جست‌وجوی استاد و پژوهشگر

Laura K. Jonesمشاهده پروفایل

استادیار مهمان

• Medical Anthropology
• Surgical Team Dynamics
• Healthcare Communication
• +۵ مورد دیگر

Laura K. Jones is a Visiting Assistant Professor in the Department of Anthropology at Emory University. Her academic background includes a PhD in Anthropology from Rice University (2010), postdoctoral fellowships at the Yerkes National Primate Center and Emory University School of Medicine, and additional training at institutions like Tulane University and the University of Texas Health Science Center. Her research focuses on surgical team dynamics, healthcare communication, and the application of anthropological methods to medical settings. Notable work includes studies on operating room behavior, telehealth innovation, and the impact of hierarchy in surgical environments. Dr. Jones has received prestigious awards such as the 2010 Graduate Student Paper Prize from the Society for Medical Anthropology and the Josephine Louise Newcomb Fellowship. She has secured research grants totaling over $174,000, including projects on interprofessional communication in operating rooms and mitigating medical errors through team-based approaches. Her interdisciplinary work bridges anthropology, bioinformatics, and clinical practice, with a particular interest in wearable technology and mindfulness integration in healthcare. Professional activities include roles as Principal Investigator at Kaiser Permanente and BioSelf Technology, as well as teaching and mentoring at Emory and Rice Universities. She has presented over 20 scholarly talks and posters at conferences like the American Anthropological Association meetings, focusing on topics ranging from ethological methods in surgery to medical error prevention strategies.

• Signal Processing
• Machine Learning
• Acoustics
• +۷ مورد دیگر

Luis Antonio Azpicueta Ruiz is an Associate Professor in the Department of Signal Theory and Communications at Carlos III University of Madrid. He leads research in the Signal Processing and Learning Group (GTSA) and Machine Learning for Data Science (ML4DS) group, focusing on interdisciplinary applications spanning acoustics, telecommunications, and machine learning. Research Interests: His work bridges signal processing theory with practical applications in environmental acoustics, adaptive filtering systems, and machine learning. Key research themes include: Advanced adaptive filtering architectures for nonlinear systems Distributed estimation in sensor networks Acoustic echo cancellation and room equalization Psychoacoustic evaluation methods Machine learning applications in noise monitoring and sound analysis Research Projects: Principal investigator for multiple funded projects including: Diagnóstico del ruido de chorro en aeronaves (AEI, 2022-2025) LearnINg FLow and Noise Dynamics via AI (COMUNIDAD DE MADRID, 2024-2026) BODYinTRANSIT - Sensory-driven Body Transformation (EUROPEAN COMMISSION, 2022-2026) Aprendizaje Automático para análisis Big Data (MINISTERIO DE ECONOMÍA, 2018-2021)

Ciriaco D'Ambrosioمشاهده پروفایل

پژوهشگر

• Combinatorial Optimization
• Heuristics
• Metaheuristics
• +۴ مورد دیگر

Ciriaco D'Ambrosio is a Research Fellow at the Department of Mathematics, University of Salerno, specializing in combinatorial optimization and its applications to wireless sensor networks. He teaches courses in operations research and maintains regular reception hours for students on Tuesdays (3:00-5:00 PM) and Wednesdays (4:00-5:00 PM), conducted both in-person and via Microsoft Teams. Education: PhD in Computer Science, University of Salerno (2015) - Thesis: models and algorithms for coverage in Wireless Sensor Network Laurea cum laude in Computer Science, University of Salerno (2011) Research Focus: D'Ambrosio specializes in combinatorial optimization, developing heuristics, metaheuristics, and math-heuristics for mixed integer linear programming problems. His work addresses challenging optimization problems in wireless sensor networks, particularly network lifetime maximization under coverage, connectivity, and interference constraints. His research bridges theoretical computer science with practical applications in sensor network design, seismic monitoring systems, and resource allocation problems. His methodology often combines exact approaches with sophisticated heuristic techniques to solve computationally difficult problems. Publication Trends: Analysis of D'Ambrosio's publications (2017-2025) reveals a progression from foundational work on sensor network lifetime problems toward increasingly sophisticated algorithmic approaches for combinatorial optimization. His recent work shows expansion into seismic monitoring applications while maintaining strong focus on knapsack problem variants and network optimization. His publications appear in high-quality journals including Soft Computing, Computers & Operations Research, and Networks, demonstrating both theoretical rigor and practical relevance of his research. Professional Activities: Member of the Italian Operations Research Society (AIRO) Associate Editor for Soft Computing, A Fusion of Foundations, Methodologies and Applications Active collaborator with researchers including Andrea Raiconi, Raffaele Cerulli, and Francesco Carrabs Research Infrastructure: D'Ambrosio works within the Department of Mathematics at University of Salerno's Fisciano Campus (Building F2, Room 040). His research contributes to the university's growing expertise in computational optimization and has practical applications in environmental monitoring systems like SEISMONOISY.

Kirill Djebkoمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Optimization Algorithms
• +۴ مورد دیگر

Kirill Djebko is a researcher at the Chair of Computer Science VI - Artificial Intelligence and Knowledge Systems within the Institute of Computer Science, Faculty of Mathematics and Computer Science at the University of Würzburg . His work spans AI-based optimization systems , autonomous spacecraft operations , and deep reinforcement learning applications. Doctorate completed in 2020 Active in research since 2015 Key projects: KINERGY (heating system optimization), VeriKI (AI verification for space), LeLaR (AI attitude control for nanosatellites) Research focuses on metaheuristics , genetic algorithms , regression algorithms , and deep reinforcement learning for practical applications. His work integrates digital twin modeling , decision support systems , and AI robustness in industrial and space contexts. Recent publications (2024-2016) analyze heating system optimization , spacecraft fault detection , and autonomous nanosatellite operations . These studies emphasize sim-to-real-world transfer , data-driven calibration , and AI quality assurance in complex environments. Current affiliations include the Center for Artificial Intelligence and Data Science (CAIDAS) . Contact details: Email - kirill.djebko@uni-wuerzburg.de | Phone +49 931 31-86405 | Room 03.010, Emil-Fischer-Straße 50, Würzburg.

Dorota Chwiedukمشاهده پروفایل

استاد

• Solar Energy
• Renewable Energy Systems
• Building Energy Efficiency
• +۱۱ مورد دیگر

Professor Dorota Chwieduk is a distinguished faculty member at the Division of Refrigeration and Energy in Buildings within the Faculty of Power and Aeronautical Engineering at Warsaw University of Technology. She serves as Deputy Director of the Institute of Heating Engineering and heads the Post Diploma Study program on Energy Efficient Buildings, Energy Characteristics of Buildings, Energy Auditing and Thermal Refurbishment. With a career spanning decades, Professor Chwieduk has established herself as a leading expert in solar energy applications and building energy efficiency. Her research focuses on unconventional energy conversion methods, solar technologies, heat transfer in buildings, renewable energy systems integration, thermal energy storage (including phase change materials), and energy performance assessment. She has published extensively in these fields, with numerous high-impact journal articles and book contributions. Solar Energy in Buildings: Thermal Balance for Efficient Heating and Cooling (Elsevier, 2014) Multiple publications on PV/T systems, building-integrated solar technologies, and thermal energy storage Research on high latitude building design and energy performance Professor Chwieduk's work demonstrates consistent focus on practical applications of renewable energy technologies in building systems, with particular attention to climate-specific design considerations and energy optimization. Her research bridges theoretical modeling with practical implementation, contributing significantly to advancing sustainable building technologies. Scientific Awards: Gold Medal from President of Republic of Poland for Long Service for the Country (2013) Best Scientific Achievements award from Rector of Warsaw University of Technology (2012) Pioneer of Renewable Energy award by World Renewable Energy Network (2008) Promoter of Renewable Energy award by Clean Energy magazine (2006) Throughout her career, Professor Chwieduk has actively contributed to national and international energy policy development, serving on numerous expert committees and leading significant research projects focused on renewable energy integration and building energy efficiency. Her work has influenced both academic research and practical implementation of sustainable building technologies in Poland and internationally.

Arish Sateesanمشاهده پروفایل

استاد

• Computer Engineering
• Network Security
• Hardware Acceleration
• +۳ مورد دیگر

Dr. Arish Sateesan serves as Professor and Chair of the Institute for Networked Systems at RWTH Aachen University's Faculty of Electrical Engineering and Information Technology, located at Kackertstrasse 9 in Aachen, Germany. His research group operates from House C (Room C046) with direct contact via asa@inets.rwth-aachen.de. His primary research domains center on hardware-accelerated network security solutions, specializing in FPGA implementations for high-speed networking. Key focus areas include: Real-time network monitoring and intrusion detection systems Hardware-optimized cryptographic and non-cryptographic algorithms Machine learning integration for wireless beamforming and LiDAR processing Ultra-high-speed flow measurement architectures His work bridges theoretical computer science with practical hardware constraints, emphasizing throughput optimization for security-critical applications. Analysis of his 15 most recent publications (2021-2025) reveals a pronounced shift toward hardware-software co-design for next-generation networks. The research trajectory shows increasing integration of quantized neural networks with traditional security primitives, particularly for mm-Wave and 5G/6G applications. A consistent theme across all publications is the prioritization of hardware friendliness through algorithmic simplification and architectural innovation. As Institute Chair, he leads a research ecosystem focused on developing deployable security solutions for modern network infrastructures, with current projects targeting autonomous vehicle communication systems and infrastructure protection against distributed denial-of-service attacks.

Mark E. Warnerمشاهده پروفایل

استاد

• Marine Biology
• Coral Physiology
• Phytoplankton Ecophysiology
• +۳ مورد دیگر

Mark E. Warner is a full Professor in the School of Marine Science & Policy at the University of Delaware’s College of Earth, Ocean & Environment . Based at the Lewes campus , he leads research bridging coral physiology, phytoplankton ecology, and climate-change impacts on marine symbioses. Education Ph.D., Ecology, University of Georgia, 1998 East-West Marine Biology Program, Northeastern University, 1991 B.S., Zoology, University of Georgia, 1992 Research Interests Professor Warner’s work centers on physiological ecology of phytoplankton and reef-building corals , with particular emphasis on algal–invertebrate symbioses . His laboratory investigates how temperature stress, ocean acidification, and nutrient regimes modulate the fitness of both Symbiodiniaceae (zooxanthellae) and their cnidarian hosts. A major thrust is understanding thermotolerance mechanisms that underpin coral resilience in a warming ocean, employing techniques from bio-optical fluorometry to stable-isotope probing . Additional foci include the ecology of harmful algal blooms , where he examines how dinoflagellate growth, toxicity, and fatty-acid profiles respond to multifactorial environmental change, and the development of low-cost, field-deployable instrumentation (e.g., CBASS) for standardized coral-stress diagnostics. Publication Trends Across the most recent 15 publications (2023-2025), the work spans coral bleaching physiology, symbiont diversity, thermal tolerance, and technology innovation . Themes include zooxanthellae–host fidelity , nutrient-transfer efficiency under heat stress , and portable bio-optical tools for reef monitoring , reflecting a trajectory from cellular mechanisms to ecosystem-scale applications. Scientific Awards No awards are explicitly listed in the provided text. Advising & Grants No specific student names or grant numbers were found in the supplied materials. Laboratory & Teams Professor Warner directs an active research group within the College of Earth, Ocean & Environment at the University of Delaware’s Lewes campus , housed in Cannon Laboratory (Room 232). The lab collaborates closely with the marine operations and instrumentation teams to advance coral-reef science and phytoplankton ecology.

• Chemical reactor engineering

Prof. R. (Rajamani) Krishna serves as a Professor at the University of Amsterdam within the Faculty of Science and Van 't Hoff Institute for Molecular Sciences. His primary academic affiliation centers on advancing chemical engineering research and education at this institution. His research specialization in Chemical reactor engineering focuses on the design, optimization, and analysis of chemical reactors for industrial applications. This field encompasses fluid dynamics, reaction kinetics, and process intensification to develop efficient and sustainable chemical production systems with relevance to energy, pharmaceuticals, and materials science. Dr. Krishna maintains active academic operations from his office at Science Park 904 (Room C2.218) in Amsterdam, with professional correspondence managed through R.Krishna@uva.nl and direct telephone access at +31 (0)20 525 5054.

Ali Nazarpourمشاهده پروفایل

استادیار

• Operations and Supply Chain Management
• Artificial Intelligence
• Mass Customization
• +۴ مورد دیگر

Dr. Ali Nazarpour is an Assistant Professor in Management at the School of Business, Maynooth University. He holds a PhD in Operations and Supply Chain Management from University College Dublin’s Smurfit School of Business, along with a BSc in Industrial Engineering and an MSc in Business Administration from Iran University of Science and Technology. Prior to his academic career, he spent nine years in industry roles, including Sales Supervisor, Marketing and Sales Planning Chief, and Inventory Management Project Manager in the automotive sector, alongside teaching and research activities. His work bridges industry experience with academic rigor, focusing on supply chain optimization, mass customization strategies, and AI integration in business processes. Education: PhD in Operations and Supply Chain Management (Smurfit School of Business, UCD) MSc in Business Administration (Iran University of Science and Technology) BSc in Industrial Engineering (Iran University of Science and Technology) Research Interests: Artificial Intelligence applications in supply chain and logistics Mass customization feasibility across industries and countries Third-party logistics selection methodologies Project management and risk mitigation strategies Global logistics frameworks Industry 4.0 technologies for operational efficiency His publications and conference contributions between 2014 and 2021 highlight trends in leveraging AI for supply chain decision-making, analyzing mass customization challenges, and exploring cross-country operational dynamics. Despite no explicit scientific awards listed, his active participation in conferences like INFORMS, POMS, and EurOMA underscores his academic engagement. In advising and teaching, he focuses on Contemporary Issues in Management, Operations and Supply Chain Management metrics, and Project Risk Management. His industry experience enriches classroom discussions and research projects. He is based in the TSI Building (Room 253) and reachable via ali.nazarpour@mu.ie or phone (01) 474 7516.

• 3D Light Measurement
• Optical Shape
• Structured Light
• +۷ مورد دیگر

Robert Sitnik is a Professor and Dean of the Faculty of Mechatronics at Warsaw University of Technology, where he is affiliated with The Institute of Micromechanics and Photonics. He earned his Doctorate in 2002 and has established himself as a leading researcher in 3D optical measurement techniques and applications. His research focuses on 3D light measurement, optical shape analysis, structured light techniques, and 3D data processing with applications spanning cultural heritage documentation and medical imaging. As the leader of the 3D/4D Optical Surface Measurement Team, he has pioneered innovative approaches to surface measurement and documentation. His work demonstrates strong interdisciplinary connections between mechanical engineering, computer vision, and practical applications in both cultural preservation and healthcare. His research has led to significant advancements in 3D scanning technologies, particularly for human body analysis and cultural heritage conservation. His publications reveal a consistent research trajectory focused on improving accuracy, efficiency, and applicability of 3D measurement systems. His scientific impact is evidenced by 159 publications, an h-index of 18 in Scopus and 17 in Web of Science, and 103 promoted theses. His research has been supported by 22 projects, resulting in 1 patent and substantial contributions to both academic knowledge and practical applications. As an academic leader, he has supervised numerous students and researchers, contributing significantly to the development of expertise in optical measurement technologies. His work bridges theoretical research with real-world applications in medical diagnostics, cultural heritage preservation, and industrial measurement systems.

Vinkle Srivastavمشاهده پروفایل

پژوهشگر

• Surgical Data Science
• 3D Medical Image Analysis
• Multi-modal Pre-training
• +۷ مورد دیگر

Vinkle Srivastav is a Research Scientist (Chargé de recherche R&D) at the CAMMA group, a collaborative research team between IHU Strasbourg and the University of Strasbourg, where he focuses on advancing surgical data science through novel computer vision and machine learning approaches. His work bridges the gap between clinical practice and artificial intelligence, developing methods for surgical video analysis, 3D medical imaging, and surgical workflow understanding. Education PhD in Computer Science (2018-2021) from University of Strasbourg, France. Thesis: "Unsupervised Domain Adaptation Approaches for Person Localization in the Operating Rooms." Master of Science in Computer Science (2014-2017) from Indian Institute of Technology, Delhi, India. Thesis: "Computerized evaluation of neurosurgery skills using image processing and computer vision techniques." Bachelor of Technology in Electronics and Communication (2007-2011) from Punjab Technical University, Jalandhar, India. Research Interests Vinkle's research spans surgical data science, with particular focus on multi-modal learning approaches for surgical computer vision. His work addresses fundamental challenges in medical AI including domain adaptation, self-supervised learning, and privacy preservation in clinical environments. He develops methods for 3D medical image analysis, multi-view human pose estimation in operating rooms, and surgical activity recognition. His recent work emphasizes multi-modal pretraining frameworks that leverage both visual and textual information to improve surgical workflow understanding. He also investigates scientific simulation techniques, particularly for therapeutic ultrasound applications, where physics-aware deep learning models can accelerate computational processes while maintaining accuracy. Publication Trends Vinkle's recent publications demonstrate a strong trajectory toward multi-modal surgical AI systems that integrate vision, language, and physics-based modeling. His work increasingly focuses on few-shot and zero-shot adaptation techniques to address the data scarcity problem in surgical AI. The publications reveal a progression from basic pose estimation to holistic surgical scene understanding, incorporating team communication analysis and surgical safety protocols. Scientific Awards IPCAI 2024 Best paper award (co-author) IPCAI 2019 Runner-up award in the bench-to-bedside category (co-author) Joint winner for the best paper award in the machine learning for CAI track, IPCAI 2025 Advising and Grants Vinkle actively mentors multiple PhD students and research interns at various levels, supervising thesis work on topics including large-scale multi-modality learning, holistic surgical scene analysis, and self-supervised video representation learning. He serves as Co-PI on two ITI-HealthTech projects: one focused on multi-modality learning for 3D medical imaging (2023), and another on physics-aware deep-learning approaches for therapeutic ultrasound simulation (2024). Laboratories and Teams Vinkle is a key member of the CAMMA research group at IHU Strasbourg, a collaborative team focused on computer-assisted medical modeling and analytics. He co-organizes the Surgical Data Science Summer School, an interdisciplinary program that brings together clinicians and computer scientists to develop AI-driven solutions with clinical impact. His work involves close collaboration with surgical teams at University Hospitals of Strasbourg and international partners including Johns Hopkins University and Technical University of Munich.

Karin Leistnerمشاهده پروفایل

پژوهشگر

• Magneto-ionic Materials
• Nanoelectrodeposition
• Magnetic Nanostructures
• +۵ مورد دیگر

Dr. Karin Leistner serves as Group Leader for Nanoelectrodeposition and Magneto-ionic Materials at the Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden). Her research focuses on the intersection of electrochemistry and magnetism, developing energy-efficient methods for voltage-controlled magnetic nanostructures. Her primary research interests include Magneto-ionic Materials , Nanoelectrodeposition , Magnetic Nanostructures , and Voltage-Controlled Magnetism . Through electrochemical approaches, she pioneers methods to manipulate magnetic properties at the nanoscale without requiring external magnetic fields, enabling applications in low-power spintronics and memory devices. Her work emphasizes redox transformations, electrolytic gating, and interfacial engineering to achieve programmable magnetism in hybrid metal/oxide systems. Analysis of her publication trends reveals consistent innovation in magneto-ionic effects (2021-2025), with increasing focus on microscale patterning (2023-2025) and energy-efficient device applications . Her research spans fundamental electrochemistry (e.g., self-terminated electrodeposition) to applied nanotechnology (e.g., magnetoresistance switching aerogels), demonstrating strong translational potential. Recent work integrates advanced characterization techniques like Kerr microscopy with electrochemical control for precise magnetic manipulation. Dr. Leistner has delivered over 20 invited talks at international institutions including TU Chemnitz, Forschungszentrum Jülich, and Simon Fraser University, highlighting her recognition as a leading expert in electrochemically controlled magnetism. Her collaborative research spans multiple continents, with publications co-authored by teams in Germany, USA, Mexico, Austria, and Slovenia. She leads research activities within IFW Dresden's nanoelectrodeposition laboratory, utilizing specialized electrochemical cells coupled with in situ magnetic characterization. Her group maintains strong collaborations with transmission electron microscopy facilities for real-time observation of electrochemical deposition processes, as demonstrated in joint work with the Wigner Research Centre for Physics.

• Aerospace Engineering
• Aircraft Design
• Sustainable Aviation
• +۲ مورد دیگر

Kristina Mazur, M.Sc., is a Lecturer at the Chair of Aircraft Design, Technical University of Munich (TUM), working under Prof. Dr.-Ing. Mirko Hornung. Her research focuses on integrating sustainability metrics into aircraft design through life cycle assessment and hydrogen propulsion systems. Key Research Areas: Aircraft Design Life Cycle Assessment Hydrogen Powertrain Development Sustainable Aviation Technologies Notable Projects: UNICADO (Unified Conceptual Aircraft Design Framework) Kristina's recent publications emphasize environmental impact assessment methods for future aircraft, comparative analysis of hydrogen and biofuel powertrains, and operational cost modeling. Her work bridges conceptual aircraft design with sustainability considerations, particularly through systems-level life cycle analysis. She collaborates with researchers like Mischa Saleh and Mirko Hornung. The Chair of Aircraft Design is located at Boltzmannstr. 15, Garching b. München, Germany, with her contact information including room 5506.03.632 and phone +49 (89) 289-16346.

• Mixed-Integer Optimization
• Combinatorial Optimization
• Discrete Mathematics
• +۳ مورد دیگر

Timm Oertel is a Professor in the Department of Data Science at Friedrich Alexander University Erlangen-Nuremberg (FAU), holding the Chair of Analytics & Mixed-Integer Optimization. His office is located in Room 03.344 at Cauerstraße 11, Erlangen, and he can be contacted via email at timm.oertel@fau.de or phone at +49 9131 85-67313. His research focuses on mixed-integer optimization, combinatorial optimization, and discrete mathematics, with significant contributions to sparse solutions in lattices and semigroups, integer Carathéodory rank, knapsack polyhedra, and parametric integer optimization. His work bridges theoretical computer science, operations research, and discrete geometry, emphasizing structural properties of integer solutions and algorithmic efficiency. Professor Oertel's publication record (2013-2025) reveals consistent trends in theoretical integer programming, with recent work (2020-2025) concentrating on sparsity patterns, approximation in algebraic structures, and complexity bounds. He frequently collaborates with leading researchers including Iskander Aliev, Robert Weismantel, and Joseph Paat, publishing in top venues like Mathematical Programming and SIAM Journal on Optimization. His research demonstrates deep connections between combinatorial geometry and optimization theory.

• Combinatorial Optimization
• Operations Research
• Stochastic Programming
• +۵ مورد دیگر

Hanyu Gu is a Senior Lecturer in the School of Mathematical and Physical Sciences at the University of Technology Sydney (UTS), part of the Faculty of Science. He holds a PhD in Power Engineering and Automation from Shanghai Jiao Tong University (1999) and has extensive industry experience in telecommunications, airline optimization, and mining. His research focuses on combinatorial optimization, decomposition methods, stochastic programming, and machine learning applications. Notable awards include second place in the 2020 ROADEF competition. He collaborates with institutions like the UTS Transportation Research Centre and has contributed to projects such as optimisation engines for airline management and underground mining algorithms. Current research explores hybrid algorithms, Bayesian optimisation, and scheduling under uncertainty. Education: Bachelor in Industrial Automation, Shanghai Jiao Tong University (1994) Master in Control Theory and Application, Shanghai Jiao Tong University (1997) PhD in Power Engineering and Automation, Shanghai Jiao Tong University (1999) Industry Experience: ZTE (1999–2001): Senior Wireless Communication Engineer CTI, Melbourne (2007–2011): Airline Management Optimisation Researcher NICTA (2011–2013): Underground Mining Optimisation Researcher Grants: ARC Linkage Project LP0883855 (2008–2012): Developed optimisation tools for transportation crewing, valued at $840,000. Research interests span decomposition methods for large-scale problems (e.g., airline scheduling), stochastic programming for resource sharing, and hybridisation of mathematical programming with constraint programming. Recent work includes Bayesian optimisation for knapsack problems and relax-and-solve algorithms for project scheduling. His articles frequently address optimisation in logistics, healthcare, and transportation, emphasizing practical industry applications and algorithmic innovation. Awards: Second place in the ROADEF 2020 competition for maintenance planning solutions. Advising & Grants: Supervises Masters and PhD students in operations research and optimisation. Collaborates with Ausgrid, UGL, and ANC on optimisation projects (e.g., employee training timetabling, logistics). Active in the Optimisation Group of UTS Transportation Research Centre, he bridges academic research with real-world challenges in scheduling, logistics, and resource management. Ongoing efforts include advancing metaheuristics and integrating machine learning with traditional optimisation techniques.