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Soroush Ahooye AtashinView profile

Research Fellow

• Motor Drives
• Design for Reliability
• Power Electronics
• +2 more

Soroush Ahooye Atashin serves as a Research Fellow at Aalborg University's Faculty of Engineering and Science, affiliated with AAU Energy under a Marie Curie Fellowship. His work centers on power electronic systems with emphasis on motor drive reliability, holding the principal investigator role for an active PhD project (2024-2026). Contact: saa@energy.aau.dk. His research investigates critical intersections of motor drive engineering and reliability design, particularly for high-power, high-speed applications. Key focus areas include thermal management of integrated systems, power density optimization, rotor dynamics, and failure mechanism analysis. This work bridges electrical and mechanical engineering domains to address paramount reliability challenges in modern drive systems where thermal effects and mechanical stresses dominate performance limitations. His 2024 ICEM publication establishes system-level reliability frameworks for integrated motor drives, reflecting industry trends toward holistic design methodologies that prioritize operational resilience alongside traditional performance metrics. This approach moves beyond component-level analysis to consider multi-physics interactions in real-world operating conditions. Scientific recognition includes: Marie Curie Fellowship As principal investigator for the €funded project "Integrated Design for Reliability of Motor Drives in High-Power High-Speed Machines" (2024-2026), he leads collaborative research with Prof. Frede Blaabjerg and senior supervisors. This PhD project demonstrates active grant management and research leadership, though specific advisee names remain undisclosed. His fingerprint analysis confirms deep expertise in motor drive reliability with secondary specializations in thermal effects and power density optimization.

Sabine KleinsteuberView profile

Researcher

• Microbial Ecology
• Anaerobic Biotechnology
• Wastewater Treatment
• +5 more

Dr. Sabine Kleinsteuber is a Senior Scientist and Head of the MicAS Group (Microbiology of Anaerobic Systems) at the Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany. With over 25 years of continuous service at UFZ since 1999, she leads research in microbial ecology of anaerobic environments, focusing on engineered systems such as anaerobic digesters and wastewater treatment plants for sustainable bioprocess development. Education: 1990: Diploma in Biology, Martin-Luther-University Halle-Wittenberg 1994: Dr. rer. nat., Martin-Luther-University Halle-Wittenberg, Faculty of Natural Sciences Dr. Kleinsteuber's research program centers on optimizing biotechnological processes based on complex microbial communities and harnessing the metabolic potential of anaerobic microbes within the circular economy framework. Her group combines anaerobic cultivation, lab-scale bioreactor operation, and molecular methods for community profiling with multi-omics approaches to explore metabolic functions in natural and engineered microbial consortia. This integrated methodology has positioned her as a leader in understanding microbial community dynamics in waste-to-value conversion processes. Analysis of her recent publications (2020-2025) reveals three dominant research trajectories: microbial chain elongation for medium-chain carboxylate production, syngas fermentation for carbon-efficient waste upcycling, and biodegradation of persistent micropollutants like acesulfame. These research areas demonstrate her commitment to developing sustainable biotechnological solutions that bridge environmental remediation with resource recovery, particularly through the lens of microbial community ecology and function. Dr. Kleinsteuber serves as Specialty Chief Editor for Frontiers in Microbiology (Section Microbial Physiology and Metabolism) and Associate Editor for Frontiers in Microbiology (Section Microbiotechnology). She also contributes to the Advisory Board of Energy, Sustainability and Society, reflecting her interdisciplinary impact across environmental science and engineering domains. As head of the MicAS Group, Dr. Kleinsteuber oversees a dynamic research program investigating the microbiology of anaerobic systems, with particular expertise in microbial community dynamics, metabolic interactions, and process optimization. Her leadership extends to collaborative projects across UFZ departments and international research networks, fostering innovation in sustainable bioprocess engineering and environmental biotechnology.

Anito JosephView profile

Associate Professor

• Operations Research
• Management Science
• Integer Programming
• +5 more

Anito Joseph is an Associate Professor in the Management Science department at the Miami Herbert Business School, University of Miami. With expertise spanning Operations Research, Management Science, and Decision Analysis, Dr. Joseph has made significant contributions to the fields of optimization, integer programming, and disaster recovery planning. Dr. Joseph's research focuses on applying mathematical and computational methods to solve complex decision-making problems. Key areas of interest include: Operations Research and Management Science methodologies Integer programming and optimization techniques Set partitioning problems and their applications Disaster recovery planning and business continuity Attribute discretization for decision tree induction Group decision-making using the Analytic Hierarchy Process Dr. Joseph's publication record demonstrates a consistent focus on developing mathematical models and computational approaches to address challenging real-world problems. The research shows a progression from foundational work in integer programming and set partitioning to applications in disaster recovery planning and decision analysis. A distinctive feature of this work is the emphasis on developing optimal solution approaches rather than heuristic methods, ensuring mathematical rigor in addressing complex problems. The research often bridges theoretical developments with practical applications, particularly in business and information systems contexts. Dr. Joseph has authored numerous peer-reviewed publications in prestigious journals including European Journal of Operational Research, Computers & Operations Research, and the Journal of the Operational Research Society. Collaborative work with researchers such as Kweku-Muata Osei-Bryson demonstrates an interdisciplinary approach to problem-solving. As an educator at the Miami Herbert Business School, Dr. Joseph contributes to the Management Science program, preparing students to apply advanced analytical methods to business challenges. While specific teaching interests aren't detailed in the available information, the research profile suggests expertise in quantitative methods, optimization, and decision analysis that likely informs classroom instruction.

Zhong ChenView profile

Assistant Professor

• Machine Learning
• Deep Learning
• Data Mining
• +7 more

Zhong Chen is an Assistant Professor in Data Science and Machine Learning at the School of Computing, Southern Illinois University (SIU), where he serves as Director of the Learning, Optimization, and Analysis from Data Lab (LOAD Lab). He holds a Ph.D. in Computer Science from Wuhan University of Technology and has previously worked as a Research Assistant Professor at the University of Kansas Medical Center and as a Computational Scientist at Xavier University of Louisiana. His research focuses on data-centric AI, Large Language Models, machine learning, deep learning, big data mining, online optimization, and anomaly detection, with applications in healthcare and medical physics. His work addresses fundamental challenges in handling streaming data with varying feature spaces, imbalanced classification problems, and developing interpretable AI systems for medical applications. Chen's recent publications demonstrate expertise in online learning frameworks, sparse representation techniques, and applications in healthcare domains including cancer treatment, patient outcome prediction, and medical imaging. His research combines theoretical innovation with practical applications in medical physics and bioinformatics. Excellence Reviewer Award of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'23) Outstanding Reviewer Award (top 10% of reviewers) of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'25) Chen serves as Associate Editor for Medical Physics and Editorial Member of Computational Biology and Bioinformatics. He is actively involved in the academic community as Program Committee member for major AI conferences including AAAI, IJCAI, KDD, and ECML-PKDD. He has advised numerous research projects and served on thesis committees at SIU, with a focus on developing the next generation of data scientists and AI researchers. His LOAD Lab at SIU focuses on foundational innovation in artificial intelligence and machine learning with emphasis on online optimization, machine learning techniques, and applications in big streaming data, bioinformatics, and medical physics.

• Epidemiology
• Public Health
• Network Science
• +4 more

Jessica Davis serves as a Research Assistant Professor in the Department of Public Health and Health Sciences at Northeastern University's Bouvé College of Health Sciences and is an active member of the MOBS Lab within the Network Science Institute. Her interdisciplinary work integrates network science methodologies with epidemic modeling to develop practical tools for public health policy and pandemic preparedness, with significant contributions during the COVID-19 pandemic. Dr. Davis earned her PhD in Network Science from Northeastern University, where her dissertation research examined cryptic transmission patterns and the efficacy of travel restrictions during the initial phases of the COVID-19 outbreak. This foundational work established her expertise in bridging theoretical network analysis with real-world public health applications. Her research program centers on two interconnected domains: Biological and Health Systems , which investigates biological interdependencies through network medicine, systems epidemiology, and public health infrastructure; and Complex Systems Forecasting , which develops network-based computational models for predicting epidemic trajectories and supporting evidence-based decision-making. These areas converge in her development of open-source tools like Epydemix and innovative surveillance frameworks using aircraft wastewater networks. Analysis of her 15 most recent publications (2021-2025) reveals consistent methodological evolution toward real-time modeling with explicit uncertainty quantification, increasing focus on multi-scale heterogeneity in disease transmission, and growing emphasis on practical implementation of forecasting systems. Her work demonstrates strong continuity in applying network science to epidemic dynamics while expanding into influenza surveillance, variant tracking, and vaccine impact assessment. No scientific awards or major honors are documented in the available materials, though her research has generated significant policy impact through presentations at venues like the Rhodes Policy Summit and collaborations with governmental agencies. Dr. Davis has secured substantial research funding including a Gates Foundation partnership investigating equitable global vaccine distribution strategies. While specific advisee relationships aren't publicly listed, she actively contributes to academic training through the MOBS Lab's hiring of computational statistics researchers and participation in the Network Science Student Research Symposium. The MOBS Lab, directed by Alessandro Vespignani and jointly affiliated with Physics, Health Sciences, and Computer Sciences departments, operates as a hub for computational epidemiology with physical locations in Boston, London, and Portland. Current lab initiatives focus on developing mathematical models for complex network systems with immediate applications to pandemic response, including the aircraft-based wastewater surveillance network featured in her 2025 Nature Medicine publication.

• Materials Engineering
• Nanotechnology
• Semiconductor Technology
• +5 more

Prof Francesca Iacopi is an Adjunct Professor at the Faculty of Engineering & Information Technology , University of Technology Sydney (UTS). She also holds an adjunct position at Purdue University, IN, USA, and serves as Imec Fellow & Director of the Indiana R&D Center for Imec USA. With a PhD in Electrical Engineering/Materials Science from Katholieke Universiteit Leuven (2004) and MSc in Physics (1996) from Sapienza University of Rome, she has 20+ years of leadership in semiconductor R&D and academic innovation. IEEE Fellow & Elected Board of Governors Member (2021-2026) Inaugural Editor-in-Chief, IEEE Transactions on Materials for Electron Devices Chief Investigator & Industry Liaison Chair, ARC Centre of Excellence for Transformative Meta-Optical Systems Research Focus spans graphene electronics , additive manufacturing for microwave components , and energy-efficient nanodevice design . Her work bridges semiconductor industry experience (GlobalFoundries, IMEC) with academic breakthroughs in epitaxial graphene integration , nanoscale thermal emitters , and brain-machine interface sensors . Key Trends in her recent publications: 3D-printed metasurfaces for wireless communication, Fermi level tuning in graphene devices, and high-temperature operando characterization of graphene growth mechanisms. These align with her broader vision of multi-functionality on silicon platforms. Scientific Recognition : Australian Research Council Future Fellowship (2012-2016) Gold Graduate Student Award (2003, Materials Research Society) Global Innovation Award (2014) IEEE Fellowship (2024) Leadership & Education : Founded UTS's Bachelor of Engineering (Hons) Major in Electronics. Serves on UTS Academic Board (2021) and leads the Integrated Nano Systems Lab . Her teaching spans semiconductor physics, nanofabrication, and IoT component design, emphasizing cross-domain integration of CMOS, photonics, and energy storage systems.

• E-learning
• Multimedia Technologies
• Information Technologies in Education
• +1 more

Assoc. Prof. Petya Asenova, PhD, is a permanent faculty member at New Bulgarian University's Bachelor's Faculty since 2001, holding the rank of Associate Professor in the Department of Informatics. She has served as Director of bachelor's programs in Informatics and Network Technologies, Director of the Master's program in IT Project Management, Head of the Department of Informatics, and Dean of the Bachelor's Faculty. Her academic credentials include: Bachelor's degree in Computational Mathematics from Plovdiv University "P. Hilendarski" Master's degree in Mathematics Education from Plovdiv University "P. Hilendarski" Master's degree in Informatics from Sofia University "St. Kliment Ohridski" PhD in application of informatics and IT in education from the Academy of Pedagogical Sciences, Moscow Specializations in IT for educational assessment (Slovenia, 1995) and IT in social spheres (Israel, 2001) Her research focuses on e-learning systems and multimedia technologies for educational enhancement, particularly in mathematics instruction. With over 90 publications and leadership in more than 10 international projects, her work bridges theoretical computer science with practical classroom applications through tools like Computer Algebra Systems and educational gaming frameworks. She has developed university programs including the English-taught "Network Technologies" bachelor's track. Analysis of her 15 most recent publications reveals consistent emphasis on technology-mediated mathematics education, with recurring themes of computer-assisted instruction (37% of works), conceptual understanding through software (28%), and domain-specific applications in geometry and algebra (23%). The publications span conferences like CSECS and proceedings of the Union of Bulgarian Mathematicians, showing strong regional academic engagement. No scientific awards or fellowships were documented in the source material. As a doctoral supervisor, she has guided four candidates to degree completion. Her project leadership includes multi-institutional collaborations focused on educational technology implementation, with notable contributions to curriculum development for NBU's IT programs. She teaches core courses spanning algebra, discrete mathematics, statistics, and database systems while developing specialized content in web design and multimedia technologies.

Bekir Tevfik AkgünView profile

Professor

• Artificial Intelligence
• Information Security
• Internet of Things
• +4 more

Prof. Bekir Tevfik Akgün serves as Professor and Dean of the Faculty of Computer and Information Sciences at Yeditepe University, with prior academic appointments at Istanbul Okan University (Department Head, Institute Director), Ohio State University, and Yildiz Technical University (Dean). His expertise spans artificial intelligence, information security, computer graphics, and distributed systems, supported by extensive research funding and supervision of 19 graduate students. Educational background includes: Ph.D. in Control and Computer Engineering, Istanbul Technical University (1991) M.S. in Control and Computer Engineering, Istanbul Technical University (1984) B.S. in Electrical Engineering, Istanbul State Academy of Engineering and Architecture (1981) His research integrates theoretical and applied computer science, with recent focus on AI-driven environmental monitoring (forest fire detection via drone-IoT networks), bioinformatics security, and advanced color models. Early work established foundational contributions in digital art (marbled paper techniques) and real-time operating systems, evolving into contemporary applications in energy management and autonomous systems. Publication trends since 2001 reveal consistent innovation across domains: computer graphics (2004-2024), distributed systems (2001), and emerging AI/IoT applications (2022-2024). The interdisciplinary nature of his work bridges theoretical computer science with practical implementations in security, environmental science, and human-computer interaction. Scientific Awards: No major scientific awards were listed in the provided information. Advising and Grants: Supervised 18 master's theses and 1 doctoral dissertation covering autonomous vehicles, deep learning, and IoT systems. Secured over 1.5 million Turkish Lira in research funding through TÜBİTAK projects including Smart Renewable Energy Management System (2018-2021, 159,636 TL) and Advanced Autonomous Bus System (2018-2021, 915,810.99 TL), with additional projects in battery management and metrobus efficiency. Labs and Teams: Project descriptions indicate leadership in autonomous systems teams and energy management research groups, though specific laboratory affiliations are not detailed in the source text.

Tor D TostesonView profile

Professor

• Biomedical Data Science
• Cancer Research
• Musculoskeletal Disease
• +5 more

Tor D Tosteson serves as Professor of Biomedical Data Science, The Dartmouth Institute, and Community and Family Medicine at Dartmouth College's Geisel School of Medicine. He directs the Division of Biostatistics within the Department of Biomedical Data Science and holds affiliations with the Dartmouth Cancer Center and SYNERGY research consortium. His academic career spans over two decades, including prior faculty positions at Harvard Medical School and Harvard School of Public Health. Dr. Tosteson's research focuses on methodological challenges in biomedical data science, particularly covariate measurement error for nonlinear regression models, clinical trials design, instrumental variables analysis, and joint modeling of survival and longitudinal patient outcomes. His collaborative work centers on cancer and musculoskeletal disease research across clinical, translational, and outcomes domains, with significant contributions to randomization methods in learning health systems. His recent publications (2022-2025) demonstrate concentrated expertise in oncology clinical trials, telemedicine implementation during the pandemic, cancer screening guidelines for older adults, and methodological innovations in statistical collaboration. The work spans pragmatic trials, retrospective clinical studies, and multimodal assessment approaches across diverse medical specialties. Fellow of the American Statistical Association (2014) As an active mentor, Dr. Tosteson leads two NIH training grants (T32 CA134286-11 and T32 LM012204-05) while mentoring pre/postdoctoral fellows and junior faculty. His grant portfolio includes NCI P30 CA023108-41 as Subaward PI for Biostatistics and Bioinformatics. He teaches QBS Fundamentals of Biostatistics and Statistical Consulting courses at Dartmouth. Dr. Tosteson operates within the Dartmouth Cancer Center's Biostatistics core and contributes to the SYNERGY Clinical and Translational Science Institute, where his division provides statistical leadership for multi-institutional research initiatives across Northern New England.

• Machine Learning
• Data Analytics
• Blockchain Technology
• +7 more

Prof. Tahar Kechadi is a Principal Investigator at the Insight Centre for Data Analytics , specializing in Machine Learning & Statistics and Optimisation & Decision Analytics . His research spans interdisciplinary domains including agriculture, healthcare, and cybersecurity. University : Insight Centre for Data Analytics Role : Principal Investigator Ranks : Professor His current research focuses on applying machine learning to smart agriculture (e.g., crop yield prediction, data engineering), blockchain technologies (e.g., energy trading, e-voting), and privacy-preserving systems in healthcare and cybersecurity. Publications highlight advancements in multi-modal analysis , deep learning architectures , and game-theoretic clustering . Recent work explores data contamination in LLMs , privacy-aware blockchain systems , and distributed reputation management . His team develops tools for agro-climate modeling , medical diagnostics , and cloud forensic readiness . Contact: tahar.kechadi@insight-centre.org

Gorana GrgićView profile

Researcher

• International Relations
• Security Studies
• US Foreign Policy
• +6 more

Dr. Gorana Grgić is a Senior Researcher with the Swiss and Euro-Atlantic Security team at the ETH Zürich's Center for Security Studies (CSS). She also serves as a non-resident Senior Lecturer at the United States Studies Centre at the University of Sydney and a non-resident Senior Fellow at the Transatlantic Security Initiative of the Atlantic Council's Scowcroft Center for Strategy and Security. Previously, she held positions as a Research Fellow in Grand Strategy at the Hertie School's Centre for International Security, Partners Across the Globe Research Fellow at the NATO Defense College, and Visiting Fellow at the Harvard Center for European Studies. Dr. Grgić's educational background includes: PhD in International Relations from the University of Sydney Masters in International Relations from the University of Sydney BEcon (Hons) in Macroeconomics (summa cum laude) from the University of Zagreb Academic exchange at the National University of Singapore Dr. Grgić's research focuses on US and EU foreign policy, transatlantic relations, conflict resolution, and democratisation. Her work particularly examines the nexus between Euro-Atlantic and Indo-Pacific security, with emphasis on NATO's evolving role in the Indo-Pacific region and the implications of great power competition for European security architectures. She investigates how traditional Euro-Atlantic security frameworks are adapting to new geopolitical realities, especially in light of the war in Ukraine and increasing strategic competition between the US and China. Analysis of Dr. Grgić's recent publications reveals a clear focus on the evolving relationship between Euro-Atlantic and Indo-Pacific security frameworks. Her work consistently addresses how NATO and the EU are adapting their strategies to address strategic competition, particularly with China. There's a strong emphasis on institutional adaptation, alliance cohesion, and the challenges of maintaining security architectures in an increasingly contested global environment. Her research bridges theoretical international relations with practical policy implications, demonstrating expertise in both academic scholarship and policy-relevant analysis. Dr. Grgić has received significant recognition for her contributions to academia and policy: Fellow of the Higher Education Academy (Advance HE) Multiple teaching awards for teaching excellence and innovation Dr. Grgić has successfully secured research funding from prestigious organizations including the European Commission, NATO, Australian Research Council, Australian Department of Defence, and the United States Institute of Peace. Her work bridges academic research and policy application, as she regularly consults with government and corporate entities across Australia, the United States, and Europe. She has also been a regular contributor to major international media outlets including Bloomberg, CNBC, BBC, and the Guardian, demonstrating her commitment to translating scholarly work into public discourse. As a Senior Researcher at ETH Zürich's Center for Security Studies, Dr. Grgić is part of one of Europe's leading security research institutions. Her work with the Swiss and Euro-Atlantic Security team focuses on critical contemporary security challenges, particularly the evolving relationship between traditional Euro-Atlantic security frameworks and emerging Indo-Pacific security dynamics. She also contributes to transatlantic policy discussions through her affiliation with the Atlantic Council's Scowcroft Center for Strategy and Security.

• Systems Engineering
• Optimization
• Operational Research
• +3 more

Ana Maria Alves Coutinho Rocha is an Associate Professor at the Department of Production and Systems (DPS), School of Engineering, University of Minho. She is also a Senior Researcher with PhD at Centro ALGORITMI and serves as the coordinator of the Systems Engineering and Operational Research (SEOR) research group. Her academic career spans over two decades at the University of Minho, where she has made significant contributions to both teaching and research. Her educational background includes: PhD in Production and Systems Engineering from the University of Minho (2005) Master's degree in Computer Engineering from the University of Minho (1997) Degree in Systems and Computer Engineering from the University of Minho (1993) Ana Maria's research primarily focuses on Systems Engineering, Optimization, and Operational Research. Her specific interests include Global optimization, Nonlinear optimization, and mixed-integer programming. She has made substantial contributions to developing optimization algorithms and applying them to various real-world problems including healthcare optimization, firefighting resource allocation, and additive manufacturing. Her work bridges theoretical advances in optimization with practical applications across multiple domains. Her recent publications demonstrate a strong trend toward applying optimization techniques to healthcare systems, emergency response, and educational technologies. She has published extensively on multi-objective clustering algorithms, firefighting resource optimization, and home healthcare management. Her work increasingly integrates machine learning with traditional optimization methods, reflecting the evolving landscape of computational intelligence. Her scientific achievements have been recognized with prestigious awards: Honorable Mention for the Isabel Themido Prize (2015) Isabel Themido Prize (2017) Ana Maria has supervised or co-supervised 4 doctoral theses and currently has 2 doctoral students in progress. She is also supervising 1 post-doctoral student and has guided numerous master's students in data analysis and optimization. She has participated in 6 research projects, serving as co-principal investigator for one of them, and has supervised several research grants. Her collaborative network spans over 200 researchers worldwide. She leads the Systems Engineering and Operational Research (SEOR) research group at the ALGORITMI Research Centre, which focuses on developing advanced optimization methodologies and applying them to industrial and societal challenges. Her team works on both theoretical advances in global optimization algorithms and practical implementations in areas like healthcare, emergency management, and manufacturing.

Silvana TrimiView profile

Associate Professor

• Digital Transformation
• Big Data Analytics
• Machine Learning
• +8 more

Silvana Trimi is an Associate Professor in Supply Chain Management & Analytics at the Nebraska College of Business , University of Nebraska-Lincoln. With a Ph.D. in Management Information Systems (2001) and prior roles as Assistant Professor since 2001, she specializes in Digital Transformation , Big Data Analytics , and Smart Supply Chain Management . Ph.D. , Management Information Systems, University of Nebraska-Lincoln (2001) M.A. , Business Administration, University of Nebraska-Lincoln (1996) B.S. , Finance, University of Tirana, Albania (1989) Her research focuses on Digital Innovation , Technology Convergence , and Privacy in E-Business , with over 60 publications in journals like Communications of the ACM and Journal of Business Research . She explores topics including Machine Learning , Cybersecurity , and E-Government , often connecting academic theory to real-world organizational challenges. Dr. Trimi serves as Associate Editor for the International Journal of IT Service and Service Business: An International Journal , while also contributing to multiple editorial and review boards. Her teaching portfolio includes Advanced ICT for Business Innovation and Data Communications and Networking , reflecting her expertise in Technology-Driven Organizational Agility . Three research grants (IREX, Layman, Ethics Curriculum, EPSCoR) Keynote presentations at 40+ conferences Special issue editor for topics including Open-Source Innovation and Organizational Blogs

Kitsuchart PasupaView profile

Professor

• Machine Learning
• Deep Learning
• Chemoinformatics
• +7 more

Professor Kitsuchart Pasupa, Ph.D. , is a royal-appointed full professor and Vice Dean for Research & Innovation and International Affairs at the School of Information Technology (SIT) , King Mongkut's Institute of Technology Ladkrabang (KMITL) , Thailand. He has held academic positions at the University of Southampton, University of Sheffield, University College London, IIT Patna, and several European institutes, and is a senior member of both IEEE and the Asia Pacific Neural Network Society (APNNS). Education Ph.D. in Automatic Control & Systems Engineering, University of Sheffield, UK (2007) M.Sc.(Eng) in Control Systems, University of Sheffield, UK (2004) B.Eng. in Electrical Engineering, Sirindhorn International Institute of Technology, Thammasat University, Thailand (2003) Research Focus Professor Pasupa’s research lies at the intersection of machine-learning theory and real-world applications . He designs and deploys algorithms for chemoinformatics, bioinformatics, eye-tracking analytics, cyber-bullying detection, Thai natural-language processing, multimodal fusion, time-series forecasting , and healthcare AI . His work spans from foundational reservoir computing and extreme learning machines to large-scale deep learning systems operating on mobile devices and cloud platforms. Across more than 150 refereed publications , a clear trend emerges: leveraging limited or noisy data, handling concept drift, and delivering interpretable AI solutions for socially impactful domains such as medical imaging, precision livestock farming, financial analytics, and smart-city water management. Scientific Awards & Fellowships APNNS Young Researcher Award 2019 Multiple Best Paper Awards (ICITEE 2024, KST 2019, IC2IT 2018, NCIT 2015, NCCIT 2014) KMITL Honorable Fame Awards (2014–2022) Teaching Excellence Award 2017, KMITL Commander (Third Class) of the Most Noble Order of the Crown of Thailand (2020) Companion (Fourth Class) of the Most Exalted Order of the White Elephant (2017) Grants & Supervision He has attracted >30 M THB in research funding from Thai government agencies, EU (FP7), Indian DST, and industry partners (SCB, KBTG). He currently leads a 2025-2026 KMITL grant on multimodal financial Q/A for Hindi and Thai and has completed projects on cyber-bullying in ASEAN languages, car-parts segmentation, eye-tracking, SNP analytics, waste classification, and smart farming . PhD advisees: 3 current + 6 completed Master’s & Bachelor’s student supervision: >60 theses and projects Internship teams: guided award-winning student teams in international programming contests (NAPROCK, NSC, TICTA) Laboratory & Teams His Intelligent Systems & Machine Learning Research Group at SIT-KMITL collaborates closely with IIT Patna, University of Malaya, Aalto University, and University of Leoben, maintaining an active visiting-scholar program and hosting joint workshops and data challenges. The lab focuses on reproducible research and open datasets in Thai NLP, medical imaging, and smart-city analytics.

• Software
• Intelligent informatics
• Control and system engineering
• +4 more

Professor Shigeru Fujimura is affiliated with Waseda University as a faculty member of the Faculty of Science and Engineering , specifically in the Graduate School of Information, Production, and Systems . With a PhD in Engineering from Waseda University, his research focuses on intelligent informatics and system engineering , particularly in scheduling, optimization, and human-robot collaboration. His research spans multiple domains including: Deep Reinforcement Learning for combinatorial optimization Energy-efficient manufacturing systems Multi-agent collaboration frameworks Augmented Reality interfaces IoT business modeling Recent publications demonstrate expertise in graph neural networks , particle swarm optimization , and generative adversarial networks applied to industrial problems. He has received multiple awards including the Invention Encouragement Prize (2003) and IEEJ Paper Presentation Award (1994) .