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. Danialโs 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.
profile
Google Scholar
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 todayโs 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.
Educationย
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. Danialโs 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.
Experienceย
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 Honorsย
Danial Waleedโs 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 Waleedโs 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
- ๐ An in-pipe leak detection robot with a neural-network-based leak verification system, IEEE Sensors Journal, 2018, 69 citations
- ๐ Drone-based ceramic insulators condition monitoring, IEEE Transactions on Instrumentation and Measurement, 2021, 39 citations
- โ๏ธ Using Small Capacity Fuel Cells Onboard Drones for Battery Cooling: An Experimental Study, Applied Sciences, 2018, 20 citations
- ๐ ๏ธ Dynamic friction characterization of a linear servo motor using an optimal sinusoidal reference tracking controller, Journal of Robotics and Mechatronics, 2018, 6 citations
- ๐ง 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
- ๐ Integration of a robust Kalman filter with model-free control, IEEE Conference on Control Technology and Applications, 2022, 2 citations
- ๐ Drone-based outdoor insulator inspection, 2019, 1 citation
- ๐ Simultaneous Parameter Estimation in Model-Free Control, American Control Conference, 2024
- ๐ฐ๏ธ 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.