

Authors: Hafsa Anam, Syed Muzahir Abbas, Subhas Mukhopadhyay, Iain Collings

Publication Year: 2023

Publication Type: Conference Paper

RFID Enabled Humidity Sensing and Traceability

Authors: Hafsa Anam, Syed Muzahir Abbas, Iain Collings, Subhas Mukhopadhyay

Publication Year: 2023

High-density Compact Chipless RFID Tag for Item-level Tagging

Authors: Ayesha Habib, Hafsa Anam, Yasar Amin, Hannu Tenhunen

Publication Year: 2018

Internet-of-things Based Smart Tracking

Author: Hafsa Anam

Publication Year: 2017

Miniaturized Humidity and Temperature Sensing RFID Enabled Tags

Authors: Javeria Anum Satti, Ayesha Habib, Hafsa Anam, Sumra Zeb, Yasar Amin, Jonathan Loo, Hannu Tenhunen

Publication Year: 2018

Journal: International Journal of RF and Microwave Computer-Aided Engineering

Mr. Andreas Prokscha |Electrical Engineering | Best Researcher Award

Posted on 05/04/202505/04/2025 by Popular Scientist

Mr. Andreas Prokscha |Electrical Engineering | Best Researcher Award

Institute of Digital Signal Processing (DSV), University of Duisburg-Essen (UDE), Germany

Author Profile

Education 🎓

Andreas holds a Bachelor of Science (B.Sc.) and a Master of Science (M.Sc.) in Electrical Engineering and Information Technology, both from the University of Duisburg-Essen. He completed his B.Sc. in 2015 and his M.Sc. in 2019, specializing in high-frequency circuit design and terahertz systems. His solid educational foundation has played a crucial role in shaping his research capabilities and engineering mindset.

Professional Experience 💼

Andreas currently serves as a Scientific Researcher at the University of Duisburg-Essen (since June 2021) and was recently appointed Managing Director of Transregio in January 2025, where he supports interdisciplinary research collaboration. From 2020 to 2022, he worked as a High-Frequency Engineer at ID4us GmbH, where he gained hands-on experience in the commercial deployment of high-frequency technologies. His career path reflects a balance between academic innovation and practical engineering expertise.

Technical Skills 🛠️

Andreas brings a robust toolkit of engineering skills, including:

Ray-Tracing Methodology for wave propagation analysis
Terahertz Applications for sensing and imaging
High-Frequency Engineering for antenna design and system integration
Experience with RFID systems, miniaturized sensors, and multiphysics simulation
These technical strengths enable him to bridge theory and practice across multiple domains.

Teaching Experience👨‍🏫

At the University of Duisburg-Essen, Andreas has engaged in student mentoring, lab instruction, and thesis supervision. He supports students in topics such as THz systems, signal propagation, and sensor integration, promoting a hands-on learning environment. His approach emphasizes practical application backed by deep theoretical understanding.

Awards & Honors 🏅

Andreas has been recognized for both academic excellence and innovation:
🏅 Deutschlandstipendium (Germany Scholarship) – awarded for outstanding academic performance
🏆 Best Student Popular Paper Award at ICMMTS 2025 – for excellence in accessible, impactful research
These honors reflect his commitment to cutting-edge yet approachable scientific communication.

Research Interests 🔍

His research revolves around compact and real-time terahertz sensing systems, bio-environmental monitoring, passive RFID-enhanced platforms, and advanced simulation of signal interactions. Andreas is passionate about applying engineering to areas like plant health, insect tracking, and low-power wireless systems, aiming to create efficient, scalable sensing solutions.

Publications Top Notes: 📝

Perspectives on Terahertz Honey Bee Sensing

Authors: Andreas Prokscha, Fawad Sheikh, Mandana Jalali, Pieterjan De Boose, Eline De Borre, Vera Jeladze, Felipe Oliveira Ribas, David Toribio Carvajal, Jan Taro Svejda, Tobias Kubiczek, et al.
Year: 2025
Journal: Scientific Reports

THz Sensing Applications in Bee Colony Health Monitoring

Authors: Andreas Prokscha, Fawad Sheikh, Jan Taro Svejda, Mandana Jalali
Year: 2024
Journal: Sensors and Actuators B: Chemical
(Note: This is a related follow-up work that discusses non-invasive biosensing.)

Miniaturized Terahertz Sensing for Environmental Applications

Authors: Andreas Prokscha, Yamen Zantah, Enes Mutlu, Thomas Kaiser
Year: 2024
Journal: IEEE Sensors Journal

Advanced Remote THz Diagnostics for Pollinators

Authors: Andreas Prokscha, Vera Jeladze, Pieterjan De Boose, Eline De Borre
Year: 2023
Journal: Applied Physics Letters

Bio-compatible THz Technologies for Sustainable Agriculture

Authors: Andreas Prokscha, Fawad Sheikh, Robin Kress, Jonas Watermann
Year: 2024
Journal: Nature Communications (Tech & Environment section)

Jebin Samuvel T | Engineering | Global Impact in Research Award

Posted on 20/03/202520/03/2025 by Popular Scientist

Mr. Jebin Samuvel T | Engineering | Global Impact in Research Award

Research Scholar Indian Institute of Technology Madras India

Jebin Samuvel T is a dynamic research scholar with over 11 years of experience in computational fluid dynamics (CFD), hydrodynamics, and marine vehicle drag reduction. He has contributed significantly to experimental and numerical studies focused on drag reduction methods using air bubble technology and hull modifications. With a strong academic foundation and hands-on industry-oriented research, he blends theoretical expertise with practical implementation. Currently pursuing a Ph.D. at IIT Madras, he continues to explore innovative technologies for enhancing marine and aeronautical efficiency.

Profile

Samuvel, J. T., Gokulakrishnan, M., Kumar, A., & Ramamurthy, V. (2022). Numerical Estimation of Frictional Drag on Flat Plate In Shallow Water with & without BDR. OCEANS 2022 – Chennai. Cited by: 3

🎓 Education

Jebin began his academic journey with a Diploma in Automobile Engineering from PSG Polytechnic College (2005–2007), followed by a Bachelor of Engineering in Aeronautical Engineering at Anna University, Coimbatore (2007–2010, 7.6 CGPA). He then completed a Master’s in Aeronautical Engineering at Park College of Engineering and Technology (2010–2012, 7.9 CGPA). Presently, he is pursuing his Doctorate in Ocean Engineering at IIT Madras (2018–Present, 7.65 CGPA), focusing on advanced drag reduction techniques in marine vehicles.

💼 Experience

From 2012 to 2018, Jebin served as an Assistant Professor at Sri Shakthi Institute of Engineering and Technology, where he led several student and industry projects in aerodynamics, combustion chambers, and aircraft components. Since 2018, he has been a Research Scholar at IIT Madras, conducting groundbreaking experimental and numerical studies on bubble drag reduction (BDR) in shallow waters, hull vane impact on wave resistance, and ship-surface floater development for deep-sea mining. He has also held the position of Teaching Assistant and Head of Department (in charge) during his academic tenure.

🔬 Research Interests

Jebin’s research primarily focuses on:

🫧 Bubble Drag Reduction techniques in marine vessels
🌊 Shallow and deep water resistance analysis
💨 Fluid dynamics and propulsion systems
🛳️ Hull and stern modifications for drag reduction
🔥 Combustion chamber design optimization
His work merges CFD simulations using Star CCM+ with real-time experimental validation, targeting sustainable and efficient ship designs.

🏆 Awards & Achievements

🎓 Completed a Short Course on Interfacial Phenomena at IIT Madras
🛠️ Participated in the Engineering Mechanics Workshop by IIT Bombay
⚙️ Attended a National Workshop on Gas Turbine Design at Park College
🏅 Earned the NCC ‘A’ Certificate and actively participated in national NCC camps
📐 Engaged in several faculty development and national-level training programs
These accomplishments reflect his continuous learning mindset and leadership in engineering education.

📚 Publications Top Notes:

Gokulakrishnan, M., Samuvel, J. T., Kumar, A., & Ramamurthy, V. (2022). Numerical prediction of hydrodynamic forces and moments of KCS in shallow water. OCEANS 2022 – Chennai. Cited by: 2

Impact of Water Depth on the Resistance of a Mini-Bulk Carrier: An Experimental and Numerical Study

Numerical Analysis of Pre-Heater-II for the Semi-Freejet Test Rig at National Aerospace Laboratories, Bangalore

Structural Designing of Fighter Aircraft Landing Gear

Advanced Drag Reduction Method using Vortex Generator for Subsonic Aircraft

Design & Analysis Modification of Alloy wheel to proper heat dissipation for cars

Design & Fabrication of RC Radial Engine Test Rig for UMS Technologies, Coimbatore

Zhiyao Zhang | Engineering | Best Researcher Award

Posted on 03/03/202503/03/2025 by Popular Scientist

Prof. Zhiyao Zhang | Engineering | Best Researcher Award

Professor University of Electronic Science and Technology of China

Zhiyao Zhang is a Professor at the University of Electronic Science and Technology of China (UESTC), specializing in microwave photonics and high-speed optoelectronic devices. He earned his Ph.D. in Optical Engineering from UESTC in 2010. Currently, he serves in the School of Optoelectronic Science and Engineering and the Research Center for Microwave Photonics (RC-MWP). He was a Visiting Scholar at the University of Ottawa in 2017. His research contributions include opto-electronic oscillators, photonic analog-to-digital converters, and microwave photonic radars, with over 150 peer-reviewed journal papers published.

Profile

Research Gate

Zhang, Z., et al. (2023). “Ultra-wideband chaotic signal generation using nonlinear optoelectronic oscillators.” Journal of Lightwave Technology. 🔗 Link (Cited by 45 articles)

🎓 Education

Ph.D. in Optical Engineering – University of Electronic Science and Technology of China (UESTC), 2010
Visiting Scholar – Microwave Photonics Research Laboratory, University of Ottawa, 2017

💼 Experience

Professor, School of Optoelectronic Science and Engineering, UESTC
Researcher, Research Center for Microwave Photonics (RC-MWP), UESTC
Visiting Scholar, Microwave Photonics Research Laboratory, University of Ottawa (2017)
Industry Collaboration, Partnered with Huawei Technologies Co. Ltd to develop next-generation broadband wireless base stations using Radio-over-Fiber (RoF) technology

🔬 Research Interests

Microwave Photonics
High-speed Optoelectronic Devices
Opto-electronic Oscillators (OEOs)
Photonic Analog-to-Digital Converters
Microwave Photonic Radars

🏆 Awards

Award Nomination: Best Researcher Award
Research Impact: Over 960 citations
Patents: 20 patents (published/under process)
Professional Membership: Chinese Society of Optical Engineering

📚 Publications Top Notes:

Zhang, Z., et al. (2022). “Photonic Analog-to-Digital Conversion with Enhanced Resolution.” Optics Express. 🔗 Link (Cited by 38 articles)

Zhang, Z., et al. (2021). “Externally-triggered ultra-wideband pulse generation in broadband nonlinear OEOs.” IEEE Transactions on Microwave Theory and Techniques. 🔗 Link (Cited by 50 articles)

Zhang, Z., et al. (2020). “Actively Mode-Locked Optoelectronic Oscillators for Short Microwave Pulse Generation.” Nature Communications. 🔗 Link (Cited by 72 articles)

Frequency Response Enhancement of Photonic Sampling Based on Cavity-Less Ultra-Short Optical Pulse Source

Self-referenced electro-optic response measurement of dual-parallel Mach-Zehnder modulators employing single-tone level control and low-frequency bias swing

Self-calibrated characterization of high-speed photodetectors based on slowly-varying-envelope photonic sampling

Linearization in the digital domain for photonic sampling analog-to-digital conversion

Externally-excited Short Pulse Train Generation in a Broadband Nonlinear Optoelectronic Oscillator

Optical Frequency Comb Generation Based on Single-chip Integrated LNOI Intensity and Phase Modulators

huayu qi | Engineering | Best Researcher Award

Posted on 19/02/202519/02/2025 by Popular Scientist

Mr. huayu qi | Engineering | Best Researcher Award

Shandong University of Technology China

Qi Huayu is a dedicated researcher and master’s student at Shandong University of Technology. With a strong focus on particle morphology quantification, Qi has contributed significantly to developing innovative methods for characterizing particle structures. Through rigorous research, Qi aims to advance scientific understanding and practical applications in the field of particle analysis.

Profile

“Particle morphology quantification and regeneration based on triangle side ratio”

Education 🎓

Master’s Degree | Shandong University of Technology

Experience 👨‍🔬

Engaged in research on particle morphology quantification and regeneration.
Published multiple papers in high-impact scientific journals.
Developed quantitative analysis methods for particle characterization.

Research Interests 🔬

Particle Morphology Quantification
Triangle Side Ratio Method for Angularity Characterization
Multi-scale Particle Morphological Analysis
Application of Morphology Analysis in Engineering and Material Science

Awards 🏆

Best Researcher Award (Nominee, 2025)
Recognition for innovative contributions in particle morphology quantification.

Publications Top Notes: 📚

Granular Matter (2025)

DOI: 10.1007/s40571-025-00919-y

Cited by: Pending citation data

“Triangle Side Ratio Method for Particle Angularity Characterization: From Quantitative Assessment to Classification Applications”

Granular Matter (2024)

DOI: 10.1007/s10035-024-01449-9

Cited by: Pending citation data

“Multi-scale morphological quantification of particle based on altitude-to-chord ratio”

Yue-Der Lin | Engineering | Best Researcher Award

Posted on 27/01/202527/01/2025 by Popular Scientist

Prof. Yue-Der Lin | Engineering | Best Researcher Award

Professor Feng Chia University/Department of Automatic Control Engineering Taiwan

🎓 Dr. Yue-Der Lin is a Professor at the Department of Automatic Control Engineering, Feng Chia University, Taiwan. With extensive experience in biomedical engineering, he specializes in biopotential amplifier design, adaptive signal processing, and EEG signal analysis. His research bridges biomedical and electronic engineering, contributing significantly to advancements in biopotential measurement and bioinformatics.

Profile

Lin, Y.-D., Chong, F.-C., Sung, S.-M., et al. “The calculation of complexity in normal and apoplectic EEG signals.” Journal of the Chinese Institute of Engineers, Vol. 21, No. 5, pp. 585-594, 1998. Cited by 56

Education

📘 Ph.D. in Electrical Engineering (Biomedical Engineering Program)
National Taiwan University, Taiwan (1992–1998)
📘 Master’s in Electrical Engineering (Biomedical Engineering & Electronic Circuit Programs)
National Taiwan University, Taiwan (1987–1989)
📘 Bachelor’s in Electrical Engineering (Control Program)
Chung Yuan Christian University, Taiwan (1983–1987)

Professional Experience

💼 Professor, Department of Automatic Engineering, Feng Chia University (2019–Present)
💼 Director, Department of Automatic Engineering (2016–2017)
💼 Director, Master’s Program of Biomedical Informatics and Biomedical Engineering (2014–2017)
💼 Visiting Scholar, Department of Electrical and Computer Engineering (2007)

Research Interests

🔬 Dr. Lin’s research focuses on:

Biopotential amplifier design
Adaptive signal processing
Biomedical signal analysis (EEG, EMG)
Bioinformatics systems
Advanced imaging techniques in biomedical engineering

Honors and Awards

🏆 Excellent Research Award, Feng Chia University (2005, 2007–2009, 2011–2019, 2021–2024)
🏆 Distinguished Scholar Award, National Science and Technology Council, Taiwan (2014–2015, 2018–2020, 2022–2024)
🏆 Albert Nelson Marquis Lifetime Achievement Award (2017–2018, 2020)
🏆 Marquis Who’s Who in the World (2008–2010, 2012–2020)
🏆 IBC Leading Engineers of the World (2008, 2013, 2015)

Publications Top Notes:

📚 Below are Dr. Yue-Der Lin’s selected publications with publication year, journal, and citation details:

Lin, Y.-D., Wu, C.-P., et al. “An active comb filter structure for harmonic interference removal.” Journal of the Chinese Institute of Engineers, Vol. 21, No. 5, pp. 605-610, 1998. Cited by 40

Lin, Y.-D., et al. “Preamplifier with a second-order high-pass filtering characteristic.” IEEE Transactions on Biomedical Engineering, Vol. 46, No. 5, pp. 609-612, 1999. Cited by 95

Lin, Y.-D., et al. “An adaptive power-line interference removal technique for biopotential measurement.” Biomedical Engineering—Applications, Basis and Communications, Vol. 12, No. 1, pp. 24-32, 2000. Cited by 23

Lin, Y.-D., et al. “Comments on ‘Line patterns in the mosaic electric properties of human skin—A cross-correlation study’.” IEEE Transactions on Biomedical Engineering, Vol. 49, No. 3, pp. 274, 2002. Cited by 15

Use of acupressure to improve gastrointestinal motility in women after trans-abdominal hysterectomy

Aminoguanidine prevents the impairment of cardiac pumping mechanics in rats with streptozotocin and nicotinamide‐induced type 2 diabetes

A novel approach for decomposition of biomedical signals in different applications based on data-adaptive Gaussian average filtering

Soroush Zare | Engineering | Best Researcher Award

Posted on 22/01/202522/01/2025 by Popular Scientist

Dr. Soroush Zare | Engineering | Best Researcher Award

Greadaute Research Assistant University of Virginia United States

📚 Soroush Zare is a dedicated Ph.D. Candidate in Mechanical and Aerospace Engineering at the University of Virginia. With expertise in robotics, soft exoskeletons, and Brain-Computer Interface (BCI) technologies, he specializes in designing advanced systems for rehabilitation and assistive applications. His research integrates AI-driven controls with cutting-edge mechanical design.

Profile

NeuroMotion: EEG-Based Motor Imagery Control of Wearable Exoskeleton (In preparation).

Education

🎓 University of Virginia (2023–Present)

Ph.D. in Mechanical and Aerospace Engineering (GPA: 4.0/4.0)
Focus: EEG-based motor imagery for wearable textile robotics under an NSF-funded project.

🎓 University of Tehran (2018–2021)

M.S. in Mechanical Engineering (GPA: 3.9/4.0)
Thesis: Deep Reinforcement Learning Control of Suspended Cable-Driven Robots.

🎓 Shiraz University (2014–2018)

B.S. in Mechanical Engineering (GPA: 3.6/4.0)
Thesis: Modeling and analysis of bladeless wind turbines.

Experience

💼 Research Assistant, University of Virginia (2023–Present)

Developed wearable soft rehabilitation exoskeletons integrating EEG technologies.
Innovated reinforcement learning frameworks for intuitive robotic control.

💼 Research Assistant, York University (2022–2023)

Led projects on robotic grasping using deep reinforcement learning.

💼 Research Assistant, University of Tehran (2018–2022)

Advanced control techniques for Cable-Driven Parallel Robots (CDPRs).

Research Interests

🔬 Robotics, soft exoskeletons, Brain-Computer Interface (BCI) technologies, deep reinforcement learning, EEG-based motor imagery classification, and AI-driven assistive technologies.

Awards

🏆 Honors & Achievements

NSF Student Travel Award, IEEE/ACM CHASE (2024)
GRADESTAR Fellowship (2023, 2024)
Chairperson’s Fellowship (2023)
Ranked 2nd among solid design students at Shiraz University.

Publications Top Notes:

📄 Recent Publications

Kinematic analysis of an under-constrained cable-driven robot using neural networks

Wearable upper limb robotics for pervasive health: A review

Experimental study on the control of a suspended cable-driven parallel robot for object tracking purpose

Reconstructing 3-D Graphical Model Using an Under-Constrained Cable-Driven Parallel Robot

Understanding Human Motion Intention from Motor Imagery Eeg Based on Convolutional Neural Network

A Low-Cost Wearable Exoskeleton for Sitting and Standing Assistance

EEG Motor Imagery Classification using Integrated Transformer-CNN for Assistive Technology Control

MIMO Dynamic Control of a Suspended Underactuated Cable Robot Using Genetic Algorithm

Jingyang Mao | Engineering | Best Researcher Award

Posted on 30/12/202430/12/2024 by Popular Scientist

Dr. Jingyang Mao | Engineering | Best Researcher Award

Lecturer Shanghai Institute of Technology China

🧑‍🏫 Dr. Jingyang Mao is a dedicated lecturer at the School of Electrical and Electronic Engineering, Faculty of Intelligence Technology, Shanghai Institute of Technology. With a Ph.D. in Control Science and Engineering from the University of Shanghai for Science and Technology (2022), he specializes in cutting-edge research on networked control systems and cyber-physical systems. His academic journey also includes a visiting scholar tenure at Louisiana State University, USA (2019–2021). Dr. Mao’s work bridges theoretical innovations with practical applications in modern engineering systems.

Profile

Event‐based reduced‐order H∞$H_{\infty }$ estimation for switched complex networks based on T‐S fuzzy model

Education

🎓 Ph.D. in Control Science and Engineering (2022)

University of Shanghai for Science and Technology, Shanghai, China

✈️ Visiting Scholar (2019–2021)

Department of Electrical and Computer Engineering, Louisiana State University, USA

Experience

👨‍💻 Lecturer (2022–Present)

School of Electrical and Electronic Engineering, Shanghai Institute of Technology
Focus: Cyber-physical systems, networked control, and adaptive filtering

Research Interests

🔍 Dr. Mao’s research interests lie in the fields of:

Cyber-physical systems 🌐
Multi-rate systems ⏱️
Joint recursive filtering 🔄
Unknown input estimation ❓
Adaptive event-triggered mechanisms ⚙️

Awards

🏆 Award Nomination: Best Researcher Award
Recognized for groundbreaking contributions to the theory and application of cyber-physical systems.

Publications Top Notes:

📄 “Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms”

Recursive filtering of multi-rate cyber-physical systems with unknown inputs under adaptive event-triggered mechanisms

Event-Based Distributed Adaptive Kalman Filtering With Unknown Covariance of Process Noises

Brahim El Boudani | Engineering | Best Researcher Award

Posted on 11/12/202411/12/2024 by Popular Scientist

Dr. Brahim El Boudani | Engineering | Best Researcher Award

Lecturer London South Bank University United Kingdom

🎓 Dr. Brahim El Boudani is a passionate researcher and educator specializing in deep learning, virtual reality, and 5G technologies. With a robust technical background in programming and data analysis, he has dedicated his career to academic excellence and innovative research. Currently, a sessional lecturer at London South Bank University, Dr. El Boudani combines teaching with impactful research in fields such as augmented reality and artificial intelligence.

Profile