Find Academic Supervisors

Stefan StiegerView profile

Professor

• Psychological Methodology
• Psychoinformatics
• Psychometrics
• +16 more

Stefan Stieger is a Professor and Head of the Department of Psychological Methodology at the Karl Landsteiner Private University of Health Sciences. He leads an interdisciplinary research team focused on advancing psychological methodology through the integration of technology, statistics, and software development. His work bridges psychology and informatics, particularly in the emerging field of psychoinformatics. His research interests include psychometrics, individual differences, self-esteem, personality (e.g., Big Five, Dark Triad), life satisfaction, and digital well-being. He emphasizes methodological innovation, particularly through Experience Sampling Methods (ESM) and the development of open-source tools like ESMira, which enables real-time data collection in natural environments. His work often involves large-scale, cross-cultural studies and replication research to ensure robust psychological science. Recent publications highlight trends in replication studies, cross-cultural invariance of psychological scales, mood and energy dynamics, social perception, and the role of technology in behavioral research. His articles frequently appear in high-impact journals and address both foundational methodological questions and applied topics such as mental health in crisis regions. Stefan Stieger is actively involved in funded research projects, including studies on CO₂ and cognitive performance, app-based workplace health interventions, demographic diversity in groups, sexual activity frequency, and peer support for diabetes management. He collaborates extensively with international researchers and institutions. He advises and mentors students and junior researchers, though specific names are not listed. His team develops software solutions for the scientific community, promoting open science and reproducibility.

• Image Processing
• Hyperspectral Imaging
• Nuclear Fuel Characterization
• +4 more

Andrew John Campbell is a Knowledge Exchange Fellow in the Department of Electronic & Electrical Engineering at the University of Strathclyde's Faculty of Engineering. With a Doctor of Engineering in Advanced Manufacturing, Dr. Campbell specializes in applying image processing and hyperspectral imaging techniques to solve complex measurement challenges across nuclear decommissioning, aerospace, and industrial manufacturing contexts. His research bridges academic innovation with practical industrial applications, particularly in environments where traditional measurement approaches are impractical or hazardous. Doctor of Engineering, Advanced Manufacturing Dr. Campbell's research focuses on developing advanced image analysis methodologies for diverse applications. His primary expertise lies in hyperspectral imaging for nuclear fuel characterization during decommissioning processes, where his work enables remote analysis of radioactive materials through specialized techniques like short-wave infrared imaging through leaded glass. He has also applied similar methodologies to space object identification, granular material analysis in foundry applications, and biomedical contexts such as platelet analysis. His approach consistently combines cutting-edge image processing algorithms with domain-specific knowledge to address real-world industrial challenges. Analysis of Dr. Campbell's recent publications (2019-2025) reveals a clear research trajectory from fundamental image analysis techniques toward increasingly specialized applications in high-consequence environments. The 2024-2025 publications demonstrate a strong emphasis on nuclear decommissioning applications, with multiple papers addressing the characterization of nuclear fuel debris through multimodal spectroscopy. This work represents a significant advancement in the field, enabling safer and more efficient nuclear site cleanup. His publications span multiple high-impact venues including IEEE conferences and scientific journals, reflecting the interdisciplinary nature of his work. Best Technical Paper in IIF Journal Award (Non-Ferrous Category) - February 2025 Dr. Campbell has secured significant research funding through multiple competitive grants, serving as Principal Investigator for the "Spectroscopy Suite for Direct Low Waste Measurement for All States of Matter" project funded by Sellafield Limited (January-March 2024), and as Co-investigator on several other substantial projects including the HSI for Granular Material project funded by Fraunhofer UK Research Limited (2023-2024). His funding portfolio spans nuclear, aerospace, manufacturing, and biomedical applications, demonstrating the versatility of his image processing expertise. He has supervised doctoral research as evidenced by his role in the thesis "Image processing for the analysis of TI-6AL-4V microstructures" and has presented research at professional venues including a 2020 presentation on "Automated tracking of mitochondrial motility using image processing and epifluorescence microscopy". Dr. Campbell works within research groups focused on advanced imaging applications, collaborating extensively with researchers including Paul Murray, Jaime Zabalza, and Stephen Marshall. His laboratory work suggests capabilities in hyperspectral imaging, spectral analysis, and advanced image processing techniques. He appears to be part of Strathclyde's nuclear technology research initiatives and contributes to the Universities' Nuclear Technology Forum. His fingerprint analysis indicates significant contributions to image processing (100%), space object identification (87%), and microstructure analysis (65%), reflecting the interdisciplinary nature of his research program.

Alex DececchiView profile

Assistant Professor

• Paleontology
• Evolutionary Biology
• Biomechanics
• +7 more

Alex Dececchi is an Assistant Professor in the Department of Biology within the College of Arts & Sciences at Dakota State University. He holds a Ph.D. in Biology from McGill University (2012) and a B.Sc.H. in Biology from Queen’s University (2005). His academic career spans research and teaching in evolutionary biology, paleontology, and biomechanics. Education: Ph.D. in Biology, McGill University, 2012 B.Sc.H. in Biology, Queen’s University, 2005 Dr. Dececchi's research focuses on the evolutionary origins of flight in theropod dinosaurs and early birds, integrating biomechanical modeling, phylogenetic analysis, and morphological data. His work explores how anatomical changes enabled the transition from gliding to powered flight, with particular attention to limb proportions, wing structure, and aerodynamic performance. He also investigates Ediacaran biota and early animal evolution, contributing to our understanding of life before the Cambrian explosion. His recent publications span topics including aerodynamic modeling of Yi qi, phylogenetic relationships among Ediacaran fronds, and the computational annotation of phenotypic data using ontologies. These works reflect a strong interdisciplinary approach combining paleontology, computational biology, and functional morphology. Scientific Awards and Honors: The Mentorship Fund to Support Faculty-Student Scholarship, Research and Creative Activities (University of Pittsburgh at Johnstown, 2018) William E. White Postdoctoral Fellowship in Geological Sciences (Queen’s University, 2015–2017) Doctoral Research Funding, Fonds de Recherche et Technologies (Province of Quebec, 2008–2010) Delise Allison Graduate Travel Award (McGill University, 2010) Northern Scientific Training Program (Canadian Government, 2006, 2007, 2009) John B. Sampson Award (Queen’s University, 2001) Dr. Dececchi has been actively involved in mentoring students and securing research funding. He has co-organized major scientific symposia such as the International Pennaraptoran Dinosaur Symposium and presented at numerous conferences including the Society of Vertebrate Paleontology and the Canadian Society of Vertebrate Paleontology. His research has been supported by grants focused on faculty-student collaboration and innovative paleontological modeling. He is also engaged in collaborative research on morphological databases and computable anatomy, working with teams to standardize and extract phenotypic data from scientific literature. His lab integrates computational tools with traditional paleontological methods to advance synthetic knowledge of evolutionary patterns.

Andris FreivaldsView profile

Professor

• Ergonomics
• Human Factors
• Biomechanics
• +12 more

Andris Freivalds is the Lucas Professor in the Marcus Department of Industrial and Manufacturing Engineering at Pennsylvania State University, within the College of Engineering. His work bridges engineering and human health, focusing on ergonomics, biomechanics, and human performance in workplace and educational settings. His research interests center on ergonomics , human factors , and biomechanics , with specific expertise in hand and wrist mechanics, posture analysis, workstation design, and musculoskeletal health. He investigates how tools, equipment, and environments can be optimized to reduce injury risk and enhance performance. His work spans diverse domains including industrial tools, agricultural harvesting, wearable technology, and active workstations like desk bikes. The trend in his recent publications reflects a strong integration of biomechanical modeling , sensor-based assessment , and user-centered design . He frequently explores innovative technologies—such as wearable sensors, anti-vibration handles, and gamified learning—to improve human health, safety, and efficiency. His studies often involve empirical testing with human participants, cadaveric experiments, and computational modeling, published in top-tier journals like Applied Ergonomics and Gait and Posture . Dr. Freivalds has contributed to advancements in blueberry harvesting ergonomics, ergonomic pipette design, and the impact of desk pedaling on cognitive performance. His collaborations extend across engineering, health sciences, and agricultural research. Scientific Awards and Recognition: Lucas Professor – a named professorship indicating significant scholarly achievement and institutional recognition. Advising and Grants: While specific advisees are not listed, his frequent co-authorship with junior researchers suggests active mentorship. He has been involved in funded research initiatives, including projects related to human health and the environment, such as seed grants and manufacturing innovation funding at Penn State. Labs and Research Teams: Dr. Freivalds is affiliated with the Health and Environment research theme at Penn State and collaborates with interdisciplinary teams focusing on wearable technology, human performance, and sustainable systems. His work is supported through institutional and external research funding, enabling applied ergonomic solutions in real-world settings.

• Biomedical Engineering
• Artificial Intelligence
• Machine Learning
• +12 more

Associate Professor Rifai Chai is a faculty member in the Department of Biomedical Engineering at the School of Engineering, Swinburne University of Technology. He serves as the Academic Director (Partnerships), reflecting his leadership in academic-industry collaboration. His research focuses on the intersection of biomedical engineering and artificial intelligence, with applications in brain-computer interfaces, medical technologies, robotics, and embedded systems. University: Swinburne University of Technology School: School of Engineering Department: Biomedical Engineering Position: Associate Professor Email: rchai@swin.edu.au His educational and professional background includes over a decade of experience in product development in hardware, firmware, and software design in Indonesia and Australia from 2000 to 2011. His research interests are extensive and include: Artificial Intelligence and Machine Learning Brain-Computer Interfaces Medical Device Design Assistive Technology (e.g., smart wheelchairs, exoskeletons) Cognitive Fatigue and Workload Monitoring Back Pain Assessment and Rehabilitation Embedded Systems EEG and Physiological Signal Processing Rifai Chai's recent publications demonstrate a strong focus on AI-driven healthcare solutions. His work spans advanced computational intelligence in medical imaging (e.g., lung cancer and thyroid cancer detection), EEG-based systems for driver fatigue and emotion classification, rehabilitation technologies using exoskeletons, and cybersecurity in industrial IoT. He employs deep learning, hybrid models (e.g., MLP-BiLSTM), and advanced signal processing techniques to solve real-world biomedical problems. His research consistently targets practical, non-invasive, and real-time applications in clinical and industrial settings. His scientific contributions include numerous high-impact publications in journals such as IEEE Access, Sensors, and Medical & Biological Engineering & Computing, as well as book chapters with Elsevier and Springer. He has secured multiple research grants from industry partners and the Australian Research Council, supporting projects in breast electromagnetic scanning, solar-powered charging poles, and haptically-enabled motion simulation. Rifai Chai actively supervises PhD and Master’s students, with current HDR projects covering areas such as brain-computer interfaces for prosthetics, cognitive workload monitoring, distracted driving detection, and AI in medical imaging. He leads a multidisciplinary research team working at the forefront of biomedical innovation. His lab integrates AI, robotics, and physiological sensing to develop technologies that improve health outcomes and human performance.

• Operations Management
• Supply Chain Management
• Decision Making under Uncertainty
• +15 more

Hajnalka Vaagen is an Associate Professor in the Department of Ocean Operations and Civil Engineering at the Faculty of Engineering, Norwegian University of Science and Technology (NTNU), with an additional affiliation as Associate Professor II at the Norwegian School of Economics (NHH). Her research bridges theoretical and applied aspects of operations management, decision-making under uncertainty, and sustainable transformation. Her educational background includes a PhD in Quantitative Logistics from Molde University College (2009). She has held senior researcher roles at SINTEF Industry and SINTEF Technology and Society, contributing to operations research and industrial applications. Her research interests focus on: Risk and uncertainty management in project-based production systems, particularly in engineer-to-order contexts. Portfolio and assortment optimization in consumer goods, using stochastic modeling. Lean and flexible project delivery, integrating mathematical modeling with empirical data from lean construction. Circular economy initiatives in maritime industries, including ocean plastic pollution mitigation and sustainable supply chains. Industrialization of advanced 3D knitting technologies through digital platforms. The trends in her recent publications reflect a strong interdisciplinary focus combining operations research, sustainability, and behavioral insights. Her work frequently applies stochastic optimization to real-world challenges in shipbuilding, construction, and supply chains, emphasizing both technical and social dimensions of performance. She collaborates internationally, notably with the University of California, Berkeley’s Project Production Systems Laboratory. She has supervised multiple Master’s theses at NTNU, contributing to education in lean principles and ship design planning. Her outreach includes academic lectures at international conferences such as APMS, IFAC, and IGLC. Her research is supported by involvement in EU-funded projects like Blue Circular Economy (BCE) and CIRCNETS, as well as national initiatives such as SuSDesign and Sweet Spot under NTNU’s SusRes program. These projects aim to enable sustainable transformation through innovation ecosystems and policy-oriented operations management.

Henner GärtnerView profile

Professor

• Industrial Logistics
• Production Management
• Decentralized Manufacturing Control
• +5 more

Prof. Dr. Henner Gärtner is a full Professor for Industrial Logistics in the Department of Mechanical Engineering and Production at Hamburg University of Applied Sciences (HAW Hamburg). He is also Program Coordinator of the cooperative Mechanical Engineering program with the University of Shanghai for Science and Technology, Chairman of the Study Reform Committee, and deputy member of the Department Council. Education & Academic Focus Doctorate (Dissertation on stock-out cost quantification, PZH-Verlag, 2011) Research stays and teaching activities in Germany and China Research Interests Prof. Gärtner’s work spans decentralized production control , Industry 4.0 testbeds , autonomous transport systems (AGVs) , and real-time ergonomic monitoring . A flagship project is the Shared Guide Dog 4.0 , an AI-equipped autonomous rollator that supports blind and visually impaired pedestrians through advanced navigation and puddle-detection algorithms. Scientific Awards Hamburger Lehrpreis 2022 – Excellence in Teaching Projects & Funding SafeWalker – safe navigation assistance for elderly pedestrians Shared Guide Dog 4.0 – AI-driven mobility aid (with DAAD & BMAS support) GehwegNavi – sidewalk navigation for the visually impaired Decentralized Manufacturing Control testbed – “swimming-pool” model for resource negotiation Collaborative projects with Lufthansa Technik Logistik Services, VTG AG, DESY, and Krüss GmbH Teaching & Supervision He teaches bachelor and master modules such as Industrial Logistics , Production Planning & Control , Operations Management , and Project Management & Communication . Prof. Gärtner has supervised more than 30 bachelor and master theses on topics ranging from decentralized AGV control to AI-based computer-vision apps for barrier-free mobility. Labs & Teams Prof. Gärtner leads activities within the Institute for Product and Production Management (IPP) at HAW Hamburg and coordinates interdisciplinary student teams working on robotics, lean production, and service engineering.

Christian TerwieschView profile

Professor

• Healthcare operations
• Innovation management
• Lean operations
• +5 more

Christian Terwiesch is the Andrew M. Heller Professor at the Wharton School of the University of Pennsylvania, where he serves as Professor of Operations, Information and Decisions and Professor of Health Policy at the Perelman School of Medicine. He chairs the Operations, Information and Decisions department and co-directs Penn's Mack Institute for Innovation Management. His work bridges operations management, innovation, and healthcare delivery, with research published in leading journals from Management Science to The New England Journal of Medicine. Dr. Terwiesch received his doctoral degree from INSEAD and a Diploma from the University of Mannheim. His academic journey has positioned him at the intersection of business operations and healthcare innovation. Terwiesch's research focuses on healthcare operations, innovation management, lean operations, and new service delivery models. He is particularly known for his work on connected strategies that transform traditional episodic customer interactions into continuous relationships. His research explores how digital technologies can reshape business models, particularly in healthcare delivery, with an emphasis on improving quality while increasing efficiency. He has pioneered work on innovation tournaments as a systematic approach to generating and selecting new ideas, and has recently expanded his research to examine AI's impact on creativity and business processes. His recent publications demonstrate a strong focus on artificial intelligence's impact on business operations and innovation processes. Terwiesch has extensively examined how AI, particularly generative models like ChatGPT, affects creativity, customer service, and business strategy. His work reveals both the potential and limitations of AI in business contexts, highlighting areas where human-AI collaboration can yield optimal results. He has also continued his research into connected healthcare strategies that improve patient outcomes through better monitoring and engagement. Terwiesch has received numerous teaching awards throughout his career, reflecting his excellence in both MBA and executive education: Distinguished Fellow: Manufacturing & Service Operations Management (2017) Multiple Executive MBA Excellence in Teaching Awards (Philadelphia and San Francisco, 2014-2017) Helen Kardon Moss Anvil Award winner (2012) MBA Excellence in Teaching Award (2012, 2010) Numerous "Goes above and beyond the call of duty" and "Tough, but I'll thank you in 5 years" awards Miller-Sherrerd Core Teaching Award (multiple years) Named by Online Course Review as one of the 50 Most Popular MOOCs of All Time (2015) As an educator, Terwiesch has made significant contributions to online learning, developing the first Massive Open Online Course (MOOC) in business on Coursera, which has enrolled over half a million students. He co-authored the widely used textbook "Matching Supply with Demand" and has written influential management books including "Innovation Tournaments" and "Connected Strategies." His consulting work ranges from small startups to Fortune 500 companies, helping them become more innovative through implementing innovation tournaments and restructuring innovation portfolios. He has also received research grants from the Wharton e-Business Initiative. Terwiesch leads the "N=1, t=infinity Project," which focuses on connected healthcare strategies. This initiative aims to reimagine medicine by leveraging connected technologies to create continuous patient-provider relationships that improve outcomes while optimizing resource use. His work in this area has resulted in numerous publications and practical applications in healthcare delivery systems, including research on medication adherence and hospital readmissions using electronic monitoring devices.

Nura AbubakarView profile

Lecturer

• Cloud Computing
• Distributed Simulation
• Agent-Based Modelling

Nura Abubakar is an Associate Lecturer in Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences, with over 20 years of experience in software engineering and systems management. Her work bridges industry expertise with academic research in cloud computing and distributed simulation. Education: International Diploma in ICT Advanced Diploma in ICT BSc Computing and Software Engineering MSc Software Engineering PhD Computer Science Research Interests: She focuses on cloud-based distributed simulation (CBDS), agent-based modeling, and scalable cloud architectures. Her pioneering work on the Distributed Simulation Cloud Architecture for Experimentation (DICE) demonstrates how cloud computing can enable cost-effective, high-performance simulation systems. Teaching Activities: Dr. Abubakar teaches modules in Cybersecurity, Network Computing, Business Analysis and Process Modelling, and Network and Operating Systems. Professional Affiliations: The Council for the Regulation of Engineering in Nigeria (COREN) Nigeria Computer Society (NCS) Computer Professionals Association of Nigeria (CPN) Institute of Software Practitioners of Nigeria (ISPON) Academia in Information Technology (AIT) Association for Computing Machinery (ACM) Association for Information Systems (AIS) Institute of Electrical and Electronic Engineers (IEEE) The Society for Digital Information and Wireless Communications (SDIWC) The Operational Research Society (ORS), London British Computer Society (BCS), London The Institute of Leadership & Management (I'm), London

Toni M. SomersView profile

Professor

• Information Systems Strategic Planning
• Diffusion of Information Technologies
• Corporate Board Diversity
• +5 more

Toni M. Somers is a Professor at the Mike Ilitch School of Business , Wayne State University , specializing in Technology, Information Systems and Analytics . She also serves as the Senior Associate Dean and has held administrative roles for over half her career. Dr. Somers holds an MBA from Bowling Green State University (1992), a Ph.D. from the University of Toledo (1982), and a BA from the University of Toledo (1977). Education: M.B.A., Bowling Green State University (1992) Ph.D., University of Toledo (1982) B.A., University of Toledo (1977) Her research focuses on information systems strategic planning , diffusion of information technologies , corporate board diversity , and ERP implementation . She has published over 50 articles in journals like Information Systems Research , Decision Sciences , and Journal of Management Information Systems . Her work explores technology integration, organizational design, and governance frameworks. Dr. Somers teaches intermediate/advanced statistical methods , IT Security , and IT Ethics . She consults for Fortune 500 companies, the United Automobile Workers, and non-profits. Adjunct roles include appointments at the Weatherhead School of Management (Case Western University) and Wayne State’s Industrial Systems Engineering department, where she teaches multivariate statistics.

Dennis HohlfeldView profile

Professor

• Silicon-based microsystem technology
• Energy-autonomous systems
• Energy Harvesting
• +3 more

Prof. Dr.-Ing. Dennis Hohlfeld serves as Professor and Chair of Micro- and Nanotechnology of Electronic Systems at the University of Rostock's Institute of Device Systems and Circuit Technology. He holds key administrative roles as Study Advisor and Chairman of the Computational Science and Engineering (CSE) Examination Board, while actively contributing as a reviewer for research funding organizations and scientific publishers. His research spans five core domains: Silicon-based microsystem technology focusing on nanoscale material behavior for high-performance electronics Energy-autonomous systems leveraging environmental energy sources through harvesting techniques Energy-efficient circuit design for miniaturized applications Microoptics development for photonic integration Modeling and simulation techniques enabling system-level analysis of complex multiphysics phenomena Analysis of his 15 most recent publications reveals a dominant trend toward biomedical energy solutions, particularly thermoelectric generators for implantable devices. His work demonstrates strong interdisciplinary integration across electrical engineering, materials science, and neuroscience, with increasing emphasis on model order reduction for efficient simulation of MEMS devices and optogenetic applications. The publications consistently address miniaturization challenges while maintaining system-level performance. No scientific awards were documented in the provided materials. As Study Advisor and Examination Board Chairman for CSE, Prof. Hohlfeld oversees academic progression for computational science students. His research leadership encompasses: Technical Domains Energy harvesting systems for medical implants Photonic integration in microelectronics Multiphysics modeling frameworks Application Areas Autonomous environmental sensors Neuroprosthetic interfaces Power-efficient microsystems The Institute of Device Systems and Circuit Technology houses specialized laboratories for microsystem fabrication, energy harvesting characterization, and optical circuit development, supporting his research in silicon-based nanotechnology and energy-autonomous systems.

• Regional Economics
• Input-Output Analysis
• Environmental Economics
• +1 more

Luis Cruz is a Professor at the Faculty of Economics of the University of Coimbra (FEUC), actively affiliated with the Centre for Business and Economics Research (CeBER). In April 2025, he conducted research under a Fulbright Scholarship at the University of Virginia (UVA), co-organizing the Regional Economics and Input-Output Modeling Workshop with the Weldon Cooper Center for Public Service. This event fostered collaboration among PhD students and prominent economists like Michael Lahr (Rutgers University) and Geoffrey Hewings (University of Illinois Urbana-Champaign), emphasizing cross-generational dialogue in regional economics. His core research examines Environmental and Socio-Economic Interactions, with specialization in Regional Economics and Input-Output Analysis. The UVA workshop highlighted his focus on community-building in economic modeling, where he described the atmosphere as having "great energy, great conversations, and a strong sense of community across generations of regional economists" . His Fulbright experience facilitated cultural exchange and connections in socio-economic policy research. Analysis of his 15 most recent publications reveals an unexpectedly broad interdisciplinary scope spanning computer vision (LiDAR compression, 3D modeling), electrical engineering (grid inspection), and occupational medicine (dermatitis, radiation exposure). This suggests collaborative work beyond traditional economics, possibly through CeBER's cross-departmental initiatives at the University of Coimbra. Professor Cruz has secured competitive international funding through the Fulbright Program, enabling workshops that mentor emerging economists. His leadership in organizing the UVA workshop demonstrates active engagement in academic community development, though specific grant details beyond the Fulbright are not documented in the provided sources. He operates within CeBER (Centre for Business and Economics Research), a key research unit under FEUC that drives economic policy studies. The center's focus on empirical modeling aligns with his workshop on input-output analysis, though no dedicated lab or specialized team is mentioned in the current materials.

• Atomic Layer Deposition
• Thermoelectric Materials
• Thin Film Engineering
• +3 more

Ramin Ghiyasi serves as a Postdoctoral Researcher at Aalto University within the Department of Chemistry and Materials, actively contributing to the Inorganic Materials Chemistry research group. His work focuses on advanced thin-film deposition methodologies with applications in next-generation energy conversion technologies. His primary research interests center on atomic/molecular layer deposition (ALD/MLD) techniques for engineering functional materials, particularly thermoelectric systems. He investigates structure-property relationships in inorganic-organic hybrid superlattices, with emphasis on optimizing electrical conductivity while minimizing thermal transport through strategic defect engineering and interface control. His expertise spans intermetallic compounds, metal oxides, and cellulose-inorganic nanocomposites for flexible electronics applications. Analysis of his 2021-2025 publication record reveals a consistent trajectory in transport-property engineering through ALD/MLD, with increasing sophistication in multilayer architecture design. His work demonstrates particular mastery in ZnO and SnO systems, where organic components and purge-time manipulation enable unprecedented thermal conductivity suppression while maintaining electrical performance—critical for high-efficiency thermoelectric devices. No scientific awards are documented in available sources. There is no evidence of student advisement or principal investigator roles for major grants. Dr. Ghiyasi operates within Aalto University's Inorganic Materials Chemistry ecosystem under Professor Maarit Karppinen's leadership, collaborating extensively with international partners including Anjana Devi's group in Germany. His current research frontiers involve layer-engineered multilayer structures for flexible thermoelectric applications and novel precursor development for low-temperature hybrid film growth.

Andrii ShalaginovView profile

Professor

• Internet of things (IoT)
• Machine learning
• Smart cities
• +4 more

Andrii Shalaginov is a Professor in Cyber Security at Kristiania University of Applied Sciences, School of Economics, Innovation and Technology. He leads the Smart Security Lab with a research focus on applying artificial intelligence for cybersecurity, detection of computer viruses, network attacks and protection of Internet of Things devices. Dr. Shalaginov holds a PhD in Information Security from the Norwegian University of Science and Technology (NTNU), where he worked with digital forensics at the Center for Cyber and Information Security (CCIS). His research spans multiple critical areas of modern cybersecurity with a particular emphasis on Internet of Things security , machine learning applications for threat detection, and digital forensics . He has developed expertise in intelligent malware detection systems, network security for smart environments, and forensic analysis of IoT devices. His work bridges theoretical computer science with practical security implementations for real-world systems. Analysis of his recent publication trends (2022-2025) reveals a strong focus on AI-enabled security solutions for IoT ecosystems, vulnerability detection frameworks, and resource-efficient security mechanisms for constrained devices. His research increasingly addresses the intersection of machine learning and practical security implementations, with growing attention to energy efficiency in security protocols and international data space security frameworks. Dr. Shalaginov has received professional recognition through: Nomination as Norwegian representative in EU COST Action CA17124 "DigForAsp" Nomination as Norwegian representative in EU COST Action CA22104 "BEiNG-WISE" Membership in the "Impact of Technology" Expert Group at the European Union Intellectual Property Office Observatory As head of the Smart Security Lab, Dr. Shalaginov oversees research projects focused on developing practical security solutions for emerging technologies. His GitHub activity demonstrates active development of open-source tools for malware analysis across multiple platforms (Linux, Windows, IoT) and implementation of machine learning approaches for security applications. His research group appears to focus on bridging the gap between theoretical security models and practical implementations for real-world systems.

Venkittaraman Pallipuram KrishnamaniView profile

Associate Professor

• Machine Learning
• Natural Language Processing
• High-Performance Computing
• +3 more

Dr. Venkittaraman Pallipuram Krishnamani is an Associate Professor in the Electrical and Computer Engineering department at the University of the Pacific's School of Engineering and Computer Science. He serves as the Program Chair of the Master of Science in Engineering program, demonstrating leadership in academic program development. His expertise bridges engineering and computer science disciplines, with a focus on creating practical frameworks that empower domain scientists. Dr. Pallipuram's educational background includes: PhD in Computer Engineering from Clemson University (2013) MS in Computer Engineering from Clemson University (2010) Bachelor of Technology from National Institute of Technology, Tiruchirapalli, TN India (2008) Dr. Pallipuram's research focuses on applying machine learning, natural language processing, and high-performance computing to solve real-world problems across various domains. His work particularly emphasizes developing user-friendly frameworks that enable domain scientists in chemistry, physics, education, and medicine to effectively utilize advanced computing technologies. His A2Cloud series provides practical solutions for cloud resource selection, while ChatReview offers innovative approaches to analyzing large survey datasets through natural language processing. His research demonstrates a consistent commitment to bridging theoretical computer science with practical applications that advance scientific discovery. His recent publications reveal a strong trend toward educational data mining and machine learning applications in education, alongside continued work in cloud computing frameworks. The research shows increasing focus on using AI to enhance teaching and learning experiences, with several 2024 publications addressing student achievement prediction and engineering education redesign. His work consistently combines theoretical rigor with practical implementation, creating frameworks that solve specific computational challenges for domain scientists. Dr. Pallipuram actively mentors undergraduate and graduate students in his research group, providing opportunities for hands-on experience with cutting-edge technologies. His collaborative approach is evident in his numerous co-authored publications across diverse domains including education, public health, and scientific computing. While specific grant information isn't detailed in the provided text, his sustained research output suggests successful funding acquisition to support his computational research initiatives. His laboratory work centers around developing the A2Cloud series of frameworks and ChatReview, creating practical tools that help domain scientists navigate complex computing environments. These projects involve interdisciplinary collaboration with chemists, physicists, educators, and medical professionals, reflecting his commitment to applying computer engineering solutions to advance science across multiple fields.