Shijie Li | Embodied AI | Best Researcher Award

Dr. Shijie Li | Embodied AI | Best Researcher Award

Scientist | A*STAR Institute for Infocomm Research | Singapore

Dr. Shijie Li is a computer vision researcher with expertise in 3D perception, embodied AI, and vision-language models, contributing to the development of intelligent systems for real-world applications. He earned his Ph.D. in Computer Science from Bonn University under the supervision of Prof. Juergen Gall, following a master’s degree from Nankai University and a bachelor’s degree in Automation Engineering from the University of Electronic Science and Technology of China. His professional experience includes research positions and internships at A*STAR Singapore, Qualcomm AI Research in Amsterdam, Intel Labs in Munich, Alibaba DAMO Academy in China, and Technische Universität München in Germany, showcasing strong international collaborations and applied research expertise. His research interests lie in 3D scene understanding, motion forecasting, vision-language integration, semantic segmentation, and novel view synthesis. He has published in leading journals and conferences such as ICCV, CVPR, IEEE TPAMI, IEEE TNNLS, WACV, BMVC, ICRA, and IROS, reflecting impactful and consistent contributions. His academic excellence has been recognized through scholarships and awards including the Fortis Enterprise Scholarship, National Inspirational Scholarship, First Class Scholarship, and Outstanding Graduate Award. He has also served as a reviewer for top journals and conferences such as IEEE TPAMI, IJCV, CVPR, ICCV, ECCV, NeurIPS, and AAAI, reflecting his active role in the research community. His skills include deep learning, diffusion models, semantic and motion forecasting, vision-language modeling, and embodied AI, with a focus on interdisciplinary innovation. His research impact is reflected in 183 citations, 10 documents, and an h-index of 7.

Profiles: Google Scholar | Scopus | ORCID | LinkedIn

Featured Publications

Li, S., Abu Farha, Y., Liu, Y., Cheng, M., & Gall, J. (2023). MS-TCN++: Multi-stage temporal convolutional network for action segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(6), 6647–6658.

Chen, X., Li, S., Mersch, B., Wiesmann, L., Gall, J., Behley, J., & Stachniss, C. (2021). Moving object segmentation in 3D LiDAR data: A learning-based approach exploiting sequential data. IEEE Robotics and Automation Letters, 6(4), 6529–6536.

Qiu, Y., Liu, Y., Li, S., & Xu, J. (2020). MiniSeg: An extremely minimum network for efficient COVID-19 segmentation. Proceedings of the AAAI Conference on Artificial Intelligence, 34(11), 13180–13187.

Li, S., Chen, X., Liu, Y., Dai, D., Stachniss, C., & Gall, J. (2021). Multi-scale interaction for real-time LiDAR data segmentation on an embedded platform. IEEE Robotics and Automation Letters, 7(2), 738–745.

Li, S., Zhou, Y., Yi, J., & Gall, J. (2021). Spatial-temporal consistency network for low-latency trajectory forecasting. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 10737–10746.

Huaiqu Feng | Agricultural Robotics | Best Researcher Award

Dr. Huaiqu Feng | Agricultural Robotics | Best Researcher Award

Huaiqu Feng | Zhejiang University | China

Huaiqu Feng is a skilled researcher with expertise in robotics and electromechanical intelligent equipment, focusing on computer vision, deep learning, and image processing for agricultural automation. He holds a Master of Engineering in Agricultural Mechanization Engineering from Northeast Agricultural University and a Bachelor of Engineering in Automation from Hubei Normal University. Throughout his academic and professional career, he has participated in multiple research projects, including provincial science and technology programs and industrial transformation initiatives, demonstrating strong capability in applying AI and robotics to practical agricultural problems. He has contributed to several high-impact publications, patents, and software developments, showcasing his innovative approach and technical proficiency. His professional experience includes leading research teams, mentoring students, and managing projects that integrate advanced technologies into real-world applications. His research interests span robotics, precision agriculture, intelligent equipment, and AI-based image analysis. He is proficient in Matlab for algorithm development, microcontroller programming with STM32, and 3D modeling and simulation using Creo and Pro/E. Huaiqu Feng also actively engages in community and leadership roles through student organizations, innovation competitions, and volunteer initiatives, highlighting his commitment to fostering collaboration and advancing the research community. 426 Citations, 20 Documents, 8 h-index.

Profiles: Google Scholar | Scopus | ORCID

Featured Publications

  1. Quan, L., Feng, H., Lv, Y., Wang, Q., Zhang, C., Liu, J., & Yuan, Z. (2019). Maize seedling detection under different growth stages and complex field environments based on an improved Faster R–CNN. Biosystems Engineering, 184, 1-23.

  2. Zhao, G., Quan, L., Li, H., Feng, H., Li, S., Zhang, S., & Liu, R. (2021). Real-time recognition system of soybean seed full-surface defects based on deep learning. Computers and Electronics in Agriculture, 187, 106230.

  3. Li, D., Li, B., Long, S., Feng, H., Xi, T., Kang, S., & Wang, J. (2023). Rice seedling row detection based on morphological anchor points of rice stems. Biosystems Engineering, 226, 71-85.

  4. Wei, C., Li, H., Shi, J., Zhao, G., Feng, H., & Quan, L. (2022). Row anchor selection classification method for early-stage crop row-following. Computers and Electronics in Agriculture, 192, 106577.

  5. Li, D., Li, B., Long, S., Feng, H., Wang, Y., & Wang, J. (2023). Robust detection of headland boundary in paddy fields from continuous RGB-D images using hybrid deep neural networks. Computers and Electronics in Agriculture, 207, 107713.

Michael Koch | Robotics | Best Researcher Award

Prof . Dr . Michael Koch | Robotics | Best Researcher Award

Professor at Technische Hochschule Nürnberg, Germany

Prof. Dr.-Ing. Dipl.-Wirt.-Ing. Michael Koch is a distinguished German academic and research professor in mechanical engineering with a robust focus on engineering design, simulation technologies, and additive manufacturing. Currently serving as Vice Dean and Professor at Technische Hochschule Nürnberg Georg Simon Ohm, he has over 20 years of experience in academia and industry. His research integrates innovative technologies like augmented reality, motion capture, and cyber-physical systems to optimize design processes and intelligent manufacturing systems. He has published extensively in high-impact conferences and journals, and he actively leads curriculum and academic initiatives in engineering education. As a certified Six Sigma Black Belt and a key user of PTC CREO Parametric, Prof. Koch demonstrates a blend of theoretical depth and industrial pragmatism. His contributions toward intuitive robot programming, knowledge-based simulation, and 3D geometry integration in product development make him a prominent figure in Germany’s mechanical engineering research landscape.

Professional Profile 

Education🎓F

Prof. Michael Koch has a strong academic foundation combining mechanical engineering and industrial engineering. He earned his Dr.-Ing. (Ph.D.) in Engineering Design from Friedrich-Alexander University Erlangen-Nuremberg in 2005 with the distinction of “very good.” His doctoral work laid the groundwork for his later research in design optimization and simulation integration. He previously completed a Diploma in Mechanical Engineering (Dipl.-Ing.) from the same university in 2000, specializing in design and computation with an excellent academic grade (1.8). Complementing his technical background, he pursued a Diploma in Industrial Engineering (Dipl.-Wirt.-Ing.) at the University of Hagen (2001–2004), focusing on marketing and human resources, which reflects his interdisciplinary strengths. This combination of design engineering and business-oriented knowledge has enabled him to lead academic programs and collaborate effectively with the manufacturing industry. His diverse academic trajectory supports his holistic approach to innovation in both engineering education and applied research.

Professional Experience📝

Prof. Koch’s professional journey spans both academic excellence and industry leadership. He has been a Professor at Technische Hochschule Nürnberg Georg Simon Ohm since 2009, where he teaches engineering design and machine parts and serves as the Vice Dean and Head of the Master’s Program in Mechanical Engineering. He has played a pivotal role in curriculum design and quality assurance within the faculty. Before transitioning fully into academia, he worked at Schaeffler Technologies GmbH & Co. KG (2005–2009) in the special machines department, where he managed key industrial projects. Earlier in his career, he served as a scientific assistant at Friedrich-Alexander University Erlangen-Nuremberg, contributing to engineering research and instruction. Prof. Koch also holds certifications like Six Sigma Black Belt and Key User of PTC CREO Parametric, underscoring his practical orientation. His combined industry-academic experience uniquely positions him as a leader in engineering innovation and applied research.

Research Interest🔎

Prof. Koch’s research interests lie at the intersection of engineering design, additive manufacturing, simulation technologies, and robotics. His work frequently explores knowledge-based design methods, real-geometry integration in simulations, and intuitive user interfaces for robotic applications. He is particularly interested in optimizing design and manufacturing processes through augmented reality, motion capture, and cyber-physical systems. His studies also delve into reverse engineering, finite element (FE) simulations using real 3D-scanned data, and product development driven by simulation and automation. Prof. Koch aims to bridge the gap between idealized models and real-world manufacturing variances, improving accuracy and efficiency in digital engineering. His interdisciplinary approach integrates mechanical engineering, human-computer interaction, and data-driven decision-making, resulting in innovations that benefit both academia and industry. His research significantly contributes to smart manufacturing, lightweight design, and automation in production, making him a key figure in the advancement of intelligent engineering systems.

Award and Honor🏆

While Prof. Michael Koch’s CV does not list formal awards or honors explicitly, his distinguished academic positions and repeated invitations to present at international conferences reflect peer recognition of his expertise. His appointment as Vice Dean and Research Professor at Technische Hochschule Nürnberg, along with his leadership in curriculum development and examination boards, underscores the institutional trust placed in him. He has been a consistent contributor to high-impact events such as IFAC Workshops, ISR, Sim-AM, ICED, and the Design for X Symposium, where his papers have been accepted for both presentation and publication—an honor in the global research community. His certification as a Six Sigma Black Belt and designation as a Key User of industry-standard CAD tools (PTC CREO) also highlight his professional credibility. These roles and participations collectively showcase a career marked by excellence, leadership, and sustained contributions to both research and education in mechanical engineering.

Research Skill🔬

Prof. Koch demonstrates a comprehensive set of research skills across simulation, design, modeling, and experimental validation. He excels in integrating real 3D geometry data into simulations, thereby enhancing the accuracy of engineering analyses. His ability to combine parametric CAD modeling with finite element methods (FEM) enables more realistic structural assessments. He is skilled in developing cyber-physical systems, utilizing augmented reality for robot programming, and implementing motion capture technologies for intuitive control interfaces. Prof. Koch also possesses strong capabilities in knowledge-based simulation frameworks, making product development processes more efficient and intelligent. His certification in Six Sigma demonstrates his proficiency in process optimization and quality control, and his work often bridges the gap between academic theories and industrial applications. Proficient in engineering software like PTC CREO Parametric, he brings both depth and versatility to his projects. These research skills collectively establish his expertise in designing cutting-edge, applied engineering solutions.

Conclusion💡

Prof. Dr.-Ing. Michael Koch is highly suitable for the Best Researcher Award based on his:

  • Depth of domain knowledge,

  • Multidisciplinary research footprint,

  • Educational leadership,

  • Technical innovations in engineering design, simulation, and additive manufacturing.

His work bridges academic rigor and industry relevance, and he has made consistent, innovative contributions to mechanical engineering and product development.

With additional international collaboration and visibility in global rankings or research grants, he would further elevate his candidacy for top-tier global research honors.

Publications Top Noted✍

  1. Title: Expression and functions of transmembrane mucin MUC13 in ovarian cancer
    Authors: SC Chauhan, K Vannatta, MC Ebeling, N Vinayek, A Watanabe, MD Koch, et al.
    Year: 2009
    Citations: 149

  2. Title: MUC13 mucin augments pancreatic tumorigenesis
    Authors: SC Chauhan, MC Ebeling, DM Maher, MD Koch, A Watanabe, et al.
    Year: 2012
    Citations: 110

  3. Title: Identification of an essential Caulobacter crescentus gene encoding a member of the Obg family of GTP-binding proteins
    Authors: J Maddock, A Bhatt, M Koch, J Skidmore
    Year: 1997
    Citations: 71

  4. Title: Increased expression and aberrant localization of mucin 13 in metastatic colon cancer
    Authors: BK Gupta, DM Maher, MC Ebeling, V Sundram, MD Koch, DW Lynch, et al.
    Year: 2012
    Citations: 54

  5. Title: Combined staining of TAG-72, MUC1, and CA125 improves labeling sensitivity in ovarian cancer
    Authors: SC Chauhan, N Vinayek, DM Maher, MC Bell, KA Dunham, MD Koch, et al.
    Year: 2007
    Citations: 42

  6. Title: Design for X
    Authors: H Meerkamm, M Koch
    Year: 2005
    Citations: 33

  7. Title: Intuitive welding robot programming via motion capture and augmented reality
    Authors: F Mueller, C Deuerlein, M Koch
    Year: 2019
    Citations: 23

  8. Title: Innovative extruder concept for fast and efficient additive manufacturing
    Authors: R Löffler, M Koch
    Year: 2019
    Citations: 20

  9. Title: Integrating optical 3D measurement techniques in pipe bending: a model-based approach
    Authors: S Katona, M Lušić, M Koch, S Wartzack
    Year: 2016
    Citations: 19

  10. Title: The neuro-linguistic programming treatment approach
    Authors: C Zastrow, V Dotson, M Koch
    Year: 1987
    Citations: 16

  11. Title: Cyber-physical-system for representing a robot end effector
    Authors: F Müller, C Deuerlein, M Koch
    Year: 2021
    Citations: 15

  12. Title: Trace component removal in CO2 removal processes by means of a semipermeable membrane
    Authors: JK Bockman, M Koch
    Year: 2016 (US Patent)
    Citations: 15

  13. Title: Robot guided computed tomography—production monitoring in automotive industry 4.0
    Authors: A Ziertmann, P Jahnke, S Kerscher, M Koch, W Holub
    Year: 2020
    Citations: 12

  14. Title: Microstructure of the HMX‐Based PBX KS32 after Mechanical Loading
    Authors: M Herrmann, U Förter‐Barth, MA Bohn, H Krause, M Koch, W Arnold
    Year: 2015
    Citations: 12

  15. Title: PM10 source apportionment at three urban background sites in the western Ruhr-area, Germany
    Authors: TAJ Kuhlbusch, U Quass, M Koch, H Fissan, P Bruckmann, U Pfeffer
    Year: 2004
    Citations: 12

  16. Title: Method and system for reducing energy requirements of a CO2 capture system
    Authors: JP Naumovitz, M Koch
    Year: 2014 (US Patent)
    Citations: 10

  17. Title: Process gas treatment system
    Authors: PU Koss, M Koch, JP Naumovitz
    Year: 2014 (US Patent)
    Citations: 10

  18. Title: Reverse Engineering – Prozess, Technologien und Anwendungsfälle
    Authors: S Katona, M Koch, S Wartzack
    Year: 2014
    Citations: 9

  19. Title: POEAM – a method for the part orientation evaluation for additive manufacturing
    Authors: S Jung, S Peetz, M Koch
    Year: 2019
    Citations: 7

  20. Title: Long-term primary culture of a clear cell ovarian carcinoma reveals an epithelial–mesenchymal cooperative interaction
    Authors: AA Goyeneche, M Koch, MC Bell, CM Telleria
    Year: 2015
    Citations: 7

Dr. Marco Antonio Narvaez Tamayo | Autonomous Systems | International Visionary in Computer Vision Award

Dr. Marco Antonio Narvaez Tamayo, Autonomous Systems, International Visionary in Computer Vision Award

Doctorate at Fedelat is official continental chapter of IASP, Bolivia

Professional Profile

🌟 Summary:

Dr. Marco Antonio Narváez Tamayo is a distinguished specialist in Pain Medicine and Anesthesiology with extensive international training and leadership roles across Latin America. He currently serves as President of FEDELAT (Federación Latinoamericana de Asociaciones para el Estudio del Dolor) and has held significant positions in ALMID (Academia Latinoamericana de Médicos Intervencionistas en Dolor) and ABD (Asociación Boliviana del Dolor).

🎓 Education:

  • Fellowship in Pain Medicine, Moffit Cancer Center, Tampa, Florida, USA
  • Clinical and Interventional Pain Medicine, Hospital Ramón y Cajal, Madrid, Spain
  • Interventional Pain Management, Montreal General Hospital, Montreal, Canada
  • Master’s in Pain Treatment, University of Salamanca, Spain
  • Master’s in Anesthesia and Ultrasound-Guided Analgesia, University of Salamanca, Spain

💼 Professional Experience

  • Director, CLÍNICA del DOLOR, La Paz, Bolivia
  • Teaching positions at various institutions including Universidad de Salamanca, Spain, and Hospital Obrero N.º 1 – Hospital Materno Infantil, Bolivia
  • Coordinator for Hispanoamérica, Master’s Programs in Pain Treatment and Ultrasound-Guided Anesthesia, University of Salamanca, Spain
  • Extensive involvement in pain management education and training across Latin America

🔬 Research Interests:

Dr. Narváez Tamayo’s research interests include advanced pain management techniques, ultrasound-guided procedures, and improving outcomes in pain medicine through interdisciplinary approaches.

📖 Publications Top Noted:

Paper Title: Map of pain education in Latin America: current state and perspectives
  • Authors: Liñeiro, M.G., Garcia, J.B.S., Narváez Tamayo, M.A., Molina-Muñiz, H.G., Del Villar, B.M.
  • Journal: Pain Management
  • Volume: 13
  • Issue: 3
  • Pages: 193–199
  • Year: 2023
Paper Title: Spinal erector plane block as a neuropathic pain management in post-burned pediatric patient | Bloqueo del plano del erector espinal como manejo de dolor neuropático en paciente pediátrico postquemado
  • Authors: Vela Izquierdo, C.E., Narváez Tamayo, M.A., Renilla Carranza, E.S., Fiestas Bancayan, M., Rodríguez Calderón, M.
  • Journal: Revista de la Sociedad Española del Dolor
  • Volume: 27
  • Issue: 2
  • Pages: 127–132
  • Year: 2020
  • Citations: 2
Paper Title: Pain control in patient with kidney disease | Paciente con enfermedad renal: Manejo del dolor
  • Authors: Narváez Tamayo, M.A., Castañeda De La Lanza, C., O Shea Cuevas, G.J., Lozano Herrera, J., Castañeda Martínez, C.
  • Journal: Gaceta Mexicana de Oncología
  • Volume: 14
  • Issue: 6
  • Pages: 335–341
  • Year: 2015
  • Citations: 2
Paper Title: Quality of life and symptom control in the cancer patient | Calidad de vida y control de síntomas en el paciente oncológico
  • Authors: Castañeda De La Lanza, C., O’Shea C., G.J., Narváez Tamayo, M.A., Castañeda Peña, G., Castañeda De La Lanza, J.J.
  • Journal: Gaceta Mexicana de Oncología
  • Volume: 14
  • Issue: 3
  • Pages: 150–156
  • Year: 2015
  • Citations: 3