Christopher Piech is an Assistant Professor (Teaching) in the Department of Computer Science at Stanford University, with a courtesy appointment in the Graduate School of Education. He serves as a Faculty Affiliate at the Institute for Human-Centered Artificial Intelligence (HAI) and is affiliated with the Symbolic Systems Program. Current courses: AI for Social Good (CS 21SI), Introduction to Probability for Computer Scientists (CS 109), Researching Presenting and Publishing Work in AI & Education (CS 220/EDUC 481) Advises 11 Master's students and co-advises 3 Doctoral students His research focuses on computational education, leveraging artificial intelligence to enhance learning analytics, student collaboration detection, and knowledge tracing in programming education. Publications span ACM Technical Symposium on Computer Science Education (SIGCSE) and NeurIPS conferences. Key article trends include: (1) AI-driven educational tools for code analysis, (2) collaboration monitoring in large classes, and (3) probabilistic models for student learning trajectories.
Dr. Rajesh Bhargave is an Associate Professor of Marketing at the Department of Analytics, Marketing and Operations within Imperial Business School, Imperial College London. He holds a B.B.A. from the University of Texas at Austin and a Ph.D. from the Wharton School of the University of Pennsylvania. His research focuses on consumer behavior, particularly how social contexts and digital tools influence decision-making and product evaluations. Dr. Bhargave’s academic journey includes prior faculty positions at the University of Texas at San Antonio before joining Imperial College London. He teaches across programs including MBA, Executive Education, and Pre-experience Masters, emphasizing practical application of marketing principles. His research explores two primary areas: (1) the impact of social environments on product preferences, analyzing shared versus solitary consumption experiences, and (2) how online technologies reshape consumer decision-making processes. Key topics include hedonic judgments, numerical processing in choices, and the psychological effects of digital cues like 'cloud' reminders. His publications span journals such as Journal of Consumer Research and Psychological Science , reflecting a strong focus on behavioral economics and consumer psychology. Notable themes include 'collective satiation,' 'cue-of-the-cloud effects,' and the role of round numbers in consumer perceptions of product longevity. Dr. Bhargave has advised students such as JORGE PENA-MARIN and Nicole Votolato Montgomery. While no scientific awards are explicitly listed, his work contributes significantly to marketing theory and practice. His research and teaching underscore the intersection of technology, social dynamics, and consumer behavior.
Xihong Lin is a Professor of Statistics at Harvard University and a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health. She is a distinguished academic, holding membership in both the National Academy of Sciences and the National Academy of Medicine. Her research focuses on scalable statistical inference for big data, statistical machine learning, causal inference, and integrative data analysis, with applications in genomics, public health, and precision medicine. Lin’s work addresses challenges in analyzing large-scale genomic and multi-ancestry data, including methods for rare variant association testing, ancestry-adjusted sample analysis, and scalable computing frameworks. Her contributions span biobank studies (e.g., UK Biobank, TOPMed) and clinical applications in lung cancer, cardiovascular health, and smoking cessation. Her scientific awards reflect her leadership in statistical genetics and public health. Key research trends include leveraging single-cell sequencing for functional genomics, developing ensemble machine learning methods for health subtyping, and enhancing polygenic risk prediction across diverse populations. Lin’s methodologies prioritize interpretability and scalability, enabling impactful analyses of complex observational and genomic datasets. Awards: Member, National Academy of Sciences; Member, National Academy of Medicine Her grants and advising efforts focus on interdisciplinary collaborations, bridging statistics, AI, and domain sciences. Lin leads initiatives to improve genomic data management and ethical use of federated data (e.g., FADI framework). She is affiliated with labs advancing statistical genetics and cloud-based workflows (e.g., STAAR workflow).
Stefano Leonardi is a Full Professor in the Department of Computer, Control and Management Engineering Antonio Ruberti at Sapienza Università di Roma. His research focuses on Algorithm Theory, Algorithms and Data Science, and Economics and Computation. He leads the ERC Advanced Grant project AMDROMA, exploring algorithmic mechanisms for online markets. He has held roles as Conference Chair for STOC 2021, WWW 2015, and FUN 2018, and coordinates the Sapienza School of Advanced Studies (2016-2018). His work spans approximation algorithms, online algorithms, and mechanism design. Awards include the ERC Advanced Grant and EATCS Fellowship. His research interests emphasize foundational algorithmic problems in web-based markets, leveraging rigorous design and large-scale data analysis. Recent projects include ALGADIMAR (PRIN 2019-2022) for digital market algorithms. He chairs the Highlights of Algorithms conference series and serves on program committees for top venues like EC, ICALP, and SODA. His lab focuses on web algorithmics and data mining, addressing challenges in online labor markets and fair division. Leonardi's academic contributions include over 100 publications, with recent work on fair algorithms, prophet inequalities, and mechanism design in auctions. He has pioneered methods for submodular optimization, online learning, and multi-agent systems. Grants and awards reflect his leadership in bridging theory with real-world applications, particularly in digital economies. Grants: ERC Advanced Grant (2018-2023), PRIN ALGADIMAR (2019-2022) Leadership: Chair of ACM STOC 2021, WWW 2015, and 9th FUN Conference Labs/Teams: Laboratory on Web Algorithmics and Data Mining Key Projects: AMDROMA (algorithmic mechanisms), ALGADIMAR (digital markets)
Wesley Willett is an Associate Professor in the Department of Computer Science at the University of Calgary, holding the NSERC CRC II Chair in Visual Analytics. His primary research focuses on information visualization, human-computer interaction, and new media applications. He leads the Data Experience Lab and Interactions Lab, exploring innovative methods for data representation and interaction in augmented/virtual reality environments. Education includes a B.S. in Computer Science from the University of Colorado (2006) and a Ph.D. in Computer Science from UC Berkeley (2012). His work bridges technical innovation with user-centered design principles, emphasizing ethical considerations in data visualization and inclusive representation. Key research contributions include: spatial visualization techniques for large environments, gesture-based interfaces for AR/VR, and physical data representations through projects like Cetonia (swarm robotics visualization) and Data Embroidery. His work has been recognized with Best Paper awards at CHI 2015 and Pervasive 2010. Current research emphasizes immersive analytics, wearable visualization systems, and demographically diverse anthropographics. He collaborates with urban designers, neurologists, and environmental scientists to apply visualization in diverse domains like epilepsy surgery planning and air quality monitoring.
Zoran Kalinic serves as an Assistant Professor at the Faculty of Economics, University of Kragujevac, where he teaches Electronic Business since October 2012. Previously, he worked at the Faculty of Mechanical Engineering in Kragujevac from 1996 to 2005, and joined the Faculty of Economics in February 2005 as an assistant in Information Systems, later teaching Information Technology and Electronic Business from 2009 onward. Doctorate (2012): Faculty of Engineering, University of Kragujevac, specializing in information systems development and mobile communications Postgraduate studies: Faculty of Mechanical Engineering in Kragujevac (completed with average grade of 10) Bachelor's degree: Faculty of Mechanical Engineering in Kragujevac (1996, average grade 9.43) Professor Kalinic's research focuses on digital transformation and its economic implications, with particular expertise in mobile commerce, electronic business systems, digital payment technologies, and consumer behavior in online environments. His work frequently employs advanced analytical methods including artificial neural networks, structural equation modeling, and hybrid analytical approaches to investigate technology adoption patterns and digital marketplace dynamics. He has conducted extensive research on Serbian digital markets, including studies on mobile payment systems, e-commerce development barriers, and real estate price prediction using AI techniques. His publication record demonstrates a clear progression from foundational technology acceptance research toward more complex analyses of digital ecosystems, with recent work examining influencer marketing effects on TikTok, biometric payment systems, and gig economy measurement in Serbia. The integration of artificial intelligence methodologies with traditional consumer behavior theories represents a distinctive feature of his scholarly approach. Professor Kalinic maintains active international academic engagement through short study visits to institutions including the University of Udine, Vienna University of Economics, University of Maribor, Krakow University of Economics, Coventry University, Polytechnic of Turin, and Comenius University in Bratislava. He spent six weeks at the University of Maribor in 2007 through a Tempus IMG grant and served as a visiting lecturer at the Krakow University of Economics in 2012. Author/co-author of over 60 papers in international and domestic journals and conferences Participant in multiple scientific research and professional projects Recipient of academic awards during studies from University, Faculty, Ministry of Science and Technology of Serbia, Embassy of Norway, WUS-Austria, Zastava-Yugo Automobiles, and Kragujevac City Assembly His professional development includes a month-long visit to the Faculty of Informatics at the University of the Basque Country in San Sebastian (2004) and ongoing collaboration with regional and European academic institutions. Professor Kalinic's research bridges theoretical frameworks with practical applications in the Serbian and Western Balkan digital economy context.
Teng-Fong Wong is a Research Professor in the Department of Geosciences at Stony Brook University, where he has been a faculty member since 1982. His research focuses on the intersection of rock mechanics, earthquake processes, and environmental applications, making significant contributions to understanding deformation mechanisms in geological materials. Education: Sc.B., Brown University, 1973 M.S., Harvard University, 1976 Ph.D., Massachusetts Institute of Technology, 1981 Research Interests: Professor Wong's research centers on rock mechanics with emphasis on earthquake mechanics, energy resources, and environmental applications. He investigates both phenomenological and micromechanical aspects of rock deformation and fluid flow using an integrated approach combining high-pressure deformation experiments, quantitative microstructure characterization, and theoretical analysis. His work spans brittle-ductile transitions in porous rocks, permeability evolution, strength properties of fault zone materials from SAFOD and TCDP drilling projects, and submarine groundwater discharge systems. Publication Trends: Wong's recent publications (2006-2008) demonstrate a consistent focus on strain localization mechanisms in porous rocks, particularly examining compaction bands and deformation bands in sandstones. His work integrates advanced imaging techniques (X-ray radiography, CT scanning) with mechanical testing to understand the micromechanics of rock failure. A significant thread connects his research on fault zone properties from major drilling projects (SAFOD, TCDP) with fundamental rock deformation processes. Scientific Recognition: U.S. Patent 6,874,371 for Ultrasonic Seepage Meter (2005) U.S. Patent 7,107,859 for Ultrasonic Seepage Meter (2006) Co-author of "Experimental Rock Deformation - The Brittle Field" (2nd Edition, Springer-Verlag, 2005) Professional Activities: Professor Wong maintains an active international research profile with numerous visiting appointments including at Australian National University, MIT, ETH Zurich, and institutions in China and France. His work involves extensive collaboration with USGS and international research teams on major fault zone drilling projects. He has developed specialized equipment like the ultrasonic seepage meter for measuring submarine groundwater discharge. Research Infrastructure: Wong's laboratory utilizes advanced capabilities including high-pressure deformation equipment, 3D visualization through laser scanning confocal microscopy and synchrotron microCT, and integrates these with analytic modeling and numerical simulation techniques (finite element and discrete element methods) to investigate micromechanics of dilatant and compactant failure in geological materials.
Param Vir Singh is the Carnegie Bosch Professor of Business Technologies and Marketing and Associate Dean for Research at Carnegie Mellon University’s Tepper School of Business. His research examines how AI and algorithmic systems reshape markets, influence consumer trust, and redefine platform strategy, pricing, and fairness. He leads the Collaborative AI Initiative at CMU, focusing on adaptive learning environments for business education. Affiliations : Carnegie Mellon University, Tepper School of Business Editorial Roles : Senior Editor at Information Systems Research , Associate Editor at Management Science Research Themes : AI ethics, algorithmic fairness, platform economics, consumer behavior, and generative AI applications. Key Research Contributions : His work spans algorithmic pricing, bias mitigation, sharing economy dynamics, and AI-driven inequality analysis. Articles often intersect computer science, economics, and marketing. Scientific Recognition : INFORMS Information Systems Society Distinguished Fellow Award Don Lehmann Award (Winner) John DC Little Award Don Morrison Long-Term Impact Award (Finalist) AIS Senior Scholar's Best Paper Award (Winner) Academic Leadership : Served as Director of the PNC Center for Financial Services Innovation, securing $5.5M for research programs. Mentored PhD students now at Harvard, NYU, Michigan, and other top institutions.
Elena Karahanna is a Professor at the Terry College of Business , University of Georgia. Her research spans Artificial Intelligence , Health Information Technology , and the social and algorithmic implications of digital platforms . PhD in MIS, University of Minnesota (1993) MBA in Business Administration, Lehigh University (1988) BS in Computer Science, Lehigh University (1986) Her work examines how conversational agents and social bots reshape e-commerce and social media, the algorithmic coordination in organizations, and the integration of IT in healthcare systems . She has contributed to foundational theories like the Needs-Affordances-Features (NAF) framework for social media analysis. Recent publications highlight her focus on digital governance (e.g., firm-sponsored online communities), chatbot applications in public health (e.g., pandemic response), and privacy concerns in online social networks. Her research often bridges information systems and marketing (e.g., hyper-privacy and dark web insights). Scientific Awards Terry College of Business Service Award, 2024 INFORMS Information Systems Society President's Service Award, 2023 MIS Quarterly Best Paper Award, 2022 AIS Leo Award for Exceptional Lifetime Contributions, 2020 AIS Fellow, 2012 Karahanna has served as Senior Editor for MIS Quarterly , Information Systems Research , and Journal of AIS . She co-founded the Doctoral Student Corner (2014) and the Senior Scholar Consortium (2004), emphasizing her leadership in academic mentorship. She has taught courses on theory development and business intelligence , and her international teaching includes stints in Hong Kong, Cyprus, Singapore, and Australia .
Gedas Bertasius is an Assistant Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. Previously, he served as a postdoctoral researcher at Meta AI (Facebook AI) and earned his PhD in Computer Science from the University of Pennsylvania. His academic journey began with a bachelor’s degree in Computer Science from Dartmouth College. Dr. Bertasius specializes in computer vision and machine learning with specific interests in: Video understanding First-person vision (egocentric vision) Human behavior modeling Multimodal deep learning Transfer learning Computer vision for sports analytics Video+robotics integration His research produces practical frameworks like Video ReCap for hierarchical captioning of long videos, SiLVR for language-based video reasoning, and BASKET for fine-grained skill estimation. He focuses on developing models that can process videos across multiple temporal granularities while maintaining computational efficiency. Key research themes in his work include: Recursive video processing architectures Space-time attention mechanisms Generative video modeling LLM integration with vision systems 3D-aware representation learning Continual learning for video QA He has received notable recognition, including: CVPR 2024 Egocentric Vision (EgoVis) Distinguished Paper Award CVPR 2020 Best Paper Award Nomination First Place at CVPR 2025 Multi-Discipline Lecture Understanding Workshop Dr. Bertasius collaborates with prominent researchers like Mohit Bansal and Lorenzo Torresani . His recent publications demonstrate expertise in advancing video-language models, with applications in semantic alignment, temporal grounding, and cross-modal reasoning. For detailed information about his research, publications, and ongoing projects, please visit his official website .
Dr. Ronita Bardhan is Associate Professor of Sustainable Built Environment at the University of Cambridge , where she leads the Cambridge Sustainable Design Group and serves as Director of Research & Deputy Head of the Department of Architecture . She holds courtesy roles at Cambridge Public Health and the Department of Computer Science and Technology , and is a Fellow at Selwyn College . Education: BArch, MCP, MA, PhD (Urban Engineering) Her research intersects built environment , climate change , and public health , focusing on data-driven strategies for precision prevention of health and energy burdens. She pioneers algorithmic approaches to identify decarbonisation potential in buildings and urban areas, with a particular emphasis on gender-inclusive climate adaptation in the Global South. The 15 most recent articles span topics such as urban cooling with tree canopies , heatwave impacts on social systems , and machine learning applications for building energy efficiency . Her work addresses climate justice , hybrid workspace design , and thermal comfort in low-income housing . Awards: Top 50 Finalist Women in Engineering, UK 2024 Exceptional Woman of Excellence, Women Economic Forum Felicitated by Ministry of Health, Maharashtra, India She advises World Bank and ADB on affordable housing and climate resilience, and chairs the Research Ethics Committee at the Department of Architecture. Her lab, the Sustainable Design Group , develops solutions for health and low-carbon potential in built environments.
Riccardo Raheli is a Full Professor at the University of Parma , Department of Engineering and Architecture, with a career spanning over three decades in Information and Communication Technologies (ICT). He has served as Chair of the Councils for Telecommunications and Communication Engineering programs, and as representative of the University of Parma in CNIT and its Members' Assembly. Education: Laurea in Electronic Engineering (University of Pisa, 1983), M.Sc. in Electrical and Computer Engineering (University of Massachusetts, 1986), Postgraduate Diploma (Scuola Superiore Sant'Anna, 1987) Key Roles: President of Degree Councils (2002-2018), CNIT Committee Member (2000-2005), Editorial Board member for IEEE Transactions, Springer and MDPI journals His research bridges telecommunications , digital signal processing , and healthcare applications , producing extensive international publications and industrial patents. He has co-authored monographs including Detection Algorithms for Wireless Communications (Wiley, 2004) and LDPC Coded Modulations (Springer, 2009). Recent article trends show interdisciplinary work in automotive stress monitoring (IoT/Matlab-based systems), video processing for healthcare (neonatal seizures, respiratory monitoring), and acoustic field control (microphone virtualization, personal sound zones). His work spans machine learning applications in automotive systems, stochastic acoustic modeling , and power-line communications . Scientific Leadership : Co-Chair for IEEE conferences (ICC 2010, GLOBECOM 2011, ISPLC 2020) Editorial roles in 7+ international journals Grants & Collaborations : Led industrial patents in communications systems Coordinated CNIT Technical Reports series (2025) He teaches Wireless Communications and Digital Signals Laboratory , emphasizing Matlab/Simulink proficiency. His laboratory sessions focus on practical implementation of signal processing algorithms, requiring full software installation on personal devices.
SangHyung Ahn is a Lecturer at the School of Civil Engineering , University of Queensland (UQ), since 2017. He joined UQ as a postdoctoral research fellow in 2015 after earning his PhD in Civil Engineering (Construction Engineering and Management) from Purdue University, USA. Prior to his academic career, he worked as an assistant manager at Hyundai Engineering and Construction Co., Ltd. (2003-2007) and holds an MBA in international business from Hanyang University and a B.Sc in Civil Engineering from Korea University. Research Focus: Construction process modelling with virtual reality, decision support systems for construction, automation of data-driven simulation modelling, sensor-based operations analysis, and integration of Building Information Modelling (BIM). Teaching: Coordinates undergraduate courses Introduction to Project Management (CIVL3510) and Construction Engineering Management (CIVL4522) . Research Trends: His recent publications highlight interdisciplinary work in transportation engineering, structural design, and AI-driven simulation tools. Key themes include application of machine learning to car-following models, drone-based vehicle identification, and optimization of public transport systems using agent-based simulations. Supervision: Available for supervision, with completed supervision of PhD and Master’s theses on topics such as BIM-LCA integration, pedestrian trajectory analysis, and AI-driven driving behavior models.
John Harry Evans is the III Katz Alumni Professor of Accounting at the Department of Accounting, Katz School of Business, University of Pittsburgh. His research focuses on economic perspectives of accounting phenomena, analytical models of incentives, experimental studies in managerial and tax reporting, and empirical investigations of healthcare incentives. He teaches courses in Financial Accounting, Financial Statement Analysis, Managerial Accounting, and Strategic Cost Management. Research spans incentive design, corporate governance, healthcare accounting, and empirical methodologies. Recent publications address CEO turnover, physician compensation, tax reporting ethics, and organizational incentive structures. Awarded multiple honors including the Outstanding Management Accounting Paper Award (2012), Provost Award for Excellence in Mentoring (2011), and multiple Best Paper Awards across journals. Active in professional service as a financial consultant to the Department of Defense and expert witness in legal cases. Designed financial analysis training programs for healthcare managers at University of Pittsburgh Physicians and Highmark Insurance Company.
Hannu Saarijärvi is a Professor in the Faculty of Management and Business at Tampere University, specializing in Marketing. His research bridges consumer behavior, retail innovation, and data-driven health studies. Based in Tampere University's City Centre Campus, he explores transformative retailing and societal impacts of consumer data. University: Tampere University School: Faculty of Management and Business Department: Business Studies Email: hannu.saarijarvi@tuni.fi His research focuses on consumer behavior in omnichannel and second-hand retailing, data analytics using loyalty card datasets, and health research linking maternal experiences to dietary patterns. Recent studies examine sustainable diets , alcohol consumption dynamics , and food waste reduction . Key article trends highlight loyalty card data applications in health informatics , retail transformation , and sustainability . Collaborative studies with Finnish institutions analyze population-level consumption behaviors, legislative impacts, and digital service innovations. Professor Saarijärvi's work emphasizes value co-creation , customer experience , and strategic digitalization in retail contexts, with practical implications for public health and business models.
