Beulah Sujan Karumanchi | Engineering | Best Researcher Award

Ms. Beulah Sujan Karumanchi | Engineering | Best Researcher Award

Research Scholar at  National Institute of Technology Andhra Pradesh, India

Dr. Beulah Sujan K is a researcher in Wireless Communication Networks with a Ph.D. in Heterogeneous Cognitive Radio Networking from NIT Andhra Pradesh. Her expertise spans dynamic spectrum access, soft fusion schemes, and automated frequency coordination. She holds an M.Tech in ECE (MEMS) from Pondicherry University and a B.Tech in ECE from Acharya Nagarjuna University, both with distinction.

Profile:

🎓 Academic Background:

  • Ph.D. in Heterogeneous Cognitive Radio Networking, NIT Andhra Pradesh

  • M.Tech (ECE – MEMS), Pondicherry University – CGPA: 9.22/10

  • B.Tech (ECE), Acharya Nagarjuna University – CGPA: 9.2/10

🧠 Core Skills:

  • Mathematical Analysis

  • Numerical Methods

  • Algorithm Design

  • Monte Carlo Simulations

  • Performance Evaluation

🔍 Research Interests:

  • Wireless Communication Networks

  • Dynamic Spectrum Access

  • Soft Fusion Techniques

  • Cognitive Radio Networks

  • Automated Frequency Coordination Systems

🧪 Technical Proficiency:

  • MATLAB

  • Optimization Algorithms

  • Intellisuite Software

  • LaTeX for Technical Documentation

📚 Teaching & Mentorship:

  • Courses: Analog & Digital Communications, Wireless Communications, Signals & Systems

  • Labs: Communication Systems, LICA Lab

  • Mentoring UG/PG students in advanced communications

🏅 Achievements:

  • 🏆 UGC-NET Qualified (2018, 2019, 2024)

  • 🎯 GATE Qualified (2023)

  • 🎓 PG Merit Scholarship (2017)

  • 🥈 Silver Medal – State-Level Tech Quiz (2015)

  • 🥇 Gold Medal – Technical Quiz (2014)

📄 Key Publications:

  • IEEE, Springer, and SCI-indexed journals

  • Topics: Cognitive Radio, Spectrum Sensing, MEMS, Soft Fusion

  • Recent work under review in IEEE Transactions on Cognitive Communications and Signal Processing

Publication:

Efficient spectrum allocation by heterogeneous automated frequency coordination network within 6 GHz band

You Zhang | Engineering | Best Researcher Award

Mr. You Zhang | Engineering | Best Researcher Award

University of Rochester, United States

Dr. You (Neil) Zhang is a Ph.D. candidate in Electrical and Computer Engineering at the University of Rochester, specializing in machine learning for speech, acoustics, and audio signal processing. His research focuses on spatial audio (HRTF personalization), speech anti-spoofing, singing voice deepfake detection, and audio-visual learning. He has held research roles at Dolby, Meta, Microsoft, Tencent, and Bytedance, contributing significantly to areas like perceptual HRTF modeling and audio-visual deepfake detection.

Profile:

🎓 Education:

  • Ph.D. in Electrical & Computer Engineering (Expected 2025)
    University of Rochester

  • M.S., University of Rochester

  • B.Eng., University of Electronic Science & Technology of China

  • Exchange Program, UC Berkeley

🧠 Research Interests:

  • Spatial Audio & HRTF Personalization 🎧

  • Speech Deepfake Detection & Audio Security 🔐

  • Multimodal Learning: Audio-Visual & Emotional Speech Synthesis 🎥🗣️

🏆 Honors & Fellowships:

  • IEEE SPS Scholarship (2024)

  • NIJ Graduate Research Fellowship (2023)

  • ICASSP Rising Star in Signal Processing (2023)

  • Open Scholarship Award @ UR (2025)

🧪 Research & Industry Experience:

  • Dolby Labs 🎶 – Sr. Researcher, Multimodal Spatial Audio

  • Meta Reality Labs 🧠 – HRTF Perceptual Learning

  • Microsoft, Tencent, ByteDance, IngenID 💼 – AI R&D Internships

  • Audio Information Research Lab, UR 🎙️ – Deepfake Detection, AV Speech, HRTF Neural Fields

📚 Selected Publications:

  • IEEE T-MM, SPL, ICASSP, Interspeech, NAACL

  • Co-organizer of SVDD Challenge at SLT 2024 & MIREX 2024

  • Contributor to Handbook of Biometric Anti-spoofing (Springer)

🎤 Talks & Tutorials:

  • Invited speaker at CMU, NII Japan, ISCA SPSC

  • Tutorials @ ASA, ICME, AES (Topics: HRTF, Deepfakes, ML for Acoustics)

🎓 Teaching & Mentorship:

  • TA for Machine Learning, Audio Signal Processing, Random Processes

  • Mentored 10+ undergrad and graduate students in UR, Tsinghua, UESTC

💼 Professional Service:

  • Reviewer for IEEE TASLP, TPAMI, ICASSP, Interspeech, CVPR Workshops

  • Member: IEEE, ASA, ACM, AES

  • DEI Committee @ UR ECE | Organizer of AR/VR Events

💻 Skills:

  • Programming: Python, MATLAB, C, Java

  • Tools: Git, Linux, PyTorch, Slurm

  • Languages: English 🇺🇸, Mandarin 🇨🇳

🏃 Hobbies & More:

  • Half-Marathon Finisher 🏅

  • Loves stand-up paddleboarding, travel, badminton 🌊✈️🏸

Google Scholar Citation Metrics:

  • Citations: 751 (All time) | 751 (Since 2020)

  • h-index: 12 (All time) | 12 (Since 2020)

  • i10-index: 14 (All time) | 14 (Since 2020)

Publication Top Notes:

  1. One-class Learning Towards Synthetic Voice Spoofing Detection
    Y. Zhang, F. Jiang, Z. Duan
    IEEE Signal Processing Letters, vol. 28, pp. 937–941, 2021.

  2. Speech Driven Talking Face Generation from a Single Image and an Emotion Condition
    S.E. Eskimez, Y. Zhang, Z. Duan
    IEEE Transactions on Multimedia, vol. 24, pp. 3480–3490, 2021.

  3. UR Channel-Robust Synthetic Speech Detection System for ASVspoof 2021
    X. Chen, Y. Zhang*, G. Zhu*, Z. Duan
    ASVspoof 2021 Workshop, 2021.

  4. SingFake: Singing Voice Deepfake Detection
    Y. Zang, Y. Zhang*, M. Heydari, Z. Duan
    IEEE ICASSP, 2024.

  5. An Empirical Study on Channel Effects for Synthetic Voice Spoofing Countermeasure Systems
    Y. Zhang, G. Zhu, F. Jiang, Z. Duan
    Interspeech, pp. 4309–4313, 2021.

  6. SAMO: Speaker Attractor Multi-Center One-Class Learning for Voice Anti-Spoofing
    S. Ding, Y. Zhang, Z. Duan
    IEEE ICASSP, 2023.

  7. A Probabilistic Fusion Framework for Spoofing Aware Speaker Verification
    Y. Zhang, G. Zhu, Z. Duan
    Odyssey: The Speaker and Language Recognition Workshop, pp. 77–84, 2022.

  8. Global HRTF Personalization Using Anthropometric Measures
    Y. Wang, Y. Zhang, Z. Duan, M. Bocko
    Audio Engineering Society (AES) 150th Convention, 2021.

  9. Rethinking Audio-Visual Synchronization for Active Speaker Detection
    A. Wuerkaixi, Y. Zhang, Z. Duan, C. Zhang
    IEEE MLSP, 2022.

  10. CtrSVDD: A Benchmark Dataset and Baseline Analysis for Controlled Singing Voice Deepfake Detection
    Y. Zang, J. Shi, Y. Zhang, et al.
    Interspeech, pp. 4783–4787, 2024.

  11. VERSA: A Versatile Evaluation Toolkit for Speech, Audio, and Music
    J. Shi, H. Shim, J. Tian, Y. Zhang, et al.
    NAACL (Demo Track), 2025.

  12. HRTF Field: Unifying Measured HRTF Magnitude Representation with Neural Fields
    Y. Zhang, Y. Wang, Z. Duan
    IEEE ICASSP, 2023.

  13. SVDD 2024: The Inaugural Singing Voice Deepfake Detection Challenge
    Y. Zhang, Y. Zang, J. Shi, R. Yamamoto, T. Toda, Z. Duan
    IEEE SLT, pp. 782–787, 2024.

  14. DyViSE: Dynamic Vision-Guided Speaker Embedding for Audio-Visual Speaker Diarization
    A. Wuerkaixi, K. Yan, Y. Zhang, Z. Duan, C. Zhang
    IEEE MMSP, 2022.

  15. Predicting Global Head-Related Transfer Functions from Scanned Head Geometry Using Deep Learning and Compact Representations
    Y. Wang, Y. Zhang, Z. Duan, M. Bocko
    arXiv preprint, arXiv:2207.14352, 2022.

  16. Learning Arousal-Valence Representation from Categorical Emotion Labels of Speech
    E. Zhou, Y. Zhang, Z. Duan
    IEEE ICASSP, 2024.

  17. SVDD Challenge 2024: A Singing Voice Deepfake Detection Challenge Evaluation Plan
    Y. Zhang, Y. Zang, J. Shi, et al.
    arXiv preprint, arXiv:2405.05244, 2024.

  18. ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech
    X. Wang, H. Delgado, Y. Zhang, et al.
    Computer Speech & Language, 2025.

  19. Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions
    K. Zhou, Y. Zhang, S. Zhao, et al.
    arXiv preprint, arXiv:2409.16681, 2024.

  20. Mitigating Cross-Database Differences for Learning Unified HRTF Representation
    Y. Wen, Y. Zhang, Z. Duan
    IEEE WASPAA, 2023.

 

Dr. Xiao Fu | Engineering | Best Researcher Award

Dr. Xiao Fu | Engineering | Best Researcher Award

Xi`an University Of Science And Technology, China

Profile

Scopus

Education 🎓

Dr. Xiao Fu is currently pursuing her Ph.D. at Xi’an University of Science and Technology. She completed her master’s degree at Nanchang Institute of Technology and her undergraduate studies at Xi’an University of Science and Technology. Throughout her academic career, she has demonstrated exceptional dedication to research and scientific discovery.

Professional Experience 💼

Dr. Fu has made significant contributions to the field of bio-cement applications for sand stabilization. Her research focuses on enhancing soil mechanical properties using plant-based bio-cement and organic materials. She has published in leading journals, including Applied Biochemistry and Biotechnology and Bioresources & Bioprocessing, collaborating with experts to develop eco-friendly solutions for soil reinforcement.

Technical Skills 🛠️

Dr. Fu is highly skilled in geotechnical testing and analysis, biochemical soil treatment, and multivariate experimental design. Her expertise lies in combining biological and engineering principles to develop sustainable soil stabilization techniques.

Teaching & Mentorship 👨‍🏫

She actively participates in mentorship and academic guidance for postgraduate students, helping them refine their research methodologies. She also delivers guest lectures on soil mechanics and stabilization techniques, fostering knowledge exchange within the academic community.

Awards & Honors 🏅

Dr. Fu has been recognized for her outstanding academic performance, including being a top scorer in her doctoral entrance exams. Her research contributions have received acclaim for their innovation and impact in geotechnical engineering.

Research Interests 🔍

Her research focuses on sustainable soil improvement, bio-cement applications, and desert sand stabilization. Passionate about pioneering eco-friendly geotechnical solutions, Dr. Fu is dedicated to developing innovative, sustainable technologies for the future of soil engineering.

Publications Top Notes: 📝

“Experimental Study on Mechanical Properties of Cured Sand Combined with Plant-Based Bio-cement (PBBC) and Organic Materials”

Authors: Xiao Fu, Wan-jun Ye, Gang Yuan, Xue-li Zhang, Rui-yuan Niu

Publication Year: 2024

Journal: Applied Biochemistry and Biotechnology

Citations: Currently, no available citation metrics

“An experimental study on the curing of desert sand using bio-cement”

Authors: Xiao Fu, Wan-jun Ye

Publication Year: 2024

Journal: Bioresources and Bioprocessing

Citations: No citation metrics available yet

“Experimental study on the mechanical properties of desert sand improved by the combination of additives and bio-cement”

Authors: Wan-jun Ye, Xiao Fu, Yi Wu, et al.

Publication Year: 2024

Journal: Bioprocess and Biosystems Engineering

Citations: No citation data available at this time

“Soybean urease induced calcium carbonate precipitation multivariate experimental study”

Authors: Meng Cui, Xiao Fu, Junjie Zheng, et al.

Publication Year: 2022

Journal: Rock and Soil Mechanics

Citations: No specific citation metrics available

Jamal Alotaibi | Engineering | Best Researcher Award

Assist. Prof. Dr. Jamal Alotaibi | Engineering | Best Researcher Award

Department of Computer Engineering, College of Computer, Qassim University, Buraydah, Saudi Arabia.

Dr. Jamal Alotaibi is an accomplished researcher and educator in the field of Computer Engineering. With expertise in IoT, AI, and security, he has contributed significantly to the advancement of Smart Transportation and Vehicle-to-Vehicle (V2V) communication. Currently serving as the Head of the Computer Engineering Department at Qassim University, his work focuses on secure and efficient computing frameworks for the Internet of Vehicles (IoV).

Profile

Google Scholar

Education 🎓

  • Ph.D. in Computer Engineering (2018 – 2022) – Wayne State University, USA

  • M.Sc. in Electrical and Computer Engineering (2016 – 2017) – Wayne State University, USA

  • B.Sc. in Computer Engineering (2008 – 2013) – Qassim University, KSA

Experience 👨‍🏫

  • Qassim University (2022 – Present) – Assistant Professor, now Head of the Computer Engineering Department (2024–Present)

  • Wayne State University (2016 – 2022) – Research Assistant in IoT and Security Labs

  • STC Company (2013) – Network Engineer

  • Consultations:

    • Ford Motor Company (2020 – 2022) – Embedded Systems Consultant for Electric Vehicles

    • Verizon Company (2021–2022) – V2V Infrastructure Consultant

    • City of Detroit (2021–2023) – IoV Consultant

Research Interests 🔬

  • Internet of Vehicles (IoV) and Fog Computing

  • Software-Defined Networking (SDN) for Smart Transportation

  • Blockchain-based Security Solutions

  • Machine Learning for Secure Communication Systems

Awards 🏆

  • Head of IoT Research Lab – Wayne State University

  • Head of Research Committee – Qassim University (2023 – Present)

Publications Top Notes: 📚

SAFIoV: A Secure and Fast Communication in Fog-Based IoV Using SDN and Blockchain

IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2021

Read Here

A Lightweight and Fog-Based Authentication Scheme for Internet-of-Vehicles

IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEM-CON), 2021

Read Here

PPIoV: A Privacy-Preserving Framework for IoV-Fog Using Federated Learning and Blockchain

IEEE World AI IoT Congress, 2022

Read Here

Insight into IoT Applications and Common Practice Challenges

Insight Journal, 2022

Read Here

A hybrid software-defined networking approach for enhancing IoT cybersecurity with deep learning and blockchain in smart cities

SDN-Enabled Efficient Resource Utilization in a Secure, Trustworthy and Privacy Preserving IOV-Fog Environment

huayu qi | Engineering | Best Researcher Award

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

Scopus

Orcid

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: 📚

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

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

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

Scopus

Google Scholar

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., 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

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

Jingyang Mao | Engineering | Best Researcher Award

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

Orcid

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”

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

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

RISHITEJ CHAPARALA | Engineering | Best Researcher Award

Mr. RISHITEJ CHAPARALA | Engineering | Best Researcher Award

Assistant professor Pragati engineering college India

👨‍🎓 Rishitej Chaparala is an Assistant Professor and Ph.D. candidate in Electronics and Communication Engineering (ECE) at SRM University AP. With 6.5 years of teaching experience, he has been an integral part of institutions like TKR College of Engineering, BVC Engineering College, and Kallam Harnadhreddy Institute of Tech & Engineering. Rishitej’s primary research interest lies in plasmonic waveguide and antenna design, spanning the RF to THz spectrum. He is an active member of OPTICA, IEEE, and IETE and has filed multiple patents in the field of sensor systems.

Profile

Scopus

Google scholar

Education 🎓

Rishitej holds a Ph.D. (Full-time) in ECE from SRM University AP, with his synopsis submitted in October 2024. He completed his M.Tech in VLSI Design from Sasi Institute of Technology and Engineering (2013-2016) and B.E. in ECE from GGR College of Engineering, Vellore, in 2011.

Experience 💼

With over 6.5 years in teaching and 3 years in research, Rishitej has held positions in institutions like TKR College of Engineering, BVC Engineering College, Dhanekula Institute of Engineering & Tech, and currently at Pragati Engineering College, Rajahmundry. He has also worked as a Quality Analyst at SERCO Pvt Ltd for a year.

Research Interests 🔬

His research focuses on Plasmonic Waveguide/Antenna Design across the RF to THz spectrum. He explores the enhancement of spoof surface plasmon polariton (SSPP) waveguides and their applications in sensor-based technologies, including glucose detection for medical diagnostics and dielectric constant measurement for material analysis.

Awards 🏆

Rishitej’s work has been recognized at national and international platforms. His research on SSPP waveguides has earned him multiple accolades in conferences and journals. Notable recognitions include contributions to IEEE Sensors Journal, Optical Engineering, and Progress in Electromagnetics Research M.

Publications Top Notes: 📚

Chaparala, R., Shaik Imamvali, & Sreenivasulu Tupakula. “Enhancement of spoof surface plasmon polariton waveguide performance through modified groove width.” Optical Engineering, 63.5 (2024): 055102-055102. DOI: 10.1117/1.OE.63.5.055102

Chaparala, R., Shaik Imamvali, & Sreenivasulu Tupakula. “Spoof surface plasmon polaritons based feeder for a dielectric rod antenna at microwave frequencies.” Progress in Electromagnetics Research M, Vol. 129, 23-32, 2024.

Chaparala, R., et al. “Optimization of Dielectric Rod Antenna Performance Using Spoof Surface Plasmon Polaritons.” Sensors MDPI (Accepted, IF: 3.4).

Imamvali, S., Chaparala, R., Tupakula, S. “Spoof surface plasmon polaritons based detection of glucose in blood phantom for medical diagnosis.” IEEE Sensors Journal (2024, IF: 4.3).

Kolli, V. R., Chaparala, R., Tupakula, S., & Talabattula, S. “A high-sensitive integrated optic serially coupled racetrack ring resonator based pressure sensor.” Optical Materials (2024, Q1, IF: 3.1).

Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Prof. Yusuf Alper KAPLAN | Engineering | Best Researcher Award

Prof. Osmaniye Korkut Ata Unv. Turkey

Dr. Yusuf Alper Kaplan is a Professor of Energy Systems Engineering at Osmaniye Korkut Ata University in Turkey. He has a distinguished career in renewable energy, specializing in solar and wind energy modeling, estimation, and system performance. With over two decades of experience, Dr. Kaplan has contributed to advancing energy systems through innovative methodologies and predictive models.

Profile

Google scholar

Education 🎓

  • Bachelor’s in Electrical and Electronics Engineering, Gaziantep University, 2002
  • Master’s in Electrical and Electronics Engineering, Çukurova University, 2008
  • Ph.D. in Electrical and Electronics Engineering, Anadolu University, 2014

Professional Experience 💼

  • Lecturer (2004-2009) at Çukurova University
  • Research Assistant (2010-2014) at Anadolu University
  • Assistant Professor (2014-2018), Associate Professor (2018-2023), and Professor (2023-present) at Osmaniye Korkut Ata University
  • Head of Department of Energy Systems Engineering (2019-2020)
  • Director of the Continuing Education Centre (2020-present)

Research Interests 🔬

Dr. Kaplan’s research focuses on renewable energy, especially solar and wind energy systems. His work involves developing statistical and computational models for solar radiation forecasting, wind energy assessment, and performance optimization of renewable energy sources in varying environmental conditions.

Awards and Recognitions 🏆

Dr. Kaplan has been honored for his contributions to renewable energy and academic excellence. His achievements include national and international recognitions for advancements in energy system performance modeling and contributions to sustainable energy solutions.

Publications Top Notes: 📚

Kaplan, Y. A. (2024). Forecasting of global solar radiation: A statistical approach using simulated annealing algorithm. Engineering Applications of Artificial Intelligence, 136, 109034. (Cited by 15)

Kaplan, A. G., & Kaplan, Y. A. (2024). Using of the Weibull distribution in developing global solar radiation forecasting models. Environmental Progress & Sustainable Energy. (Cited by 10)

Kaplan, Y. A. (2023). Development of backpropagation algorithm for estimating solar radiation: A case study in Turkey. Revue Roumaine des Sciences Techniques, 68(3), 313-316. (Cited by 8)