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Prasanna (Sonny) Tambe is a Professor at the Wharton School of the University of Pennsylvania, specializing in the economics of technology and labor markets. His research explores AI’s impact on workforce dynamics, HR algorithms, and the gender wage gap in tech industries. Education: Ph.D. in Managerial Science and Applied Economics (Wharton, UPenn); S.B. and M.Eng. in Electrical Engineering and Computer Science (MIT). His work leverages internet-scale data from job platforms and patent databases to analyze trends in skill acquisition, remote work diversity, and algorithmic bias in hiring. Recent studies examine AI’s role in HR decision-making, the economics of emerging technologies, and labor market responses to IT innovation. Scientific Awards: Best Undergraduate Professors (Poets & Quants, 2020) Best Paper Awards (Management Science, Information Systems Research) ISS Sandra A. Slaughter Early Career Award (2016) Tambe co-directs Wharton Human-AI Research, focusing on ethical AI integration in organizations. His teaching includes award-winning courses on AI’s societal implications and data-driven business strategies.

• Economics of IT Labor
• Technological Change and Reskilling
• Algorithms and AI in HR and Management
• +5 more

Dr. Brady D. Lund is an Assistant Professor at the University of North Texas, focusing on interdisciplinary research at the intersection of information science, artificial intelligence, and ethics. His work addresses AI adoption in libraries, data privacy, academic integrity, and international development. He holds a Ph.D., M.S., and B.S. from Emporia State University and Wichita State University. Education: Ph.D., Emporia State University M.S., Emporia State University B.S., Wichita State University Research Interests: Dr. Lund explores how AI impacts information seeking behaviors, data privacy literacy, and library services. His work emphasizes ethical AI deployment in academic and clinical settings, with a focus on marginalized communities. Key areas include AI-driven library systems, blockchain applications for academic integrity, and the societal implications of generative AI. Research Trends: Recent publications analyze AI's role in health information, cybersecurity threat intelligence, and library leadership in minority-serving institutions. He critiques AI authorship policies, evaluates large language models, and advocates for equitable AI access in developing countries. Labs & Teams: Leads the Computational Humanities and Information Literacy Lab and the CyberCrews initiative, focusing on AI ethics, digital literacy, and interdisciplinary collaboration.

• Cyberpsychology
• Information Ethics
• Information Security
• +5 more

Jack B. Soll is the Gregory Mario & Jeremy Mario Distinguished Professor of Management and Organizations at Duke University's Fuqua School of Business. He joined Duke in 2005 after roles at INSEAD and visiting positions at Chicago and Wharton. His Ph.D. from the University of Chicago focused on behavioral science and economics. Research : Soll specializes in the psychology of judgment and decision making, particularly overconfidence, group decision making, and behavioral policy implications. He has pioneered studies on: Overconfidence's societal impacts Wisdom of crowds dynamics Decision biases in hiring and energy policy Teaching : Teaches decision making, leadership, and statistics across executive and MBA programs. Known for bridging academic research with practical managerial insights. Awards : Decision Analysis Publication Award (2021) Key Contributions : Co-created the 'MPG Illusion' concept showing consumer misunderstandings of fuel efficiency Pioneered 'self-blinding' techniques to reduce decision biases Advanced understanding of advice-taking dynamics in organizations

• Behavioral Decision Making
• Judgment and Decision Science
• Overconfidence
• +3 more

Dr. Kanwaljeet S. Anand is a dual-appointed Professor of Pediatrics (Pediatric Critical Care) and Anesthesiology, Perioperative & Pain Medicine at Stanford University School of Medicine. As director of the Pain/Stress Neurobiology Lab and Jackson Vaughan Critical Care Research Fund, he serves as Editor-in-Chief of Pediatric Research and maintains active membership in Bio-X, MCHRI, and Wu Tsai Neurosciences Institute. Rhodes Scholar with D.Phil from University of Oxford Harvard postdoctoral fellowship and Boston Children's Hospital residency Founded Harmony Health Clinic - Arkansas' largest charitable medical-dental facility A translational researcher with 30+ years of impact, Dr. Anand established the first scientific framework for infant pain perception and developed novel pain assessment methodologies. Current research focuses on: Hair biomarker analysis for stress and social affiliation (cortisol/oxytocin) Machine learning systems for objective pain detection in non-verbal infants Biopsychosocial interventions for stress reduction in disadvantaged youth Neurotoxicity mechanisms of sedatives in developing brains Global NICU opioid usage patterns through the NeoOpioid Consortium His work has yielded over 260 publications and significant advances in: Pediatric pain management protocols Neonatal stress biomarker development Critical care neurobiology insights Community health initiatives AI-driven clinical decision support systems Scientific Recognition 9th Annual 'In Praise of Medicine' Public Address, Erasmus University (2014) Nightingale Excellence Award (2016) Honorary Doctorate from University of Örebro (2019) NIH SBIB-H82 Study Section Chair (2018) Multiple IASP and American Pain Society awards Swedish Academy of Medicine's Nils Rosén von Rosenstein Award (2009) St. Jude Endowed Chairholder (2010) As mentor to Med Scholar Anjali Gupta and advisor to numerous professional bodies, Dr. Anand maintains active clinical leadership in Pediatric Intensive Care while advancing computational approaches to pain detection through collaborations with Stanford's AI researchers.

• Pediatric Pain and Stress Neurobiology
• Neonatal and Fetal Pain Assessment
• Biomarker Development
• +3 more

Louis Hickman is an Assistant Professor of Industrial-Organizational Psychology at Virginia Tech’s Department of Psychology. He also serves as a Visiting Academic at Amazon and holds a Senior Fellow position at Wharton People Analytics, University of Pennsylvania. His research bridges technology and work, focusing on machine learning applications in organizational science, particularly automated interviews and algorithmic fairness. He leads the Workplace Assessment and Social Perceptions (WASP) Lab, exploring how biases influence hiring and using AI to reduce algorithmic bias. Hickman holds a Ph.D. in Industrial-Organizational Psychology from Purdue University (2021), alongside advanced degrees in Computer Science and Creative Writing. His work emphasizes interdisciplinary collaboration, spanning psychology, computer science, and management. Research Interests: Automated personnel assessment via AI Algorithmic bias mitigation in hiring Machine learning applications in HR and education Interpersonal perception dynamics Unproctored testing in the AI era Publications: Recent work examines automated interview validity, LLM impacts on testing, and recruitment algorithm ethics. His 2025 studies highlight risks of unproctored testing and bias in automated systems. Earlier research (2023–2022) explores text mining for personality assessment and fairness in AI-driven selection. Awards: None explicitly mentioned, though his work has been widely cited in organizational psychology and AI ethics domains. Advising & Labs: Currently not accepting graduate students for 2026, but oversees the WASP Lab. Past research collaborations include projects on LLM competencies, bias simulation, and algorithmic fairness frameworks. Grants and funding sources are unspecified in provided text.

• Industrial-Organizational Psychology
• Algorithmic Fairness
• Machine Learning in Personnel Assessment
• +4 more

Monideepa Tarafdar is the Charles J. Dockendorff Endowed Professor of Information Systems at the Isenberg School of Management, University of Massachusetts Amherst. She holds a PhD in Management from the Indian Institute of Management Calcutta, specializing in Information Systems and Strategy. Her research focuses on technostress, AI ethics, and the societal impacts of digital technologies. She has held academic roles at Lancaster University and the University of Toledo, and visiting positions at MIT Sloan and LSE. A world-leading scholar, she was named AIS Fellow (2024) and featured in Stanford’s Top 2% Cited Scientists (2024). Her work examines technostress creators like overload, complexity, and invasion, offering coping strategies such as proactive reorientation and organizational support. She studies AI’s role in hiring bias, social media addiction, and gig economy well-being. As Editor-in-Chief of the Journal of AIS and coordinator of Isenberg’s PhD program, she drives interdisciplinary research in IS. Key achievements include over 120 papers, mentorship accolades, and grants addressing ICT-enabled inclusion and algorithmic transparency. Recent awards include the AIS Best Publication Award (2022), multiple Research Excellence Awards, and recognition for her impactful work on workplace resilience. She advises organizations on managing technostress and serves as a scientific advisor to Unplug (Dublin). Her current projects explore gender bias in job ads and the sociotechnical dimensions of climate change discourse.

• Information Systems
• Technostress Management
• Artificial Intelligence Ethics
• +4 more

Reda Mastouri is an Adjunct Professor in the Department of Data Sciences within the College of Computer and Information Sciences at Saint Peter’s University. He combines academic roles with 12 years of industry experience as a Lead Cyber Security Engineer and Product Consultant, collaborating with Fortune 200 and 500 companies. His teaching includes courses such as DS-520 Data Analysis, DS-530 Big Data, and CS-332 Advanced Computing. Ph.D., AI & Data Sciences, Saint Peter’s University M.Eng., Telecommunication and Network Engineering, ENSA-M Cadi Ayyad University M.S., Data Sciences, Saint Peter’s University B.S., Computer Sciences, New Jersey Institute of Technology B.A., Applied Mathematics, Rutgers University His scholarly work focuses on AI-driven algorithms for truth demystification and cluster computing applications in high-fidelity image/video forgery detection within cybersecurity. Additional expertise spans DevSecOps, enterprise architecture, and software economics, with a dedication to innovation in business strategy and technology integration. Dr. Mastouri’s research trends emphasize heterogeneous ad hoc networks, collaborative honeypot architectures, and blockchain-based security models for IoT. His work addresses distributed attack detection, false positive/negative reduction, and protocol optimization, aligning with his specialization in cybersecurity and artificial intelligence. Certified Splunk Super User Palo Alto Networks Certified Cybersecurity Associate (PCCSA) CyberArk Certified Trustee Certified Scrum Professional SFPC Certified 10-Hr OSHA Training for the Construction Industry Certified Project Management Essentials Certified (PMEC)™ Lean Six Sigma Yellow Belt (ICYB) CPR & AED Certified AWS Certified Developer Associate Scrum Foundation Professional Certificate NSE 1 Network Security Associate NSE2 Fortinet's Network Security Expert

• Artificial Intelligence
• Cybersecurity
• Data Science
• +3 more

Jeffrey K. Mullins is an Assistant Professor in the Department of Information Systems at the Sam M. Walton College of Business, University of Arkansas. His research explores the intersection of emotion, cognition, and ethics in information systems, with a focus on how digital technologies blur boundaries between work and play through gamification and metaverse development. Ph.D. in Information Systems, University of Arkansas Director of Ph.D. Program, Walton College Research interests span: Emotion and cognition in digital environments Ethics of biometric and gamification technologies Metaverse development and Web3 transitions Work-life convergence in IS-enabled contexts His publications in MIS Quarterly , Journal of Business Ethics , and Journal of the Association for Information Systems reflect these themes. Recent work examines AI biometrics policy and immersive learning applications. 2024 Walton College Executive MBA Teacher of the Year 2020 ACM SIGMIS Doctoral Dissertation Award 2016 Outstanding Lecturer Award With over a decade of IT experience at a Fortune 100 firm, he teaches graduate courses in IT management and multivariate analysis while maintaining certifications like ERPsim Level 2 Training.

• Emotion in Information Systems
• Cognitive Aspects of Technology
• Ethics in Information Systems
• +5 more

Merve Hickok is a Lecturer at the University of Michigan's School of Information, where she teaches data ethics. She also serves as the Responsible Data and AI Advisor at the Michigan Institute for Data Science (MIDAS) and is an affiliated faculty member at the Gerald R. Ford School of Public Policy. Additionally, she is the President and Research Director at the Center for AI and Digital Policy (CAIDP), advising governments and international organizations on AI policy and regulation. Her research focuses on AI policy, ethics, and governance, with particular emphasis on fundamental rights, democratic values, and social justice. She examines the impact of AI systems on individuals, society, and organizations, exploring issues like algorithmic bias, privacy concerns, and the societal implications of emerging AI technologies. Her work bridges technical understanding with social and ethical considerations to promote responsible AI development and deployment, with special attention to employment applications, government procurement, and international policy frameworks. 100 Brilliant Women in AI Ethics™ – 2021 Runner-up for Responsible AI Leader of the Year – 2022 (Women in AI) Lifetime Achievement Award - Women in AI of the Year - 2023 Top AI Leaders in Retail (Ethics & Compliance) - 2024 Hickok provides consultancy to C-suite leaders and training services to public and private organizations on Responsible AI development, due diligence, and governance. She has provided testimony to the US Congress, State of California Civil Rights Office, New York City Department of Consumer and Worker Protection, Detroit City Council, and numerous global organizations. She founded AIethicist.org to help professionals navigate the complex landscape of AI ethics and serves on the founding editorial board of Springer Nature's AI & Ethics journal.

• AI policy
• AI ethics
• AI governance
• +10 more

Andrew Soderberg serves as an Associate Professor in the Management and Human Resources Department at the College of Business, University of Wisconsin Oshkosh. He holds a Ph.D. from the University of Utah (2016) and a BS from Brigham Young University (2005), bringing over a decade of academic expertise to his role. His research spans critical domains in organizational behavior and business ethics, with particular emphasis on: Workplace ethics and moral decision-making processes Leadership dynamics and trust formation Political ideology's impact on organizational perceptions Artificial intelligence ethics in human resources Sexual harassment training effectiveness Work-life balance and parental status implications Soderberg's publication trajectory reveals a sophisticated evolution toward examining ethical tensions in modern workplaces. His recent work demonstrates increasing focus on AI ethics, political polarization in organizations, and psychological reactance to leadership failures. Methodologically, he employs mixed-methods approaches to dissect complex interactions between status perceptions, moral reasoning, and organizational outcomes, with notable contributions to understanding how e-training design influences harassment prevention and how political identity shapes workplace status hierarchies. His scientific recognition includes: Dean's Excellence Award, College of Business (2024) College of Business Outstanding Faculty Award (2023) Dean's Excellence Award (2022) Management Department Teaching Award (2022, 2019) As an educator, Soderberg has pioneered innovative classroom methodologies including the 'Court of Theories' debate exercise for motivation theory instruction and the 'FOG' framework for team communication training. His research collaborations span multiple institutions, addressing pressing organizational challenges from sexual harassment prevention to ethical AI implementation. While specific grant details aren't provided, his publication record indicates sustained funding for research on workplace ethics, leadership dynamics, and political ideology in organizations.

• Organizational Behavior
• Business Ethics
• Leadership Dynamics
• +6 more

Nigel Bosch is an Assistant Professor in the School of Information Sciences (iSchool) at the University of Illinois Urbana-Champaign, with a joint appointment in the Department of Educational Psychology. He is also a faculty affiliate at the National Center for Supercomputing Applications (NCSA) and Illinois Informatics. His primary research focuses on machine learning and human-computer interaction applications in education, with particular emphasis on affective computing, metacognition, and online learning environments. Bosch holds a PhD in Computer Science from the University of Notre Dame, followed by a postdoctoral research position at the National Center for Supercomputing Applications. His research explores machine learning applications in education, including automatic emotion measurement in programming education, metacognition analysis through natural language processing, and ethical implications of AI in learning. He also investigates wearable technologies for health monitoring and algorithmic bias mitigation in educational data. Bosch’s work is supported by grants from the National Science Foundation (NSF), the Institute of Education Sciences (IES), and the University of Illinois. He leads the (Human + Machine) Learning lab, which develops innovative technologies for educational analytics, AI ethics, and human-centered computing.

• Machine Learning
• Human-Computer Interaction
• Educational Technology
• +3 more

Yeqing Kong is an Assistant Professor of Technical Communication at Georgia Institute of Technology’s School of Literature, Media, and Communication (Ivan Allen College of Liberal Arts). Her research focuses on transnational risk communication, AI-assisted technologies, and social justice in communication. She holds a Ph.D. in Communication, Rhetoric, and Digital Media from North Carolina State University (2017-2021), an M.A. in Language and Linguistics from Lancaster University (2014-2015), and a B.A. in English from Hunan University (2010-2014). Education: Ph.D. North Carolina State University | M.A. Lancaster University | B.A. Hunan University Her research interests include corpus-assisted discourse analysis, cross-cultural communication strategies for vulnerable communities, and AI ethics in recruitment technologies. Recent work explores global health communication during the pandemic and environmental justice in crises like the Flint Water Crisis. Publications span journals like IEEE Transactions on Professional Communication and ACM conferences, focusing on technical communication, crisis management, and digital rhetoric. Her work emphasizes participatory approaches to promote equitable communication practices. Awards : Over $40,000 in grants (2017-2024), including IAC SODA Award, ACM SIGDOC grants, and HASTAC Scholar recognition. Grants and projects include AI-assisted recruiting tools and pedagogical initiatives like the Information Literacy Faculty Fellowship. She advises on technical writing pedagogy and health communication strategies, with ongoing collaborations in global media studies.

• Technical Communication
• Risk/Crisis Communication
• Cross-cultural Communication
• +5 more

Patryk Perkowski is an Assistant Professor of Strategy and Entrepreneurship at the Sy Syms School of Business, Yeshiva University. He holds a PhD from Columbia Business School and completed a postdoctoral fellowship in Business, AI, and Democracy at Columbia. His research focuses on the intersection of information technology, human resource management, and causal inference, examining how technological advancements like AI reshape talent competition and organizational strategies. He also develops methodological tools for empirical business research. Education: PhD and Postdoctoral Scholar at Columbia Business School. Research interests include AI's impact on workplaces, internal talent markets, labor discrimination trends, and algorithmic hiring. He publishes in top journals such as the Strategic Management Journal and Management Science. His work analyzes modern workforce dynamics, including automation effects, team coordination, and central banking AI applications. Notable studies address gender representation in hiring algorithms and long-term discrimination trajectories through meta-analyses. Advising: No advisee list provided. Grants and funding details not specified. His research bridges theory and practice, offering insights for firms to leverage human capital strategically in tech-driven environments.

• Information Technology
• Human Resource Management
• Causal Inference
• +3 more

Dr. Jennifer L. Wessel is an Associate Professor of Psychology at the University of Maryland, College Park, and Director of the Identity Management (IMg) Lab. Her research focuses on diversity and inclusion in the workplace, identity management strategies, and authenticity. She has taught courses in Social Psychology, Industrial/Organizational Psychology, and Diversity in Organizations. Her research is funded by the National Science Foundation, Society for Human Resource Management, and others. Education: PhD in Psychology (2012), MA in Psychology (2008) from Michigan State University; BA in Psychology (2006, cum laude) from Rice University. Research interests include stigma management in marginalized groups, authenticity at work, and organizational policies promoting inclusion. Recent studies explore applicant reactions to AI systems and mental illness disclosure in workplaces. The IMg Lab combines laboratory and field methodologies to address these topics. Advising and grants: Supervised numerous doctoral and undergraduate students (e.g., Rewina Bedemariam, Precious McQuade). Grant funding includes NSF and private foundations. Publications span journals like Journal of Business and Psychology and Psychology of Women Quarterly . Labs/Teams: Directs the IMg Lab, which examines identity management in work contexts. Collaborates on projects related to diversity, equity, and inclusion in organizations.

• Diversity and Inclusion in the Workplace
• Identity Management
• Authenticity
• +3 more

Dr. Saptarshi Sengupta is an Assistant Professor in the Department of Computer Science at San José State University (SJSU), leading the Machine Intelligence and Complex Systems (MICoSys) Lab. He advises the ACM student club at SJSU and holds a 'Alien of Extraordinary Ability' visa (Einstein Visa) from USCIS. His work focuses on resilient cyber-physical systems, risk analysis, and deep learning applications in healthcare and industrial systems. Education: Ph.D. in Electrical Engineering, Vanderbilt University M.S. in Electrical Engineering, Vanderbilt University B.Tech. in Electronics & Communication Engineering, West Bengal University of Technology Research Interests: Cyber-Physical Systems Security Healthcare AI for Cancer and Chronic Disease Prediction Battery Prognostics and Energy Systems Machine Learning for Complex Systems Analysis Key Achievements: Dr. T.M.A. Pai Gold Medal Award for Healthcare AI contributions Recipient of multiple best paper awards at international conferences Author of over 30 peer-reviewed publications Labs & Teams: Leads the MICoSys Lab, developing AI solutions for healthcare diagnostics, industrial prognostics, and smart infrastructure systems. Collaborations include interdisciplinary projects with biomedical and engineering domains.

• Cyber Physical Systems
• Risk/Reliability Analysis
• Deep Learning
• +3 more