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Ali Tajer

Associate Dean of Engineering & Professor of ECSE

Rensselaer Polytechnic Institute
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Ali Tajer is the Associate Dean of Engineering and a Professor of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute in the United States. His research areas encompass causal inference, reinforcement learning, and stochastic bandits, as evidenced by his recent publications, which include topics such as cascading failure prediction, blackout mitigation, and efficient best arm identification. Professor Tajer's work contributes significantly to advancements in real-time fault prediction and change detection methodologies.

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Ali Tajer

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Rensselaer Polytechnic Institute

PhD Positions in Machine Learning, Robotics, and Causality at Rensselaer Polytechnic Institute

Professor Ali Tajer, Associate Dean of Engineering and Professor of ECSE at Rensselaer Polytechnic Institute (RPI), is recruiting multiple PhD students for research in machine learning and its applications to robotics. The research focus includes causality and representation learning, with opportunities for close collaboration with researchers from IBM and Google DeepMind. This is an excellent opportunity for students interested in artificial intelligence, robotics, and advanced machine learning topics. Applicants should have a strong interest in machine learning, robotics, causality, and representation learning. The ECSE Department at RPI is committed to increasing accessibility and diversity in its graduate programs. As part of this commitment, the department has waived the application fee for its PhD program for students from a selected group of institutions. The list of eligible institutions can be found at the provided link. Students from other institutions may also contact the admissions office to request a fee waiver by emailing [email protected] with the subject 'ECSE Application Fee Waiver'. To apply, interested candidates should send their CV and transcripts to Professor Tajer at [email protected]. The position offers the chance to work in a collaborative environment with leading industry partners and to contribute to cutting-edge research in machine learning and robotics. No specific funding details are provided in the announcement, but the application fee waiver is highlighted as a benefit. For more information, applicants are encouraged to review the provided links and contact the department as needed.

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Collaborators (2)

Vincent Y. F. Tan

National University of Singapore (NUS)

SINGAPORE

Urbashi Mitra

Professor/Dr.

University of Southern California

UNITED STATES
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