جستجوی استاد راهنمای دانشگاهی

Julia Milner is a Professor and Leadership Development Chair at EDHEC Business School (faculty of Management & Humanities) and a Research Associate. Her work focuses on leadership development, positive psychology, team effectiveness, organizational culture, digital leadership, empathy/neuroscience, social media, coaching, and workplace well-being. Her research has been published in prominent academic journals including: Organizational Dynamics Harvard Business Review Journal of Applied Behavioral Science Asia Pacific Journal of Human Resources International Journal of Technology & Human Interaction She actively engages in knowledge dissemination through: TEDx talks on leadership and turning regrets into change Columns in HBR France, HBR US, and The Conversation A YouTube channel dedicated to career development topics Her recent work emphasizes leadership challenges such as micromanagement, empathetic communication, and feedback efficacy. She provides actionable strategies for leaders to improve team dynamics and organizational culture. No information is available regarding scientific awards, student advising, or lab affiliations.

• Leadership Development
• Positive Psychology
• Team Effectiveness
• +۶ مورد دیگر

Philipp Strack is an Assistant Professor in the Department of Economics at the University of California, Berkeley, holding a Ph.D. from the University of Bonn. His academic profile centers on microeconomic theory with emphasis on dynamic strategic interactions and information processing. His research portfolio spans: Microeconomic Theory Dynamic Decision Making Strategic Experimentation Dynamic Mechanism Design Behavioral Economics with particular focus on private learning in contests, experimentation games, and information dynamics in sequential decision environments. Publication analysis reveals consistent contributions at the intersection of game theory and behavioral economics, examining how agents process information under uncertainty. Recent works address survey response mechanisms, progressive participation constraints, and regret-driven choices, demonstrating methodological rigor through experimental and theoretical approaches. No scientific awards are documented in the source material. While specific advising details remain unlisted, his position implies graduate student mentorship within Berkeley's Economics Department. Research activities likely involve grant-supported projects typical of active microeconomic theorists at R1 institutions, though specific funding sources aren't referenced. Departmental affiliation is exclusively with Economics at UC Berkeley; no specialized labs or research teams are mentioned in available documentation.

• Microeconomic Theory
• Dynamic Decision Making
• Strategic Experimentation
• +۲ مورد دیگر

Mengxiao Zhang is an Assistant Professor in the Department of Business Analytics at the Tippie College of Business, University of Iowa, holding this position since August 2024. His research develops theoretically grounded machine learning algorithms for practical business applications, with expertise spanning online learning, bandit problems, and game-theoretic optimization. His academic foundation includes: Ph.D. in Computer Science from the University of Southern California (2018-2024), advised by Prof. Haipeng Luo Bachelor's degree from Peking University (2014-2018), advised by Prof. Liwei Wang Zhang's research bridges theoretical machine learning with operational business challenges, focusing on adaptive algorithms that maintain performance guarantees in non-stationary environments. His work addresses core problems in regret minimization, efficient exploration, and equilibrium computation, with increasing emphasis on supply chain optimization, auction design, and fair multi-agent systems. He designs methods that function effectively under constraints like delayed feedback, budget limitations, and unknown demand distributions. Analysis of his 15 most recent publications (2022-2025) reveals a consistent trajectory toward business-relevant applications while maintaining theoretical rigor. Key trends include contextual bandit extensions for advertising auctions, supply chain optimization under uncertainty, and fairness-aware multi-agent learning. His contributions appear in top-tier venues including COLT, ICML, and NeurIPS, with notable recognition including a NeurIPS 2020 Oral presentation. No scientific awards are documented in the provided materials. Zhang teaches Database Management (BAIS-3200) at the University of Iowa and previously served as teaching assistant for multiple graduate algorithms and machine learning courses at USC. No information regarding research grants or student advising is available in the source materials. No dedicated laboratory or research team structure is specified in the provided information.

• Online learning and bandits
• Reinforcement learning
• Game theory
• +۳ مورد دیگر