Dimitrios Skalkos serves as a Professor at the Department of Chemistry, University of Ioannina, holding the specific title of Professor of Innovation Management in Food Businesses. His office is located in building X2, room X2-206c on the Ioannina Campus (45110 Ioannina), and he leads the Food Chemistry Laboratory. He earned his Basic Degree in Chemistry from the University of Ioannina (1980-1985) followed by a Doctoral Degree from the University of Toledo, USA (1986-1989) with dissertation research on "Di- and Tetrahydroporphyrins: Syntheses and Antitumor Activities". Skalkos's research spans Food Business Management, Food Innovation, and Innovation Management, with specialized focus on Innovation & Entrepreneurship, Aromatic Plants, Innovative Foods, and Strategic Marketing. His work bridges academic research with industry applications in food systems, emphasizing Greek agricultural products and pandemic-era consumer behavior. His 36 publications (2020-2024) reveal strong trends in post-pandemic food innovation, consumer perception of traditional Greek foods, functional food development (particularly olive oil, cheese, and grape by-products), and sustainable agri-food supply chains. Key thematic clusters include traceability systems, bioactive properties of novel foods, and economic impacts on food choices. He has actively supervised Master's and PhD students through departmental presentations, directed 23 research programs, and organized 15 seminars and conferences. His laboratory website ( https://foods.chem.uoi.gr ) showcases ongoing food chemistry innovations.
Dr. Amin Keramati is an Assistant Professor of Supply Chain Management at Widener University’s School of Business Administration. He holds a PhD in Transportation & Logistics from North Dakota State University and previously served as a graduate research assistant at the Upper Great Plains Transportation Institute. His work includes federally funded projects like the Mountain-Plains Consortium’s MPC-550 project, focusing on highway-rail grade crossing safety. Dr. Keramati teaches courses in enterprise resource planning, decision analytics, database management, transportation/logistics, project management, and data analytics. Education: PhD in Transportation & Logistics, North Dakota State University Graduate Research Assistant at Upper Great Plains Transportation Institute Research Focus: Dr. Keramati develops mathematical, statistical, and machine learning approaches to solve complex problems in transportation, supply chain, and logistics. Key areas include data mining, big data decision support, transportation network analytics, project scheduling, smart manufacturing, and accident analysis. His interdisciplinary work bridges supply chain optimization with emerging technologies like blockchain for healthcare and clinical trials. Awards & Recognition: Student Paper Award, American Association of State Highway and Transportation Officials (2017) Grants & Projects: Lead researcher on the Mountain-Plains Consortium’s MPC-550 project, which expanded his dissertation work on safety systems for highway-rail crossings. Collaborates on federally funded transportation safety initiatives and supply chain optimization for bioethanol and pharmaceutical industries. Labs/Teams: Active in Widener’s School of Business research groups focusing on supply chain innovation and interdisciplinary projects combining logistics with emerging technologies.
David Stillwell serves as Professor of Computational Social Science at Cambridge Judge Business School and Academic Director of The Psychometrics Centre, University of Cambridge. His research leverages big data to understand human psychology and behavior, with significant contributions in personality prediction from digital footprints and personalized advertising applications. His educational background includes: BSc in Psychology from the University of Nottingham (2007) MSc in Research Methods from the University of Nottingham (2008) PhD in Decision Making from the University of Nottingham (2012) Dr. Stillwell's research centers on computational social science and psychometrics, pioneering the myPersonality Facebook application that collected data from over 6 million users. His work demonstrates computers can predict personality as accurately as spouses, reveals psychological targeting's advertising effectiveness, and establishes links between personality-matched spending and life satisfaction. He also explores linguistic honesty markers through profanity analysis and personality-based dating patterns. His recent publications (2019-2025) reveal a strong trajectory toward AI evaluation using psychometric frameworks, particularly in medical and general-purpose AI assessment. Key themes include fairness metrics in language models, crisis emotional responses through social media, and computational personality recognition - demonstrating consistent innovation at the psychology-technology intersection. He has received significant recognition: Top 10 most influential papers of 2013 by Altmetric Nieman Journalism Lab highlight of 2013 Named in 'top 30 thinkers under 30' by Pacific Standard Magazine Dr. Stillwell maintains active industry engagement through consultancy with Barclays, Hilton, and Ubisoft on projects spanning computer-adaptive testing systems to interactive experiences like Predictive World for Watch Dogs 2. His policy impact is substantial, with citations by the European Data Protection Supervisor, World Bank, and multiple national governments, leading to speaking engagements at the European Parliament and Bank of England. As Academic Director of The Psychometrics Centre, he leads a global hub for advancing psychological assessment through innovative methods including Concerto open-source software, collaborating with organizations ranging from the European Commission to major corporations on psychometric applications in people analytics and digital behavior.
Ram Rajagopal is an Associate Professor of Civil and Environmental Engineering and Electrical Engineering at Stanford University, and a Senior Fellow at the Precourt Institute for Energy. He leads the Stanford Sustainable Systems Lab (S3L), focusing on large-scale monitoring, data analytics, and stochastic control for infrastructure networks, particularly power systems. His research emphasizes renewable energy integration, smart distribution systems, and demand-side data analytics. Education: PhD in Electrical Engineering and Computer Sciences & MA in Statistics (UC Berkeley), MS in Electrical and Computer Engineering (UT Austin), and BEng in Electrical Engineering (Federal University of Rio de Janeiro). Research interests include power grid optimization, renewable energy systems, and data-driven approaches to infrastructure challenges. He has pioneered work in grid flexibility, distributed energy resources, and machine learning applications for energy systems. His lab develops technologies like Smart Dim Fuses and the EV-EcoSim platform for EV charging infrastructure optimization. Received NSF CAREER Award, Powell Foundation Fellowship, and Berkeley Regents Fellowship Over 30 patents and best paper awards Advises/founded companies in sensor networks, power systems, and data analytics Labs/Teams: Stanford Sustainable Systems Lab (S3L), Powernet Project. His work spans grid resilience, energy equity, and scalable energy solutions.
Jillian Bohlen is an Associate Professor at the University of Georgia within the College of Agricultural & Environmental Sciences , specifically the Department of Animal and Dairy Science . Her work focuses on dairy cattle reproduction, teaching, and youth development in agricultural sciences. Education: B.S. in Dairy Science, University of Georgia (2003) M.S. in Dairy Science, University of Georgia (2005) Ph.D. in Animal Sciences, Clemson University (2012) Dr. Bohlen's research emphasizes applied reproduction in cattle , including synchronization techniques, ultrasound applications in reproductive programs, and embryo competency. She integrates students into all research projects despite lacking a formal research appointment. Her teaching interests span dairy cattle production , reproductive management , and contemporary agricultural issues , with courses like ADSC 3620 (Dairy Cattle Production), ADSC 4010 (Issues in Animal Agriculture), and ADSC 4410 (Applied Reproductive Management). Scientific awards include: Student Career Success Influencer Award (2024) Russell Award for Excellence in Undergraduate Teaching (2023) UGA Creative Teaching Award (2022) CAES Early Career Teaching Award (2022) Hoard's Dairyman Youth Development Award (2021) Larry Benyshek Teaching Award (2017) She actively promotes agricultural education through programs like the Commercial Heifer Project , Dairy Cattle Judging , and Dairy Quiz Bowl . Additionally, she participates in funded projects related to methane emissions , heat stress mitigation , and antibiotic alternatives in dairy farming.
Dr. Anwar Haque is an Associate Professor in the Department of Computer Science at Western University, Canada, and a Faculty of Science Distinguished Research Professor. He holds a Ph.D. in Electrical and Computer Engineering and an M.Sc. in Computer Science from the University of Waterloo. Prior to academia, he was Associate Director at Bell Canada. His research focuses on 5G networks, IoT, cybersecurity, AI, and autonomous systems, with over 100 peer-reviewed publications and $15M in collaborative grants. Dr. Haque leads the Western Information & Networking Group (WING) Lab and is the founder/CEO of Bamboo Innovations Inc., a tech startup developing socially responsible smart technologies. Leadership roles include industry expert-in-residence in the Faculty of Science, Undergraduate Chair of the Computer Science Department, and member of Western’s Senate. He has delivered over 30 keynote talks and media features include BBC Earth and The Globe and Mail. Awards include the IEEE CCECE Leadership Award and multiple grants from NSERC, MITACS, and Bell Canada. His work spans network reliability, smart grids, and cybersecurity, with industry partnerships like the Bell-Western 5G Research Centre.
Adriana Tapus is a Full Professor at ENSTA Paris, affiliated with Institut Polytechnique de Paris, leading the Autonomous Systems and Robotics Laboratory (SAR) within the Computer Science and Systems Engineering Unit (U2IS). She holds an HDR (Habilitation) and a PhD from EPFL, Switzerland, with postdoctoral experience at USC. Her research focuses on socially assistive robotics, human-robot interaction (HRI), and personalized therapy for individuals with physical/cognitive impairments. She directs the IP Paris Doctoral School and coordinates national/international projects like the EU-funded ENRICHME and SWEET. Education: PhD in Mobile Robotics, EPFL (2005) Habilitation (HDR), ENSTA Paris (2011) M.S. Computer Science, University Joseph Fourier Engineer, Politehnica University of Bucharest Research Interests: Tapus pioneers socially assistive robotics, integrating machine learning, human modeling, and multimodal communication (verbal/non-verbal/para-verbal). Her work addresses adaptive therapies for vulnerable populations using robotics, physiological data interpretation, and context-aware interaction. Key themes include: Human-robot cooperation and trust Emotion recognition and expression Personalized rehabilitation systems AI ethics and human-centered design Publications: Over 150 articles, with recent work exploring humor in HRI, teleoperation trust models, and cross-cultural intelligent vehicles. Notable 2025 contributions include studies on robot laughter efficacy and multimodal facial expression frameworks. Awards: 2025: 4 IROS papers accepted 2016: 25 Women in Robotics recognition 2010: Romanian Academy Award Multiple conference best paper awards (RO-MAN, ICRA, etc.) Advising & Grants: Supervised over 20 PhD students and led projects like EU Horizon 2020 ENRICHME. Current students focus on teleoperation dynamics, robot humor, and haptic interfaces. Active in editorial roles (IJSR, THRI) and conference organization (HRI General Chair 2019). Labs/Teams: Founder of RoboticsByDesign lab and co-initiator of the Hi! Paris interdisciplinary AI center. The SAR lab develops systems for healthcare, education, and human-robot collaboration.
Mungo Wilson is a Professor of Finance at the Saïd Business School , University of Oxford, and an associate member of the Oxford-Man Institute of Quantitative Finance. He holds a PPE degree from Oxford, an MSc in Economics from LSE, and a PhD in Economics from Harvard. His research focuses on asset pricing, credit risk, mutual funds, and macroeconomic influences on financial markets. He has published extensively in top journals and engages actively with industry through board roles and advisory work. Education : Bachelor's in Philosophy, Politics & Economics (PPE), University of Oxford MSc Economics, London School of Economics PhD in Economics, Harvard University Research Interests : Assesses how macroeconomic conditions and credit risk shape asset prices Analyzes mutual fund behavior and market information transmission mechanisms Explores political dynamics' impact on financial markets His professional engagements include board memberships with funds like EA Asia Absolute Return Master Fund and advisory roles at Broadwell Capital. Teaching focuses on microeconomics for MBA programs, covering game theory, market structures, and price discrimination. Advisory & Grants : Supervises doctoral students at Saïd Business School and serves on programme committees for major finance conferences (e.g., European Finance Association, CEPR Annual Spring Symposium). Awards : While no specific prizes are listed, his impactful research has been widely cited and presented globally.
Albert Presto is a Research Professor in the Department of Mechanical Engineering at Carnegie Mellon University with a courtesy appointment in Civil and Environmental Engineering. He serves as Director of the Center for Atmospheric Particle Studies (CAPS) and is a Faculty Affiliate at the Steinbrenner Institute for Environmental Education and Research. His work spans multiple interdisciplinary collaborations across environmental science, engineering, and public health domains. Department of Mechanical Engineering, College of Engineering Center for Atmospheric Particle Studies (CAPS) Steinbrenner Institute for Environmental Education and Research Africa Clean Air Network Advisory Council Health Effect Institute's Energy Review Committee Presto's research focuses on pollutant emissions from energy extraction and consumption and their subsequent atmospheric transformations. His work examines how gas and oil wells emit methane, how vehicles emit carbon monoxide and particulate matter, and how these pollutants undergo oxidation in the atmosphere to create secondary pollutants like ozone and secondary particulate matter. His approach combines ambient measurements, laboratory experiments, source testing of pollution sources, and atmospheric models to provide a holistic view of pollutant emissions and transformations. His recent publications reveal a strong emphasis on air quality monitoring technologies, particularly low-cost sensor networks deployed internationally. There's a clear trend toward studying air pollution in African cities (especially Nairobi, Kampala, and Addis Ababa), examining spatial and temporal variability of particulate matter, and investigating the health impacts of air pollution exposure. His work increasingly integrates machine learning approaches for pollution forecasting and leverages international collaborations to address global air quality challenges. Member of Africa Clean Air Network Advisory Council Collaborator with US embassies worldwide on air quality data collection Quoted in The Guardian on inequality of air pollution exposure, specifically noting how people of color are more likely to be exposed to harmful air pollution Collaborated on research regarding chemicals released during the Ohio train derailment Presto actively collaborates with medical professionals to develop neighborhood-by-neighborhood studies of pollutant exposure and to understand relationships between emissions and health effects like childhood asthma. His work includes investigating racial-ethnic exposure disparities to airborne pollutants and examining how proximity to pollution sources like fast-food restaurants affects pediatric asthma outcomes. He has received seed funding from the Scott Institute for Energy Innovation for research in clean hydrogen production, AI hardware efficiency, and decarbonizing transportation. As Director of CAPS, Presto leads a research team focused on atmospheric particle studies with applications ranging from local Pittsburgh air quality to global monitoring initiatives. His lab develops and deploys advanced air quality monitoring technologies, including low-cost sensor networks that have been implemented in multiple cities across Africa. The CAPS research group works at the intersection of environmental engineering, atmospheric science, and public health to address critical air quality challenges worldwide.
Professor Huibing Zhang is a Professor of Management at the Naveen Jindal School of Management, University of Texas at Dallas. He holds a Ph.D. in Economics from Duke University (1994) and a B.S. from Shanghai Jiao Tong University, China (1984). Prior to his current position, he served as Associate Professor at the University of North Carolina at Chapel Hill (2000–2005) and Assistant Professor at Carnegie Mellon University (1994–2000). Education: Ph.D. in Economics, Duke University, 1994 B.S., Shanghai Jiao Tong University, China, 1984 His research focuses on financial economics, tax policy, and asset pricing. Key areas include the impact of capital gains taxes on asset prices, behavioral finance, and optimal portfolio strategies. He explores topics such as model uncertainty in financial markets, external habits affecting stock returns, and optimal consumption decisions under borrowing constraints. His work integrates theoretical frameworks with practical applications in taxation and investment planning. Awards and Honors: Fellow, TIAA-CREF Institute TIAA-CREF Paul A. Samuelson Award (2004) for outstanding work on optimal asset location and allocation Barclays Global Investors/Michael Brennan Runner-Up Award (2002) for research on optimal consumption and investment with capital gains taxes Undergraduate Economics Teaching Award, Carnegie Mellon University (1998) BP America Research Chair, Carnegie Mellon University (1995–1996) Grants and Contracts: Taxes, Estate Planning and Financial Theory: New Insights and Perspectives (Q-Group, 2002; TIAA-CREF, 2002) Diversification and Capital Gains Taxes with Multiple Risky Assets (TIAA-CREF, 2001) Optimal Asset Location and Allocation with Taxable and Tax-Deferred Investing (TIAA-CREF, 2000) Optimal Portfolio Choice and Consumption with Capital Gains Taxes (TIAA-CREF, 1999) Carnegie Mellon Faculty Development Fund (1998–1999)
Tae-Ho Lee is an Associate Professor in the Department of Psychology at Virginia Tech, with affiliated appointments in the School of Neuroscience and Translational Biology, Medicine, and Health. His research focuses on affective and cognitive neural development across the lifespan, neurodegeneration, and family-based neural dynamics. PhD in Brain and Cognitive Science, University of Southern California M.A. in Clinical Psychology, Korea University B.A. in Psychology, Korea University Dr. Lee’s work explores brain connectome dynamics, dyadic neural concordance in families, and age-related attentional control. He employs neuroimaging techniques to study how familial and environmental factors shape emotional and cognitive outcomes in adolescents and older adults. Recent publications highlight trends in longitudinal studies , parent-child neural similarity , and functional connectivity in emotion regulation . Key areas include autism spectrum disorder, substance misuse risk, and the role of socioeconomic factors in brain development. Rising Star , Association for Psychological Science (2020) Dr. Lee is not currently accepting students and leads the Affective Neurodynamics and Development (AND) Lab at Virginia Tech.
Dr. Ly Fie Sugianto is an Associate Professor in the Department of Accounting at Monash Business School, Monash University. Her research focuses on the integration of data analytics, artificial intelligence, and machine learning in accounting and business systems, with applications in the energy sector and organizational behavior. Monash Business School, Monash University Department of Accounting Specialization: Accounting Information Systems, Data Analytics, AI Her research interests span Accounting Information Systems , Agent-Based Simulation , Decision Support Systems , and Technology Adoption . She applies computational methods to study competitive dynamics in deregulated electricity markets and the impact of digital tools on employee well-being and organizational resilience. The recent publications reflect a strong trend in using AI and simulation to analyze complex socio-technical systems, particularly in energy markets and leadership dynamics. Keywords across her work include agent-based modeling , data analytics , servant leadership , and enterprise social media , indicating interdisciplinary research at the intersection of information systems, management, and public policy. Her scientific awards include competitive grants from the ARC (SPIRT/Linkage) , the Australia Indonesia Governance Research Partnership (AIGRP) , and the Sumitomo Foundation . ARC Grant: Dispatch Optimisation in the Australian National Electricity Market Sumitomo Foundation: Technology Use and Employee Well-Being AIGRP: Governance and MSME Resilience during Pandemic Dr. Sugianto has advised research projects and collaborated with industry partners such as Western Power , Ecogen Energy , and AEMO . She is currently accepting PhD students and leads externally funded research initiatives. Her work contributes to UN Sustainable Development Goals related to industry innovation and responsible consumption. She is affiliated with research teams focusing on intelligent decision support systems and digital transformation in business , with active collaborations in Australia and Indonesia.
Daniel Adelman is the Charles I. Clough, Jr. Professor of Operations Management at the University of Chicago Booth School of Business. He joined the faculty in 1997 after completing his PhD in industrial engineering and operations research at Georgia Tech. Adelman is a leading expert in Business Analytics and Management Analytics, helping companies deploy data and decision analysis to build world-class strategic and tactical management capabilities. Adelman received his PhD in industrial engineering and operations research in 1997, along with a bachelor's degree in industrial engineering and a master's degree in operations research, all from the School of Industrial and Systems Engineering at the Georgia Institute of Technology. Daniel Adelman's research focuses on applying analytical models to solve complex business problems across multiple industries. He has worked with firms from diverse sectors including internet services, chemical distribution, airlines, third party logistics, fiber-optics manufacturing, semiconductor manufacturing, oil, and healthcare. His research integrates real-world data with analytical models to bring structure and discipline to decision and control processes, enabling firms to achieve higher profits with lower risk. Adelman's recent work has concentrated heavily on healthcare analytics, where he leads the Healthcare Analytics Laboratory at Chicago Booth. This lab works with teams of doctoral and MBA students on projects with major healthcare institutions to optimize clinical, operational, and financial outcomes. His research spans foundational operations research including approximate dynamic programming, inventory theory/supply chain management, and revenue management/pricing optimization, as well as examining the linkage between operational performance metrics and financial performance of firms. Adelman's publications show a clear trend toward increasing focus on healthcare applications while maintaining strong theoretical foundations in operations research. His earlier work focused more on general operations management problems like inventory control and supply chain optimization, while his recent publications demonstrate a strategic shift toward healthcare analytics, particularly examining surgical team dynamics, hospital performance metrics, and resource allocation during public health emergencies like the COVID-19 pandemic. George B. Dantzig Prize (1998) for the best dissertation in operations research and management sciences that is innovative and relevant to practice Adelman regularly advises doctoral and MBA students through the Healthcare Analytics Laboratory at Chicago Booth. He has served as Associate Editor for Management Science, currently serves as Associate Editor for Manufacturing and Service Operations Management, and is the Area Editor for Operations and Supply Chain at Operations Research. His industry collaborations include significant projects with Akamai on internet pricing, with GE Global Research Labs on the electricity smart grid, with BP on gasoline supply contract portfolio optimization, and with Symantec on software release planning. Adelman leads the Healthcare Analytics Laboratory at Chicago Booth, which brings together interdisciplinary teams of doctoral and MBA students to work on a portfolio of projects with major healthcare institutions. The lab focuses on optimizing clinical, operational, and financial outcomes through advanced analytics and decision modeling.
Qing (Cindy) Chang is a Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia, where she directs the Intelligent Systems Lab. She joined UVA in 2019 after serving as an associate professor at Stony Brook University. Prior to academia, she spent a decade at General Motors R&D, receiving their highest innovation awards. Education: M.S. from University of Wisconsin-Madison Ph.D. in Manufacturing from University of Michigan Research Focus: Chang's work integrates math-based modeling and data-driven methods to optimize manufacturing systems. Key areas include: Adaptive control and machine learning for production efficiency Human-robot collaboration frameworks Sustainable manufacturing through energy management Real-time control of cyber-physical production systems Reinforcement learning applications in industrial automation Research Trends: Her recent publications (2024-2025) demonstrate strong focus on AI-driven manufacturing optimization, with 80% leveraging reinforcement learning/LLMs for robotic control. Key themes include multi-agent coordination (67% of papers), energy efficiency (53%), and flexible production systems (47%). Awards & Recognition: Inducted as SME Scholar (2024) 20 Most Influential Professors in Smart Manufacturing - SME (2020) NSF CAREER Award (2014) Three-time GM Boss Kettering Award winner (2005,2006,2008) ASME and SME Fellow Leadership & Funding: Serves on NAMRI/SME Board of Directors with editorial roles across ASME/IEEE/SME journals. Research supported by NSF (including CAREER), Department of Energy, and multiple industry partners. Leads projects on human-robot collaboration and sustainable manufacturing. Lab & Collaboration: Directs the Intelligent Systems Lab at UVA, focusing on industrial AI applications. Collaborates with automotive and energy sectors to translate research into practical solutions for smart factories.
Chendi Zhang is a Professor of Finance at the University of Exeter Business School. He serves as the founding Director of the Exeter Sustainable Finance Centre and Director/Treasurer of the Global Research Alliance for Sustainable Finance and Investment. Previously, he was Associate Dean for Research & Impact (2021-2025) and Director of Research for Finance and Accounting (leading REF2021 submission). He holds affiliations with the Global Systems Institute and Environment and Sustainability Institute, contributing to UN Sustainable Development Goals including Climate Action and Responsible Consumption. Education PhD in Financial Economics from Tilburg University MRes in Finance from Tilburg University MSc in Economics from Tilburg University BSc in International Finance from Shanghai Jiao Tong University Research Focus Professor Zhang's research explores sustainable investing, corporate finance, and behavioral finance with emphasis on ESG integration, climate risk, and stakeholder governance. His work examines how environmental/social factors influence financial markets, corporate decision-making, and asset pricing through empirical and theoretical frameworks. Recent studies analyze biodiversity's financial impact, carbon pricing mechanisms, income inequality disclosures, and ESG resilience during crises (e.g., COVID-19, Ukraine conflict). His research identifies market inefficiencies related to climate sensitivity, gambling sentiment, and dividend policies while exploring corporate governance in state-owned enterprises. Funding and Recognition Research funded by UKRI Natural Environment Research Council, British Academy, BNY Mellon, Royal Bank of Canada, and World Bank. Work featured in The Economist , Wall Street Journal , and Forbes . Articles published in top journals including Management Science and Journal of Financial Economics , cited over 10,000 times. Professional Service Vice Chair of Research Committee for Chartered Association of Business Schools. External examiner for Imperial College London. Previous appointments at University of Cambridge, University of Warwick, University of Sheffield, and Tilburg University.
