جستجوی استاد راهنمای دانشگاهی

Mandy Goramمشاهده پروفایل

پژوهشگر

• Adaptive Learning Systems
• Learning Analytics
• Context-Based Adaptive Systems
• +۵ مورد دیگر

Mandy Goram is a researcher at FernUniversität in Hagen affiliated with the Faculty of Mathematics and Computer Science and Cooperative Systems research group. She holds an M.Sc. in Practical Computer Science and B.Sc. in Business Information Systems from the same institution and has lectured at Informatica Feminale summer school since 2015. Her educational background includes: M.Sc. in Practical Computer Science specializing in Humans and Computers, Recommender Systems, and Intelligent Assistants B.Sc. in Business Information Systems specializing in Human-Computer Interaction and Database Systems Germany Scholarship recipient Goram's research centers on adaptive personalized learning environments (APLE project) supporting self-regulation in distance education. She develops context-based adaptive assistance systems using machine learning, NLP, and information extraction while prioritizing GDPR compliance. Her work bridges AI, multi-agent systems, and human-computer interaction with applications in conversational interfaces and learning analytics. Analysis of her 11 publications (2013-2020) reveals consistent focus on context-aware adaptive systems integrating legal requirements, particularly GDPR. Key trends include explainable AI for educational settings, privacy-preserving collaboration environments, and practical applications in business intelligence and customer experience management across insurance and banking sectors. No scientific awards were documented in the source material. She has supervised three theses: Stefan Walter's 2021 Master's on GDPR-compliant conversation partner identification, Yannik Worthmann's 2020 Bachelor's on context-based learning materials under GDPR, and Arda Treijner's 2019 Bachelor's on user data tracking for meinDorf55+. Goram leads the ongoing APLE project funded by FernUniversität Hagen's Research Focus DDLL with a 36-month duration. As part of the Cooperative Systems research group, she collaborates with Dirk Veiel on context-based adaptive systems emphasizing 'Compliance by Design' principles. Her work integrates technical innovation with regulatory frameworks through multi-agent architectures and deep learning applications.

Koushik Sinhaمشاهده پروفایل

دانشیار

• Mobile Computing
• Wireless Ad hoc Networks
• Wireless Sensor Networks
• +۶ مورد دیگر

Koushik Sinha is an Associate Professor at the School of Computing, Southern Illinois University Carbondale, where he directs the Complex Networks & Applications Lab. With extensive experience spanning academia and industry—including roles at Qatar Computing Research Institute, Hewlett-Packard Labs, and Honeywell—he brings practical expertise to his research in wireless networking, complex systems, and human-machine collaboration. His work bridges theoretical foundations with real-world applications across multiple domains. Education Ph.D. in Computer Science, Jadavpur University, India (2007) M.S. in Computer Science, Clemson University, USA (2003) B.Tech. in Computer Science, Kalyani Government Engineering College, India (2001) Research Focus Dr. Sinha's research centers on energy-efficient wireless communication protocols, 5G/6G networking, and complex network analysis. His "Communication through Silence" paradigm represents a novel approach to minimizing energy consumption in wireless networks. Current projects address critical challenges in ultra-dense 5G deployments, smart city infrastructure, and the CrowdCloud platform for hybrid human-machine computing. His work increasingly intersects with societal challenges in rural connectivity, agricultural technology, and public health. Publication Trends Analysis of Dr. Sinha's recent publications reveals a strategic progression from core wireless networking research toward interdisciplinary applications. While maintaining expertise in energy-efficient protocols and network optimization, his work now addresses smart city infrastructure, rural broadband expansion, precision agriculture, and pandemic response systems. His publications demonstrate growing integration of machine learning techniques and increasing focus on real-world impact in underserved communities. Scientific Recognition Senior Member, IEEE Grand Prize Winner of 9th OSS World Challenge for AIDR (2015) N.V. Gadadhar Memorial Award from IETE (2011) Young Scientist Award from Indian Science Congress Association (2009) Mentorship and Leadership Dr. Sinha has successfully guided multiple Ph.D. and MS students through research in wireless networking and complex systems. His leadership extends to conference organization as General Co-Chair for IEEE ANTS 2018 and TPC Co-Chair for previous editions. Within his department, he has shaped curriculum as Course Coordinator for key offerings including Distributed Systems, Mobile and Wireless Computing, and Computer Architecture. Research Infrastructure The Complex Networks & Applications Lab under Dr. Sinha's direction supports cutting-edge research in wireless protocols, network optimization, and hybrid computing systems. Current projects include 5G network optimization, ultra-dense base station placement, and the CrowdCloud platform for human-machine collaborative computing, providing students with opportunities to address real-world challenges in smart cities, rural connectivity, and emergency response systems.

• Social Science
• Sociology
• Behavioral Studies
• +۴ مورد دیگر

Jason Radford is a Principal Research Scientist at Northeastern University and founder of the Social Design Lab. He joined Northeastern in 2014 as part of David Lazer’s lab, co-founding Volunteer Science—a platform for online behavioral studies that evolved into a global SaaS company. Primarily based at The Roux Institute in Portland, ME (100 Fore St), he operates in a remote capacity with additional offices in Boston and London. Education Ph.D. in Sociology, University of Chicago: Focused on organizational effectiveness Research Interests Radford’s work bridges social science methodology , big data analytics , and digital experimentation . He pioneers techniques for non-probability sampling, machine learning integration in social research, and platform-based behavioral studies. His research emphasizes translating theoretical frameworks into scalable solutions for societal challenges through scientific entrepreneurship. Publication Trends His publications (2016-2025) show a clear evolution from foundational big data concepts ( Data ex Machina , 2017) to methodological innovations in survey science (2025). A consistent thread is the critical examination of data quality in digital-era research, with increasing focus on sustainable implementation of scientific findings in real-world contexts. Labs and Initiatives As founder of the Social Design Lab, Radford leads ventures including Disinformation Monitor, Current Argument Optimization, Equitable Relationships App, and Volunteer Science. The lab partners with faculty, students, and practitioners to transform research into impactful solutions, emphasizing scientific entrepreneurship and translational science.

Isaac Lemus Aguilarمشاهده پروفایل

استاد پژوهش

• Business Model Development
• Digital Transformation
• Circular Economy
• +۵ مورد دیگر

Dr. Isaac Lemus Aguilar serves as Research Professor in the Department of Entrepreneurship and Technological Innovation at EGADE Business School, Tecnológico de Monterrey. His academic career spans multiple international institutions including Copenhagen Business School, Polytechnic University of Madrid, and Universidad Autónoma de Madrid. PhD in Management and Economics, Politecnico di Milano (Italy) European Doctorate in Industrial Management (cum laude), Polytechnic University of Madrid (Spain) Master's in Strategic Project Management, HWU Edinburgh Business School (UK) Master's in Management, Umeå University (Sweden) Bachelor's in Administrative Computer Systems, Tecnológico de Monterrey (Mexico) His research focuses on business model innovation , digital transformation , and circular economy frameworks. He examines how organizations develop value-adding solutions through strategic innovation processes, with particular emphasis on sustainable business practices and technology-driven transformation across sectors including healthcare, energy, and automotive industries. His publication portfolio reveals consistent focus on sustainability-driven innovation (40% of recent works), digital transformation (30%), and consulting firm innovation (20%), with emerging interest in eHealth systems . Key journals include Sustainability , Journal of Manufacturing Technology Management , and European Journal of International Management . EU-SPRI Circulation Award (2020 & 2018) Educational Innovation Award (Polytechnic University of Madrid, 2019) PhD Cum Laude (Polytechnic University of Madrid, 2019) CONACyT Doctoral Fellowship (2014-2019) Erasmus Mundus Doctoral Award (2013) Prior to academia, Lemus-Aguilar held significant industry roles as business consultant at KPMG and NTT Data (formerly Everis), strategic projects director at SAT and PGR, and vice president of Erasmus Mundus Association Latin American Chapter. His practical experience spans telecommunications, banking, insurance, government, education, and business services sectors, informing his applied research approach. He maintains active research collaborations across Europe, Latin America, and Asia through his extensive academic network.

Foutse Khomhمشاهده پروفایل

استاد

• software maintenance and evolution
• cloud engineering
• machine learning systems engineering
• +۳ مورد دیگر

Foutse Khomh is a Full Professor at Polytechnique Montréal, holding multiple prestigious chairs including Canada Research Chair Tier 1, Canada CIFAR AI Chair, and FRQ-IVADO Research Chair. He leads the SWAT Lab (Software Analysis and Testing) at Polytechnique Montréal and has established himself as a leading researcher in software engineering for AI systems. Dr. Khomh received his Ph.D. in Software Engineering from the University of Montreal in 2011. His research has been recognized with numerous awards including four ten-year Most Influential Paper Awards and eight Best/Distinguished Paper Awards. He was also awarded the CS-Can/Info-Can Outstanding Young Computer Science Researcher Prize for 2019. His research focuses on software maintenance and evolution, cloud engineering, machine learning systems engineering, empirical software engineering, software analytics, and dependable and trustworthy AI/ML. Dr. Khomh has published over 200 conferences and journal papers, demonstrating his prolific contribution to the field of software engineering, particularly in the context of AI and machine learning systems. His recent publications show a strong emphasis on trustworthy AI, debugging deep learning systems, and addressing challenges in LLM-generated code. Four ten-year Most Influential Paper Awards Eight Best/Distinguished Paper Awards CS-Can/Info-Can Outstanding Young Computer Science Researcher Prize (2019) Canada Research Chair Tier 1 Canada CIFAR AI Chair FRQ-IVADO Research Chair NSERC Arthur B. McDonald Fellow Dr. Khomh has mentored numerous students and researchers in the field, serving as a key advisor in the development of next-generation software engineering researchers. He has also secured significant research funding through his various chairs and fellowships. His leadership extends to major research initiatives including the DEpendable Explainable Learning (DEEL) project and the NSERC CREATE SE4AI training program, which focus on developing trustworthy AI systems and training future AI software engineers. He leads the SWAT Lab (Software Analysis and Testing Lab) at Polytechnique Montréal and is actively involved in the Confiance.ia Quebec initiative on Trustworthy AI, which aims to establish best practices for trustworthy AI development. His lab focuses on empirical studies of software systems, particularly those involving machine learning components, and develops tools and techniques for improving software quality and reliability.

• adaptive systems
• altruism
• applied empirical methods
• +۱۲ مورد دیگر

Nikos Askitas serves as Coordinator of Data and Technology at the Institute of Labor Economics (IZA) in Bonn, Germany, where he leads both the Research Data Center (IDSC) and ICT unit since joining in 2000. His dual role bridges technical infrastructure management and cutting-edge research in labor economics and social science. His research spans causal machine learning , epidemic disease modeling , big data analytics , and behavioral macroeconomics , with notable contributions to forecasting methodologies and web-based data applications. He develops novel approaches in opinion dynamics, game theory, and adaptive systems while addressing real-world challenges like pandemic response and technology-labor interactions. Recent publications reveal a strong trend toward AI-driven economic analysis , particularly examining generative AI's impact on scientific communication and labor markets. His work consistently integrates web data and real-time indicators with traditional economic modeling, emphasizing practical policy applications in consumption tracking, referendum forecasting, and mobility pattern analysis. His scientific recognition includes: CESifo Research Fellow in Economics of Digitisation Academic Editor for PLoS ONE (Economics section) As infrastructure leader, he oversees IZA's research data ecosystem and technological operations, enabling large-scale empirical studies while advancing methodological frontiers through hands-on machine learning pedagogy for social scientists. His current projects focus on GenAI implications, nowcasting techniques, and causal inference frameworks.

Daniel Chenمشاهده پروفایل

استادیار

• Operations Strategy
• Online Platforms
• Gig Economy
• +۵ مورد دیگر

Daniel Chen is an Assistant Professor of Business Analytics at Boston College's Carroll School of Management. His research focuses on online platform strategies, gig economy dynamics, and human-AI interaction. He holds a Ph.D. in Operations Management from the Wharton School (University of Pennsylvania) and degrees from the University of Southern California (BS Economics/Mathematics, MS Mathematical Finance). Education: BS in Economics/Mathematics, University of Southern California MS in Mathematical Finance, University of Southern California Ph.D. in Operations Management, Wharton School, University of Pennsylvania Research Interests: Chen analyzes strategic behavior in gig economies, algorithmic pricing transparency, and network-based solutions for online ratings. His work combines machine learning, structural estimation, and economic modeling to address platform efficiency, labor market dynamics, and regulatory challenges. Key Findings: His studies reveal that enabling gig workers to multihome (switch platforms) boosts earnings and service levels, while inefficient routing reduces worker utilization. He also highlights risks of prediction errors in causal inference using machine learning. Awards: Research Fellowship, Coalition for Equity and Opportunity (2023-2025) Finalist, INFORMS Behavioral Operations Management Best Working Paper Award (2023) Advising & Grants: Collaborates with driver analytics firms on empirical studies. Advises on gig economy policy and algorithmic fairness. Active in securing research fellowships through the Mack Institute and Coalition for Equity and Opportunity.

Jay Tanejaمشاهده پروفایل

دانشیار

• Infrastructure Measurement and Analytics
• IoT and Embedded Systems
• Machine Learning Applications
• +۴ مورد دیگر

Jay Taneja is an Associate Professor in the Department of Computer Science at the Manning College of Information and Computer Sciences, University of Massachusetts Amherst. He holds an adjunct appointment in the Electrical and Computer Engineering Department. His research focuses on applying computing tools like IoT, machine learning, and remote sensing to measure and improve infrastructure systems in both developed and developing regions, including energy grids, transportation, water, and sanitation. Dr. Taneja leads the STIMA Lab, which explores innovative solutions for infrastructure challenges through interdisciplinary projects such as predicting electricity consumption growth in low-income communities, enhancing grid reliability via smartphone-based sensing, and using satellite imagery to assess road quality. He has advised over 30 students, including PhD candidates and undergraduates, and collaborates with institutions like Columbia University and the University of Washington. His work has been published in top venues like BuildSys, IEEE SmartGridComm, and Applied Energy. Notable contributions include developing frameworks for subsidy estimation in rural electrification and detecting power outages using crowdsourced data. Awards include the Best Paper Runner-Up at BuildSys 2023 and recognition for innovative sensor network designs. Taneja earned his PhD and MS in Computer Science from UC Berkeley and a BS in Electrical & Computer Engineering from The Ohio State University. He teaches courses on decarbonization, energy networks, and engineering fundamentals.

HENG Cheng Suangمشاهده پروفایل

دانشیار

• Digital Transformation
• Platforms & Innovation
• Computational Social Science
• +۴ مورد دیگر

Dr. HENG Cheng Suang is an Associate Professor and Deputy Head of the Department of Information Systems and Analytics at the National University of Singapore (NUS) School of Computing. He holds a Ph.D. from Stanford University and has extensive experience in IT strategy, digital transformation, and entrepreneurship research. His roles include Chair of NUS Teaching Academy and membership in editorial boards of MIS Quarterly and IEEE Transactions on Engineering Management . Education: Ph.D. (Organization, Technology & Entrepreneurship, Stanford University); M.Sc. and B.Sc. (Computer & Information Sciences, NUS). Research focuses on IT strategy, digital platforms, and organizational innovation. Key areas include fintech empowerment (e.g., Yu'E Bao case study), signaling effects of subsidies on IPOs, and social media dynamics. Over 50 peer-reviewed publications span journals like JAIS , MIS Quarterly , and conferences such as ICIS and ECIS. Awarded multiple NUS Teaching Excellence Awards (2010–2022) and SOC Honors. Advised PhD student Li Ding, now at Nanjing University. Active in editorial and committee roles including NUS Overseas Colleges Steering Committee and Departmental Ethics Review Committee. Labs/teams: Collaborates with industry on digital economy projects. Research highlights include analyzing government subsidy impacts on startups and exploring paradoxes in e-commerce word-of-mouth dynamics.

Pu Yanمشاهده پروفایل

استادیار

• Computational Social Science
• Digital Media Platforms
• Algorithmic Governance
• +۳ مورد دیگر

Dr. Pu Yan is an Assistant Professor at Peking University, China, specializing in computational social science, digital media platforms, and algorithmic governance. Her research addresses digital divides, societal impacts of AI, and Chinese internet dynamics. She holds a DPhil and MSc from the Oxford Internet Institute (OII), where she also served as a Research Associate. Her work bridges theory and practice, focusing on ethical algorithmic governance and digital inequalities. Dr. Yan’s forthcoming book, China’s Algorithmic Society , explores algorithmic influence on public discourse and daily life. Education: DPhil and MSc in Social Science of the Internet from the OII, University of Oxford. Prior to Peking University, she conducted research at the OII, contributing to studies on climate skepticism and right-wing populism. She teaches courses on media-society relations, data storytelling, and computational methods. Research Interests: Everyday information behaviors, emerging social media platforms, public understanding of AI, computational social science, and digital divides. She is affiliated with research groups like the Digital Economic Security Lab and Fair Digital Economies Governance. Her recent work analyzes climate policy in sub-Saharan Africa, energy access, and carbon removal technologies. Articles focus on topics such as renewable energy scaling, urban energy poverty, and climate resilience in Kenya and China. She advocates for equitable digital transformation and ethical tech governance through interdisciplinary approaches.

Thomas Ludwigمشاهده پروفایل

استاد

• Human-Centered Technology Design
• Immersive Teaching & Learning
• Assistance Systems
• +۶ مورد دیگر

Univ.-Prof. Dr. Thomas Ludwig is a Professor of Educational Technologies for Digital Transformation at FernUniversität in Hagen, affiliated with the interdisciplinary research focus 'Work – Education – Digitalization'. He previously held a Junior Professorship in Business Informatics (Cyber-Physical Systems) at the University of Siegen. His research focuses on human-centered technology design, immersive learning, and assistive systems, with a strong emphasis on digital transformation in education and industry. Ludwig’s work bridges HCI, CSCW, and crisis management, addressing challenges like crowdsourcing, IoT applications, and SME digitalization. Education: B.Sc./M.Sc. in Business Informatics from University of Siegen and University of Newcastle (Australia); Ph.D. on 'Designing ICT Tools for Researching Information Infrastructures' (summa cum laude). Research Interests: Cyber-physical systems, crowdsourcing dynamics, crisis informatics, and end-user development. He led projects like the Mittelstand 4.0 Competence Center, focusing on SME digitalization, and pioneered studies on 3D printer appropriation and AR applications in manufacturing. Publications (2023 highlights): Explored gamification in sustainable food apps, voice messaging interfaces, and conversational agents for 3D printers. His work spans ACM, CHI, and journal articles in Computer Supported Cooperative Work and International Journal of Gastronomy and Food Science . Awards: Best Short Paper (2021), IHK Dissertation Prize (2017), Artur-Woll-Preis, and pwc-Preis for academic excellence. He has organized over 20 international workshops at ECSCW, CSCW, and CHI, focusing on topics like crowd dynamics and industrial IoT. Grants/Advising: Coordinated Mittelstand 4.0 initiatives, led EU-funded projects (e.g., EMERGENT, KOKOS), and advised SMEs on APS systems. His labs focus on augmented reality, conversational agents, and crisis management technologies.

• Social Computing Systems
• Algorithmic Fairness
• Privacy and Security in Social Media
• +۳ مورد دیگر

Krishna P. Gummadi is a Professor and Scientific Director at the Max Planck Institute for Software Systems (MPI-SWS) , leading the Networked Systems Research Group. His work bridges computer science and social science, focusing on social computing systems that network humans and computers at societal scale. Academic Leadership: Faculty (Scientific Director), Head of Networked Systems Research Group Key Research Areas: Algorithmic fairness, privacy in social media, distributed systems, human-centered machine learning His research methodology combines user-centric studies through large-scale observational analysis, data-centric studies using statistical learning and NLP, and systems-centric approaches for practical deployments like information diet tools and fraud detection services . Current work explores crowdsourcing systems , peer-to-peer networks , and trusted cloud computing . Scientific Awards & Recognitions: CNIL-INRIA Privacy Runners-Up Award (2018) Casper Bowden PET Runners-Up Award (2018) SIGCOMM Test of Time Award (2007) Students & Postdocs: Current: Junaid Ali, Reza Babaei, Nina Grgić-Hlača, Preethi Lahoti, Johnnatan Messias, Till Speicher Former: Asia J. Biega (Microsoft Research), Przemyslaw Grabowicz (UMass Amherst), Muhammad Bilal Zafar (Bosch AI), Juhi Kulshrestha (GESIS), Mainack Mondal (University of Chicago), Rijurekha Sen (IIT Delhi)

• Operations Management
• Healthcare Analytics
• Pharmaceutical Industry
• +۴ مورد دیگر

Ujjal Mukherjee is an Associate Professor of Business Administration at the Gies College of Business, University of Illinois Urbana-Champaign. His research spans interdisciplinary domains, with a focus on operational strategies in healthcare systems, pharmaceutical innovations, and data-driven decision-making in complex environments. He holds a leadership role in advancing methodologies for predictive analytics and computational drug discovery, with notable contributions to understanding drug resistance mechanisms in oncology. Dr. Mukherjee’s work integrates quantitative approaches from operations research, epidemiology, and bioinformatics. His recent studies address critical challenges such as optimizing testing strategies for pandemic control, modeling product recall decision-making in supply chains, and developing algorithms to identify novel drug combinations for treatment-resistant cancers. He collaborates extensively with medical institutions and public health agencies, contributing to real-world solutions for healthcare delivery and crisis management. Research Themes: Drug Resistance Mechanisms, Epidemic Modeling, Predictive Analytics, Operations in Healthcare, Computational Biology Affiliations: Gies College of Business, University of Illinois Contact: 306 Wohlers Hall, Champaign, IL | ukm@illinois.edu His publications demonstrate a commitment to translational research, bridging theoretical frameworks with practical applications in both business and life sciences domains. Current projects include optimizing school reopening strategies during pandemics and enhancing precision medicine through single-cell omics integration.

Byung-Cheol Minمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Multi-Robot Systems
• Robotics
• +۷ مورد دیگر

Dr. Byung-Cheol Min is an Associate Professor and University Faculty Scholar in the Department of Computer and Information Technology at Purdue University. He serves as the inaugural director of the Applied AI Research Center (AARC) and leads the SMART Lab (www.smart-laboratory.org). His research focuses on human-robot interaction, multi-robot systems, and robotics, with an emphasis on distributed algorithms, learning, and socio-technical collaboration. Dr. Min holds a Ph.D. from Purdue University (2014), an M.S. from Kyung Hee University (2010), and a B.S. from Kyung Hee University (2008). He has received prestigious awards including the NSF CAREER Award (2019), Purdue University Faculty Scholar (2021), and multiple recognition for research excellence and mentorship. His work spans robotics applications in precision agriculture, construction automation, and assistive technologies. Dr. Min has secured over $10 million in grants and has published over 100 peer-reviewed articles, contributing to advancements in AI, control systems, and human-robot collaboration. Key roles include leadership in the Realizing the Digital Enterprise (RDE) initiative (2022–2024) and interdisciplinary affiliations with the Robotics Accelerator, ICON, and ISF institutes. His labs develop innovative systems such as the ROS2-based SMARTmBOT platform and multimodal datasets for cognitive workload assessment.

Tianyi Liمشاهده پروفایل

استادیار

• Human-AI Collaboration
• Crowdsourcing
• Sensemaking
• +۴ مورد دیگر

Tianyi Li is an Assistant Professor in the Department of Computer and Information Technology at Purdue University, part of the Purdue Polytechnic Institute. Her research focuses on human-AI collaboration, crowdsourcing, and sensemaking, with applications in domain-specific decision-making. She holds a Ph.D. in Computer Science from Virginia Tech (2020) and a B.Eng. from the University of Hong Kong (2015), with additional studies at UC San Diego and Shanghai Jiao Tong University. Dr. Li's work integrates design, experimental, and computational methods to enhance collective intelligence through crowdsourcing and improve human-AI interaction. She has received an NSF IUSE Award (2023) and contributed to projects like the Event Detection Explorer and Purposeful AI initiatives. Her teaching includes courses on database programming, web development, and discrete structures. Research Grants: NSF IUSE Award for fostering culturally relevant programming learning experiences (2023) Professional Experience: Former Assistant Professor at Loyola University Chicago, and roles at Microsoft Research AI, Cloudera, and Informatica Her lab explores tools for computer-supported cooperative work, including visual analytics for hyperparameter tuning and crowd-based sensemaking systems. Current research emphasizes inclusive learning content development and human-centric AI interaction patterns.