Prof. Achim Lilienthal | LiDAR Perception | Research Excellence Award

Prof. Achim Lilienthal | LiDAR Perception | Research Excellence Award 

Prof. Achim Lilienthal | LiDAR Perception | Technical University of Munich | Germany

Prof. Dr. Achim Josef Lilienthal earned his Ph.D. in Computer Science at the University of Tübingen (summa cum laude), following a diploma in Physics from the University of Konstanz. Over his distinguished career, Achim Josef Lilienthal has held leading academic and research-oriented roles across Europe and beyond, including his current appointment as Full Professor (W3), Chair of Perception for Intelligent Systems at the Technical University of Munich (TUM), and Deputy Director at the Munich Institute of Robotics and Machine Intelligence (MIRMI). He previously served as full professor at Örebro University, founding and directing the Mobile Robotics & Olfaction Lab, and has been a visiting professor at institutions such as Cornell University, as well as a consultant for industry including Bosch and robotics startups. His research interests span mobile robot olfaction (gas distribution mapping and gas source localization), 3D perception and SLAM (LiDAR/radar mapping, sensor fusion, localization), human–robot interaction (intention recognition, human-aware navigation), and eye-tracking–based AI systems for human–robot interaction, driver monitoring, and safety applications. He is skilled in robotics, sensor fusion, 3D mapping, machine learning, perception algorithms, gas-sensing robotics, human-robot interface design, and systems integration enabling development of autonomous intelligent systems capable of robust perception in complex, dynamic environments. Through a prolific publication record of over 300 peer-reviewed papers, supervision of 50+ PhD students, leadership of major EU research projects and startups, and securing substantial research funding, Achim Josef Lilienthal has made foundational contributions to the robotics and intelligent systems community  particularly gas-sensing robotics, safe human-machine interaction, and autonomous perception.

Professional Profiles: ORCID | Google Scholar | Scopus

Selected publications 

  • Lilienthal, A. J., & Duckett, T. (2007). Scan registration for autonomous mining vehicles using 3D-NDT. Journal of Field Robotics, 24(10), 803–827. (Citations: 951)

  • Triebel, R., Arras, K., Alami, R., Beyer, L., Breuers, S., Chatila, R., Chetouani, M., … & Lilienthal, A. J. (2016). Spencer: A socially aware service robot for passenger guidance and help in busy airports. Field and Service Robotics: Results of the 10th International Conference. (Citations: 364)

  • Magnusson, M., Nüchter, A., Lorken, C., & Lilienthal, A. J. (2009). Evaluation of 3D registration reliability and speed – A comparison of ICP and NDT. IEEE International Conference on Robotics and Automation (ICRA). (Citations: 348)

  • Valgren, C., & Lilienthal, A. J. (2010). SIFT, SURF & Seasons: Appearance-based Long-term Localization in Outdoor Environments. Robotics and Autonomous Systems, 58(2), 149–156. (Citations: 314)

  • Stoyanov, T., Magnusson, M., Andreasson, H., & Lilienthal, A. J. (2012). Fast and Accurate Scan Registration through Minimization of the Distance between Compact 3D NDT Representations. International Journal of Robotics Research, 31(12), 1377–1393. (Citations: 303)

  • Neumann, P. P., Hernández Bennetts, V., & Lilienthal, A. J. (2013). Gas source localization with a micro-drone using bio-inspired and particle filter-based algorithms. Advanced Robotics, 27(9), 725–738. (Citations: 270)

  • Lilienthal, A. J., & Duckett, T. (2004). Building gas concentration gridmaps with a mobile robot. Robotics and Autonomous Systems, 48(1), 3–16. (Citations: 210)

Ms. Saleha Kamal | Pattern Recognition Awards | Best Researcher Award

Ms. Saleha Kamal | Pattern Recognition Awards | Best Researcher Award 

Ms. Saleha Kamal, Air University, Pakistan

Saleha Kamal is an accomplished AI and Computer Vision professional based in Rawalpindi, Pakistan, with expertise in image processing, silhouette detection, segmentation, and feature classification. She is currently pursuing an MS in Computer Science at Air University, Islamabad, Pakistan (2023-2025). Saleha’s research focuses on human interaction analysis and the development of advanced algorithms for computer vision tasks. Her work has been published in esteemed international conferences, including IEEE ICECT 2024 and IEEE ICET 2024, showcasing her innovative contributions to multi-feature descriptors and composite feature-based classifiers for human interaction recognition.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Saleha Kamal for the Best Researcher Award

Saleha Kamal demonstrates exceptional potential and achievements in AI, machine learning, and computer vision research, making her a compelling candidate for the Best Researcher Award. Her dedication to advancing knowledge in human interaction recognition, along with her technical and academic accomplishments, positions her as a rising star in the research community.

Education 🎓

  • MS in Computer Science (2023 – 2025)
    Air University, Islamabad, Pakistan

Work and Research Experience 💼

  • Research Experience
    • Co-authored research papers published in international conferences:
      • “Multi-Feature Descriptors for Human Interaction Recognition in Outdoor Environments” – IEEE ICECT, 2024.
      • “A Novel Human Interaction Recognition via Composite Features and Max Entropy Classifier” – IEEE ICET, 2024.

Achievements and Certifications 🏆

  • Published research in prestigious IEEE conferences.
  • Certifications:
    • Advanced Computer Vision with TensorFlow – Coursera, 2023.
    • Machine Learning Specialization – Coursera, 2023.

Publication Top Notes:

A Novel Human Interaction Recognition via Composite Features and Max Entropy Classifier

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