Find Academic Supervisors

• Business Analytics
• Marketing Analytics
• Big Data Analytics
• +7 more

Dr. Mu Yang is a Senior Lecturer (Associate Professor) in Business Analytics at Birkbeck Business School, University of London, and Head of the Business, Strategy & Analytics Subject Group. She holds a PhD in Computer Science from the University of Southampton and a BSc in Management Information Systems from Beijing Jiaotong University. Her research focuses on Marketing Analytics, Big Data Analytics, Open Innovation, Digital Economy, Privacy, and Digital Innovations (e.g., AI, Blockchain). She previously served as Senior Lecturer and Interim Director of the TIME Research Centre at the University of Kent. Her teaching emphasizes research-oriented and case-based learning in business analytics, digital marketing, and computer science. She supervises PhD students in areas like Business Analytics, Privacy, and Digital Innovations. Her work bridges computer science and business, addressing topics such as data anonymization, user privacy, and technology adoption strategies. Key research themes include the impact of geopolitical risks on technology adoption, blockchain project success factors, and consumer behavior in digital platforms. She actively contributes to interdisciplinary collaborations, integrating technical expertise (e.g., AI, blockchain) with business challenges in marketing and innovation.

Niladri SyamView profile

Associate Professor

• Artificial Intelligence
• Machine Learning
• Sales Force Management
• +6 more

Niladri Syam is the Robert J. Trulaske Sr. Associate Professor of Marketing at the Trulaske College of Business, University of Missouri. He holds a PhD in Management Science from the University of Texas at Dallas and has an extensive background in mathematics, operations research, and foreign trade. Education: BS, Mathematics, University of Delhi MS, Mathematics, University of Delhi MBA, Foreign Trade, Indian Institute of Foreign Trade MS, Operations Research, University of Texas at Dallas PhD, Management Science, University of Texas at Dallas His research and teaching focus on Artificial Intelligence and Machine Learning Applications in Marketing and Sales , Product Customization , and Product Co-Creation . He has also contributed significantly to Sales Force Management , including sales compensation, quota setting, sales contests, and analytics for sales pipeline management. The 15 most recent publications reflect a strong emphasis on Machine Learning , Sales Analytics , Co-Creation , and Behavioral Economics . These works span strategic topics like sales compensation design, team selling dynamics, and AI applications in sales optimization, with a consistent focus on bridging technical advancements with practical marketing challenges. Scientific Awards: 2018 Best Paper Award – Runner up As an active contributor to executive education, he has taught at prestigious institutions worldwide, including the Indian Institute of Management (Calcutta), Indian School of Business (ISB), IMD Lausanne, and Vlerick University. His industry collaborations with McDonald’s Corporation, Metlife, and partners of the Center for Sales and Customer Development (CSCD) highlight his practical impact.

Hossein AhmadiView profile

Research Fellow

• Digital Health
• Artificial Intelligence in Healthcare
• Machine Learning Applications
• +3 more

Hossein Ahmadi is an EPIC Research Fellow in eHealth (Data Science or Robotics) at the School of Nursing and Midwifery, University of Plymouth. His research focuses on digital health and applied health studies, leveraging machine learning and big data techniques for disease diagnosis, prediction, and healthcare innovation. He has collaborated with organizations like NHS Kernow CCG and SMEs including Akumen Ltd and n-Coders, supporting AI and data science initiatives in eHealth. Education: PhD in Information Systems (Malaysian Government Scholarship, 2016), followed by postdoctoral roles at Tehran University of Medical Sciences and Aston University. Over 8 years of academic experience across institutions like Plymouth University, Aston University, and Iran University of Medical Sciences. Research Interests: Machine learning applications in healthcare (e.g., Parkinson’s disease, breast cancer), health data analytics, AI-driven diagnostics, and telemedicine. His work has been published in high-impact journals like Biocybernetics and Biomedical Engineering and Telematics and Informatics. Advising & Grants: Supervised 9+ students in health informatics and data science projects, including master’s theses on sentiment analysis and healthcare dashboards. Active in grant proposal development, particularly in international collaborations involving UK and Iran institutions. Labs & Teams: Leads projects within the University of Plymouth’s Centre for Health Technology, focusing on interdisciplinary research in telehealth and AI for patient care.

Vahid NasirView profile

Assistant Professor

• Advanced Manufacturing
• Forest-based Bio-Products
• Resource Extension and Optimization
• +8 more

Vahid Nasir is an Assistant Professor in the Department of Wood Science & Engineering at Oregon State University's College of Forestry. He directs the Advanced Manufacturing Laboratory and advises graduate students. His educational background includes a Ph.D. from the University of British Columbia (2020), M.Sc. from Iran University of Science and Technology (2009), and B.Sc. from the same institution (2006). Research Focus: Dr. Nasir specializes in smart data-driven manufacturing systems, integrating Industry 4.0/5.0 frameworks with sustainable material applications. His work spans: Applied machine learning for manufacturing optimization and predictive maintenance Human-centric design in production systems 3D printing with renewable bio-composites Sensor fusion for industrial process monitoring Resource efficiency in forest-based product manufacturing His publications demonstrate strong cross-disciplinary integration, combining wood science fundamentals with advanced computational methods. Recent work emphasizes explainable AI for material property prediction and digital fabrication frameworks for customized manufacturing. Dr. Nasir teaches undergraduate and graduate courses including WSE 461/561: Introduction to Wood Products Manufacturing and WSE 463/563: Advanced Manufacturing 2 , covering processing technologies, automation, and emerging industry trends like IoT and Big Data analytics. He currently advises graduate student Biva Gyawali and leads research initiatives through the Advanced Manufacturing Laboratory.

• Supply Network
• Innovation
• Risk and Resilience
• +5 more

Kedong Chen is an Assistant Professor of Supply Chain and Analytics at the Lally School of Management, Rensselaer Polytechnic Institute (RPI). His research focuses on supply network resilience, innovation dynamics, e-commerce logistics, and data analytics. He holds a Ph.D. and M.S. in Supply Chain and Statistics from the University of Minnesota, and a Bachelor of Management from Fudan University in China. His work bridges theoretical frameworks with practical applications, addressing challenges in supply chain coordination, green innovation policies, and deep learning models for forecasting. Recent publications explore AI-driven SCOM strategies, last-mile logistics optimization, and the impact of China's innovative city policies on cross-border patenting. Education: Ph.D. in Supply Chain and Operations, University of Minnesota M.S. in Statistics, University of Minnesota Bachelor of Management, Fudan University Dr. Chen has received notable recognitions, including the 2023 Academy of Management Chan Hahn Best Paper Award and 2024 POMS Best Paper Finalist. His research emphasizes actionable insights for firms navigating supply chain disruptions, policy-driven innovation, and leveraging data analytics for strategic decision-making.

• Machine Learning
• Data Mining
• Big Data
• +8 more

Donato Malerba is a Full Professor at the Department of Computer Science, University of Bari, Italy, and Director of the CINI Lab on Big Data. His research focuses on Machine Learning, Data Mining, and Big Data applications, with notable contributions to spatial data analysis, process mining, and cybersecurity. He has led multiple European and national research projects and received the IBM Faculty Award in 2004. Malerba serves on the Board of Directors of the Big Data Value Association and chairs international conferences like ECML PKDD and ALT/DS. His work bridges theory and practice, addressing challenges in environmental monitoring, network security, and explainable AI. Research interests include inductive logic programming, multi-relational mining, bioinformatics, and cyber threat detection. He has published over 200 papers in top venues and actively collaborates with industry stakeholders through projects like the PPP Big Data Value initiative. Awards: IBM Faculty Award 2004 Roles: Director of Computer Science Department, Director of CINI Lab on Big Data Key Projects: Lead investigator in EU-funded projects on Big Data analytics, cybersecurity, and environmental monitoring. Recent work emphasizes LLM applications for environmental monitoring (e.g., bark beetle outbreak detection via Sentinel-2 imagery) and quantum machine learning for incremental learning. His lab develops tools like PROPHET (explainable predictive process monitoring) and PANACEA (neural ensemble-based cyber threat detection).

• Data Mining
• Social Computing
• Graph Mining
• +7 more

Erisa Terolli is a Teaching Assistant Professor at the Charles V. Schaefer, Jr. School of Engineering and Science at Stevens Institute of Technology , where she has been employed since September 2021. Her academic work spans Data Mining , Social Computing , and Graph Analytics . Education : PhD in Computer Science (2018) from Sapienza University of Rome Research Interests : Erisa focuses on Efficient graph mining techniques for massive datasets Understanding user behavior and entity dynamics in health forums Modeling political discourse anomalies on platforms like Reddit Computational psychology of digital shop assistants Physics-inspired optimization algorithms for terrain and supply chain problems Design of career office information systems Scientific Awards : Google Anita Borg Fellowship (2015) ICT Awards - Female in ICT (2016) Institutional Service : Erisa has contributed to various committees and initiatives at Stevens, including: Chair of the DEI Committee Advisor for the SWICS Student Club Member of the ADAPT S-STEM Program Chair of the Developing Curriculum Committee NSF BPC Plan Workshop participant Academic Ambassador and member of CS NTT/Chair Search Committees

Damiano ZanottoView profile

Associate Professor

• Wearable Robotics
• Gait Analysis
• Rehabilitation Engineering
• +4 more

Damiano Zanotto is an Associate Professor (with tenure) in the Department of Mechanical Engineering at Stevens Institute of Technology, within the Charles V. Schaefer, Jr. School of Engineering and Science. He directs the Wearable Robotic Systems Laboratory, focusing on wearable technology for rehabilitation, gait analysis, and injury prevention. His research integrates robotics, machine learning, and sensor systems to address mobility challenges in clinical and real-world settings. Education includes: Ph.D. in Mechatronics, University of Padua (Italy), 2011 M.S. in Mechanical Engineering, University of Padua (Italy), 2007 B.S. in Mechanical Engineering, University of Padua (Italy), 2005 His research explores three key areas: (1) Lower-extremity exoskeletons for locomotor assistance and rehabilitation, (2) Wearable sensors and ML models for gait disorder assessment and injury prevention, and (3) Cable-driven robots for suspended-load transportation. Work emphasizes real-world applicability, with projects funded by NIH, NSF, and DoD. Publications predominantly focus on gait analysis and rehabilitation robotics (2021-2024), leveraging machine learning for adaptive control and sensor validation. Trends include reinforcement learning for personalized training, instrumented insoles for ecological monitoring, and integrated robot-sensor systems for elderly mobility. Awards and honors include: NSF CAREER Award (2020) Outstanding Associate Editor, IEEE Robotics and Automation Letters (2023, 2024) Best Paper Award (2nd prize) at IEEE BioRob (2022) Columbia University Translational Fellowship (2015-16) He leads significant grants such as NIH R01 (2024) for digital biomarkers in neuromuscular disorders, NSF I-Corps (2023) for AI-enabled shoe insoles, and CDMRP projects (2022) for trauma recovery. The Wearable Robotic Systems Laboratory develops practical solutions like instrumented insoles and ankle exoskeletons, collaborating with clinical partners.

Emmanuel MogajiView profile

Associate Professor

• Advertising
• Branding
• Digital Marketing
• +7 more

Dr. Emmanuel Mogaji is an Associate Professor in Marketing and Head of the Marketing, Operations, and Digital Group at Keele Business School, Keele University. His research focuses on the ABCDE framework of Marketing (Advertising, Branding, Communication, Digital, Ethics), applied across Transportation, Education, Financial Services, and Sports sectors. He has authored numerous peer-reviewed articles in journals like Industrial Marketing Management and Transportation Research Part D, and received the Emerald Literati Award for financial services marketing research. His work bridges academic theory with industry practice, addressing global challenges such as sustainable transport in Africa and AI-driven financial innovation. Education: Prior industry experience as a marketing communication executive. Research: Emphasizes ethical marketing, inclusive transport systems, and transformative service research. Teaching: Leads modules in branding, digital marketing, and strategic marketing management at undergraduate, postgraduate, and MBA levels. Leadership: Convenor of the Black Marketing Scholars' Network and UK Academy of Marketing Executive Committee member. Recent research explores generative AI impacts on financial services and creative industries, sustainable transportation solutions, and metaverse applications. His initiatives advance diversity in academia and practical solutions for emerging economies.

Aïda Valls MateuView profile

Associate Professor

• Multi-criteria decision support systems
• Intelligent data analysis
• Fuzzy logic
• +4 more

Dr. Aïda Valls Mateu is an Associate Professor in the Department of Computer Engineering and Mathematics at Rovira i Virgili University (Spain), serving as the ETSE school secretary. She leads the ITAKA research group (Intelligent Technologies for Advanced Knowledge Acquisition), recognized as 'Consolidated' by the Catalan government since 2014. Her work focuses on decision support systems, fuzzy logic, machine learning applications in healthcare, and tourism analytics. She has developed clinical decision support systems like RETIPROGRAM for diabetic retinopathy screening, validated in large-scale studies. Her research also addresses environmental and tourism-related decision-making challenges through multi-criteria analysis and semantic technologies. Dr. Valls holds a PhD in Artificial Intelligence from the Polytechnic University of Catalonia (2002) and has been at URV since 1998. Her team’s work spans health informatics (e.g., AI-driven retinopathy detection), sustainable energy evaluation, and personalized tourism recommendations. Notable projects include AI algorithms for diabetic retinopathy grading, lipid metabolism studies in diabetic populations, and fair tourism recommendation systems. Her publications emphasize interpretable machine learning models (e.g., fuzzy decision trees), medical imaging analysis (segmentation of retinal lesions), and hybrid models for ICU patient discharge prediction. She actively contributes to advancing explainable AI through methods like Fuzzy-LORE for counterfactual explanations. Current focus areas include refining AI tools for diabetic retinopathy screening, integrating semantic criteria in decision support systems, and promoting gender equality in AI research through collaborative initiatives.

Sam AnandView profile

Professor

• Additive Manufacturing
• Manufacturing Systems Optimization
• Industrial Internet of Things (IIoT)
• +4 more

Sam Anand is a Professor and Director of the Siemens PLM Simulation Technology Center at the University of Cincinnati's College of Engineering, Architecture and Art (CEAS), Mechanical Engineering Department. He holds a PhD in Industrial Engineering from Penn State University (1990), and prior degrees from the Indian Institute of Science and the University of Madras. His research focuses on Additive Manufacturing (AM), Manufacturing Systems Optimization, Industrial IoT (IIoT), and Augmented Reality applications in industry. He has led over 50 grants totaling millions from federal agencies (NSF, DoD), industry partners (Procter & Gamble, Siemens), and state initiatives. Notable projects include topology optimization for AM, digital twin integration, and AI-driven manufacturing processes. Publications (15+ recent articles) emphasize AM distortion prediction, lattice structure design, and IIoT-enabled systems. He advises 18 current doctoral and master's students, emphasizing industry-ready skill development. His lab, the Siemens Center, collaborates with industry to bridge academia and real-world manufacturing challenges.

• Health IT Systems Design
• Human-Computer Interaction
• Human Factors Engineering
• +5 more

Akanksha Singh is an Assistant Professor and Assistant Professor (P) at the School of Health Professions, Health Services Administration, University of Alabama at Birmingham since August 2023. She holds a PhD in Informatics from the University of South Carolina (2023) and has extensive experience in health information systems design, human-computer interaction, and applied artificial intelligence techniques in healthcare. Her research focuses on human factors in health IT systems, including patient preferences in clinical decision support, health recommender systems (HRS), and community health information networks (CHINs). Education includes a Master of Science in Computer Science (2017) and Bachelor of Technology in Computer Science (2012) from the University of South Carolina and Jaypee Institute of Information Technology. She has held roles as a Research Scientist at the Center for Effectiveness Research in Orthopedics and served as a Graduate Research Assistant and IT Research Manager. Research interests span Health IT systems design, human factors, data analytics, and AI applications in healthcare. Notable projects include the CHIPSS information system for substance use recovery, I-C-IT orthopedic treatment recommender, and the STORY+ app for breast cancer adherence. Awards include the AMIA 2020 Distinguished Poster Award and multiple graduate fellowships. Her work integrates Design Science Research (DSR) methodologies, emphasizing iterative software artifact development. Active in teaching, she has instructed courses on health information systems management and HCI at both UAB and USC. Technical expertise includes programming in Python, PHP, JavaScript, and platforms like MS SQL Server and PowerBI.

• Consumer Behavior in Tourism
• Service Industry Management
• Destination Management
• +3 more

Christian Laesser is a Professor and Senior Lecturer of Management at the University of St. Gallen, specializing in Tourism and Service Management. He leads the IMP-HSG (SBB Lab) and focuses on consumer behavior in service industries, financing of tourism infrastructure, destination management strategies, and digital transformation challenges in tourism sectors. His affiliations include roles in academic research, policy advising, and industry collaborations. Laesser’s research spans over 20 years, emphasizing empirical studies of travel decision-making, crisis management in tourism, and innovative business models for destinations. He has published extensively on topics like NFT applications in tourism, AI-driven service management, and sustainable destination governance frameworks. His work bridges academic theory with practical industry solutions, particularly in alpine tourism regions. Research Highlights: Crisis resilience strategies, digital transformation trends, hybrid tourism consumer behavior, and DMO effectiveness frameworks Key Projects: St. Gallen Model for Destination Management, Travel Market Switzerland studies His contributions include shaping policy recommendations for public transport financing and advocating for process-oriented destination management approaches. Collaborations with Swiss Federal Railways (SBB) and regional tourism boards highlight his industry-research nexus.

Lien DenooView profile

Associate Professor

• Entrepreneurship
• Innovation Management
• Technology Ventures
• +3 more

Lien Denoo is an Associate Professor of Entrepreneurship in the Department of Strategy and Entrepreneurship at Tilburg School of Economics and Management (Tilburg University). She holds a PhD in Management, Innovation, and Entrepreneurship from Ghent University (2015). Her research focuses on new venture resource acquisition, business model evolution in emerging industries, and founder characteristics' impact on venture growth. Prior to Tilburg, she was a postdoctoral scholar at the University of Southern California (2015–2017). Education : PhD in Management, Innovation & Entrepreneurship (Ghent University, 2015) Master’s in Business Engineering (Ghent University, 2010) Bachelor’s in Business Engineering (Ghent University, 2008) Her research interests span entrepreneurship and innovation, particularly in technology-driven sectors. She explores topics like business model adaptation, advisor networks in science-based ventures, and the interplay between market orientation and technology commercialization. Key publications include studies on advisor impacts in science-based ventures (2024), emotional regulation in entrepreneurship (2020), and customer ties in emerging industries (2022). She has received awards such as the EBS Best Paper Award (2021) and two Excellent Teacher recognitions (2021, 2023). Denoo supervises PhD students Jiahe Wang, Luuk Baltissen, and others. She contributes to editorial roles for Journal of Business Venturing and Long Range Planning , and organizes academic events like the European QCA Conference (2024).

Hoorsana DamavandiView profile

Assistant Professor

• Marketing
• Consumer Behavior
• Price Management
• +7 more

Hoorsana Damavandi is an Assistant Professor of Marketing at the Haslam College of Business, University of Tennessee at Knoxville. Her research examines how firms navigate adversities in supply chain and customer relationships, focusing on price increases, product quality failures, and spatial marketing strategies. She employs econometrics, machine learning, and experimental methods in her work. Education: Ph.D. in Marketing, Ivey Business School at Western University (2024) MBA (First in Class), Alzahra University, Tehran (2019) B.Sc. in Geomatics Engineering, University of Tehran (2014) Research Interests: Price Management & Justification Strategies Supply Chain Relationships & Adversity Mitigation Location-based Marketing Analytics Econometric Modeling of Market Dynamics Machine Learning Applications in Marketing Awards: John F. Rankin Doctoral Scholarship (2021-2023) Brock Scholarship (2019-2023) Plan for Excellence Doctoral Fellowship (2019-2023) Teaching: Social Media Analytics (MSc elective at Ivey) and AI in Business (executive education). Authored case studies including McCain Foods UK case on inflation management and iMerit brand positioning. Professional Experience: Previously served as Director of Business Development at Namira (e-commerce startup), Geomatics Engineer at Behro Engineering, and arithmetic teacher at Jamiat Defa’.