Hanlin Zhan | Advanced Electric Machine and Drives | Best Researcher Award

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Prof. Hanlin Zhan | Advanced Electric Machine and Drives | Best Researcher Award

Tenured Full Professor, Harbin Institute of Technology (Shenzhen), China

Prof. Hanlin Zhan, born on April 26, 1990, is a Full Professor at Harbin Institute of Technology (Shenzhen), specializing in electrical engineering with a focus on advanced electric drive technologies. He earned his Ph.D. from the University of Sheffield, supported by Siemens-Gamesa, and completed postdoctoral research through the Tsinghua University–Midea Group collaboration. Prof. Zhan has a rich academic and industrial background, having led cutting-edge research at Midea’s Institute of Robotics and Automations. His work is widely published in IEEE Transactions, contributing significantly to sensorless control, PMSM drives, and high-efficiency electric motors. With over 30 million RMB in research funding, he continues to bridge academia and industry. Recognized with awards such as the “Outstanding Young Professor” and Huawei’s “Spark Prize,” he remains a driving force in the electrification of robotics, EVs, eVTOLs, and smart appliances.

Professional Profile

Scopus | Google Scholar | ORCID

Education

Prof. Hanlin Zhan’s educational journey reflects a balance of foundational knowledge and advanced specialization. He earned his Bachelor’s and Master’s degrees in Electrical Engineering from Harbin Institute of Technology (HIT), where he studied under Prof. Gaolin Wang from the esteemed group of Prof. Dianguo Xu. He later pursued a Ph.D. at the University of Sheffield (2014–2017), with his research funded by Siemens-Gamesa and supervised by Prof. Z.Q. Zhu—renowned for his contributions to electric machines. His thesis work was embedded in real-world applications, aligning with industrial innovations. Following this, Prof. Zhan completed a competitive postdoctoral fellowship (2017–2019) through the Midea Group–Tsinghua University Joint Program, mentored by Prof. Xi Xiao. This multidisciplinary exposure enabled him to integrate academic rigor with industrial demands, forming a solid basis for his future research in electric drives and intelligent systems.

Experience

Prof. Hanlin Zhan’s professional experience bridges high-level academia and transformative industry research. He began his career at Midea Group’s Corporate Research Center, serving from 2017 to 2020. There, he quickly advanced from Staff Engineer in the Institute of Motor and Drives to Senior Staff Engineer and Founder of the Institute of Robotics and Automations. In 2020, he transitioned to academia as a Tenured Associate Professor at Harbin Institute of Technology (Shenzhen), where his research and teaching significantly impacted the Department of Robotics and Advanced Manufacture. In December 2024, he was promoted to Full Professor. His career is marked by leadership in high-value projects (over 30 million RMB) and the establishment of collaborative platforms between academic institutions and industrial innovators. His cross-functional experience positions him as a thought leader in intelligent electromechanical systems, making substantial contributions to China’s high-performance robotics and electrified transport sectors.

Awards and Honors

Prof. Hanlin Zhan has received numerous prestigious honors for his contributions to electric drive systems and robotics. He was awarded the First Prize in the Science and Technology Award by the China National Light Industry Council, acknowledging his groundbreaking work in smart appliances. The Harbin Institute of Technology recognized him as an “Outstanding Young Professor,” an honor bestowed for excellence in research, teaching, and innovation. Notably, he received the “Spark Prize” from HUAWEI Technologies, highlighting his influence on intelligent hardware design. He was also globally selected for the elite “Midea Star” Global Recruitment Project in 2017—an initiative identifying under-10 international top talents in electrical and automation research. These accolades reflect Prof. Zhan’s continuous impact on industrial transformation, advanced electric machines, and sensorless control methods, reinforcing his role as a leading expert shaping the future of high-efficiency, intelligent electromechanical systems across diverse applications.

Research Focus 

Prof. Hanlin Zhan’s research focuses on high-performance electric drive technologies tailored for robotics, electric vehicles (EVs), electric vertical take-off and landing aircraft (eVTOLs), and smart home appliances. His work emphasizes sensorless control, high-efficiency motor design, and advanced position estimation methods. He has made pioneering contributions to the modeling and suppression of harmonic errors in IPMSM drives, development of novel vernier and hybrid excited machines, and the integration of zero-sequence current suppression techniques in open-winding PMSM systems. Through strong collaborations with industrial giants like Midea and Siemens-Gamesa, Prof. Zhan ensures that his research directly impacts the market-ready products and sustainable mobility solutions. His lab also explores adaptive feedback control, modular machines, and drive efficiency optimization. This comprehensive approach positions him at the frontier of electrification and automation technologies, where performance, precision, and reliability are paramount.

Publication Top Notes

  1. Adaptive compensation method of position estimation harmonic error for EMF-based observer in sensorless IPMSM drives
    G. Wang, H. Zhan, G. Zhang, X. Gui, D. Xu
    IEEE Trans. Power Electronics, 29(6), pp. 3055–3064, 2014. [Cited by: 256]
    This paper presents a method to compensate harmonic errors in EMF-based position estimators, significantly improving sensorless control accuracy in IPMSM drives.
  2. Analytical on-load subdomain field model of permanent-magnet vernier machines
    Y. Oner, Z.Q. Zhu, L.J. Wu, X. Ge, H. Zhan, J.T. Chen
    IEEE Trans. Industrial Electronics, 63(7), pp. 4105–4117, 2016. [Cited by: 159]
    Introduces an analytical model for PM vernier machines under load, enhancing prediction accuracy of electromagnetic performance.
  3. Enhanced position observer using second-order generalized integrator for sensorless IPMSM drives
    G. Wang, L. Ding, Z. Li, J. Xu, G. Zhang, H. Zhan, R. Ni, D. Xu
    IEEE Trans. Energy Conversion, 29(2), pp. 486–495, 2014. [Cited by: 150]
    Proposes a robust observer utilizing SOGI to improve sensorless control under varying operating conditions.
  4. Self-commissioning of PMSM drives at standstill considering inverter nonlinearities
    G. Wang, L. Qu, H. Zhan, J. Xu, L. Ding, G. Zhang, D. Xu
    IEEE Trans. Power Electronics, 29(12), pp. 6615–6627, 2014. [Cited by: 149]
    Addresses accurate PMSM parameter identification without motion, factoring inverter nonlinearities.
  5. Novel consequent-pole hybrid excited machine with separated excitation stator
    H. Hua, Z.Q. Zhu, H. Zhan
    IEEE Trans. Industrial Electronics, 63(8), pp. 4718–4728, 2016. [Cited by: 141]
    Demonstrates improved flux control in hybrid excitation machines using a novel stator configuration.
  6. Analysis and suppression of zero-sequence circulating current in open winding PMSM drives
    H. Zhan, Z. Zhu, M. Odavic
    IEEE Trans. Industry Applications, 53(4), pp. 3609–3620, 2017. [Cited by: 133]
    Provides insights and control strategies to reduce circulating current in open-winding configurations.
  7. A novel zero-sequence model-based sensorless method for open-winding PMSM
    H. Zhan, Z.Q. Zhu, M. Odavic, Y. Li
    IEEE Trans. Industrial Electronics, 63(11), pp. 6777–6789, 2016. [Cited by: 68]
    Utilizes zero-sequence EMF for sensorless operation, increasing drive robustness.
  8. Efficiency enhancement of general AC drives by remanufacturing induction motors
    R. Ni, D. Xu, G. Wang, X. Gui, G. Zhang, H. Zhan, C. Li
    IEEE Trans. Industrial Electronics, 63(2), pp. 808–820, 2016. [Cited by: 68]
    Proposes cost-effective conversion of IMs into IPMs to boost system efficiency.
  9. Modular PM machines with alternate teeth having tooth tips
    G.J. Li, Z.Q. Zhu, M.P. Foster, D.A. Stone, H.L. Zhan
    IEEE Trans. Industrial Electronics, 62(10), pp. 6120–6130, 2015. [Cited by: 67]
    Investigates novel modular machines for performance and fault tolerance.
  10. Performance comparison of doubly salient reluctance machine topologies
    X.Y. Ma, G.J. Li, G.W. Jewell, Z.Q. Zhu, H.L. Zhan
    IEEE Trans. Industrial Electronics, 63(7), pp. 4086–4096, 2016. [Cited by: 65]
    Assesses different reluctance machine designs under sinewave excitation.

Conclusion

Prof. Zhan is a strong and deserving candidate for the Best Researcher Award, with a proven track record of innovation, impactful research, and industry-oriented contributions.

Danial Waleed | Control and Automation | Best Researcher Award

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Dr Danial Waleed | Control and Automation | Best Researcher Award

Research Assistant at University of Vermont in United States

Danial Waleed is a driven researcher specializing in control systems, mechatronics, and drone technologies. He is currently pursuing his Ph.D. at the University of Vermont, focusing on robust model-free control and sensor outlier detection. Danial’s academic journey began with a B.S. in Electrical Engineering (Minor: Computer Engineering) and an M.S. in Mechatronics from the American University of Sharjah. His research contributions span across drone-based insulator inspection, leak detection systems, and fuel cell technologies for drones. He has been recognized for his innovation and leadership, winning multiple prestigious awards, including the Best Student Paper Award at IEEE SMC 2023. His expertise extends to UAV operations, software proficiencies in MATLAB, Python, and TensorFlow, among others. Danial is also actively involved in professional communities, serving as a manuscript reviewer and a student leader at the IEEE Green Mountain chapter.

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Strengths for the Award

Danial Waleed exhibits remarkable qualifications and professional experience that align with the Best Researcher Award criteria. His academic journey showcases a strong background in electrical and mechatronics engineering, with a Ph.D. from the University of Vermont and two degrees from the American University of Sharjah. His research work, particularly in model-free control, sensor outlier detection, and drone-based technologies, is highly relevant in today’s engineering and technological advancements. The Best Student Paper Award from IEEE SMC 2023 and his multiple publications in high-impact journals further reinforce his reputation as an innovative researcher.

Additionally, Waleed has made significant contributions to his field, including co-authoring a paper on in-pipe leak detection that has been cited 69 times. His work on drone-based insulator monitoring demonstrates his ability to apply engineering principles to real-world problems, a quality that is highly valued in the research community. His professional memberships, service as a manuscript reviewer, and leadership in student associations and IEEE chapters further add to his strong research and leadership profile.

Areas for Improvement

While Danial Waleed has strong research output, he could focus on increasing collaborations with international researchers to expand his influence and visibility in global networks. Engaging in interdisciplinary projects beyond electrical and biomedical engineering, such as in AI or renewable energy, may further enhance his research breadth and impact. Additionally, the relatively lower citation counts for some of his recent papers suggest the potential for greater promotion of his work through conferences and scientific communities.

Education 

Danial Waleed completed his Ph.D. in 2024 at the University of Vermont in the Department of Electrical and Biomedical Engineering. His dissertation focused on the robustification of model-free control systems via sensor outlier detection, with a CGPA of 3.54/4.0. Prior to this, Danial earned his M.S. in Mechatronics Engineering from the American University of Sharjah in 2019, where he graduated with a CGPA of 3.61/4.0. His thesis explored innovative approaches to drone-based insulator inspection for power grid maintenance. Danial’s academic journey began with a B.S. in Electrical Engineering from the same institution, completed in 2016 with a CGPA of 3.31/4.0 and a Minor in Computer Engineering. Throughout his education, Danial has been actively involved in research, particularly in the areas of control systems, automation, and mechatronics.

Experience 

Danial Waleed has gained a wealth of professional experience in both research and teaching roles. Since 2019, he has been a Graduate Research and Teaching Assistant at the University of Vermont, where he is involved in groundbreaking research on model-free control and sensor outlier detection. Between 2016 and 2019, Danial served as a Graduate Research and Teaching Assistant at the American University of Sharjah, where he contributed to various research projects in mechatronics and drone technologies. In 2016, he worked as an Undergraduate Teaching Assistant at the Department of Electrical Engineering at the same institution, assisting with control systems and robotics coursework. Additionally, he completed an internship at SAIPEM SPA in Sharjah, contributing to the ARBI 20/23 project in 2015. His roles have consistently emphasized research innovation, teaching, and team collaboration.

Awards and Honors 

Danial Waleed’s exceptional contributions to research and innovation have earned him several prestigious awards. In 2023, he received the Best Student Paper Award at the IEEE Systems, Man, and Cybernetics (SMC) conference, recognizing his outstanding work in control systems. In 2021, Danial was honored with the Teaching Assistant Award by the University of Vermont for his exemplary dedication to student mentoring and teaching. His innovative research on drone technologies won him the Student Innovation Award from the Sharjah Electric Water Authority in 2018. Earlier in his academic career, Danial was awarded the National Robotics for Good Award in 2017 from the American University of Sharjah. Additionally, in 2016, he earned the Best Student Poster Award at the same institution for his contributions to control and automation systems. These accolades underscore his commitment to research and teaching excellence.

Research Focus

Danial Waleed’s research primarily focuses on advancing the fields of control systems, automation, and sensor technologies. His Ph.D. work at the University of Vermont involves the robustification of model-free control systems through the innovative use of sensor outlier detection, improving the reliability and efficiency of such systems in practical applications. Danial is also heavily invested in drone-based technologies, having developed systems for ceramic insulator monitoring and leak detection robots. His research interests extend to energy-efficient drone technologies, where he explores the use of small-capacity fuel cells for improving drone performance. Additionally, Danial has investigated the application of Kalman filters in model-free control environments, which has contributed to the broader understanding of real-time estimation and control robustness in the presence of unreliable data. His multidisciplinary approach positions him at the forefront of control systems and mechatronics innovation.

Publication Top Notes

  • 📄 An in-pipe leak detection robot with a neural-network-based leak verification system, IEEE Sensors Journal, 2018, 69 citations
  • 🚁 Drone-based ceramic insulators condition monitoring, IEEE Transactions on Instrumentation and Measurement, 2021, 39 citations
  • ⚙️ Using Small Capacity Fuel Cells Onboard Drones for Battery Cooling: An Experimental Study, Applied Sciences, 2018, 20 citations
  • 🛠️ Dynamic friction characterization of a linear servo motor using an optimal sinusoidal reference tracking controller, Journal of Robotics and Mechatronics, 2018, 6 citations
  • 🔧 Friction estimation of a linear voice coil motor using robust state space sinusoidal reference tracking, International Symposium on Mechatronics and its Applications, 2018, 5 citations
  • 🔄 Integration of a robust Kalman filter with model-free control, IEEE Conference on Control Technology and Applications, 2022, 2 citations
  • 🚁 Drone-based outdoor insulator inspection, 2019, 1 citation
  • 📉 Simultaneous Parameter Estimation in Model-Free Control, American Control Conference, 2024
  • 🛰️ Robust State Estimation for Satellite Formations in the Presence of Unreliable Measurements, IEEE SMC, 2023

Conclusion

Danial Waleed’s accomplishments make him a suitable candidate for the Best Researcher Award. His impactful research in control systems, sensor detection, and UAV technologies, combined with a solid academic and professional track record, demonstrates both his leadership and innovation. With continued focus on expanding his research collaborations and visibility, he could further enhance his candidacy for this prestigious award.