Fully Funded Ph.D. Positions in DB and AI at Indiana University Bloomington
=== About the Advisor ===
Homepage: https://homes.luddy.indiana.edu/yanda
Dr. Da Yan is an incoming Associate Professor (starting Spring 2024) in the Department of Computer Sciences of the Luddy School of Informatics, Computing, and Engineering (SICE) at Indiana University Bloomington. He received his Ph.D. degree in Computer Science from the Hong Kong University of Science and Technology in 2014, and received his B.S. degree in Computer Science from Fudan University in Shanghai in 2009. He is a DOE Early Career Research Program (ECRP) awardee in 2023, and the sole winner of the Hong Kong 2015 Young Scientist Award in Physical/Mathematical Science. His research interests include parallel and distributed systems for big data analytics, data management, data mining and machine learning.
Currently a tenured Associate Professor at the University of Alabama at Birmingham (UAB), he regularly publishes high-quality papers at top conferences and journals in DB and AI such as SIGMOD, VLDB, ICML, KDD, ICDE, AAAI, ACM TODS, VLDB Journal, IEEE TKDE and IEEE TPDS. He has graduated two Ph.D. students who have secured tenure-track Assistant Professor positions at various universities in the US. Dr. Yan has led or is leading research projects funded by organizations such as NSF, DOE, DOT, SouthBDHub, Google and Microsoft. He frequently serves as a program committee member for top international conferences like SIGMOD, VLDB, KDD, ICDE, NeurIPS, AAAI, IJCAI, and as a reviewer for leading international journals including ACM TODS, VLDB Journal, IEEE TKDE, IEEE TPDS, and ACM CSUR.
=== About IU ===
Founded in 1820, Indiana University Bloomington is the flagship campus of IU’s seven campuses and two regional centers statewide. IU became a member of the American Association of Universities (AAU) as early as 1909 and is part of the Big Ten Academic Alliance (together with renowned universities such as the University of Chicago, Northwestern University, the University of Wisconsin, and the University of Michigan). IU is one of the few U.S. universities with a supercomputer and it has received 10 million investment from the NSF in 2020 to build the "Jetstream2" supercomputer. In celebration of its bicentennial, the university built the "Big Red 200" AI supercomputer equipped with 256 NVIDIA A100 GPUs.
=== Requirements ===
* Track 1: Big Data Systems and Algorithms
(Basic) Solid knowledge of the concepts of data structures and algorithms, familiarity with C++ programming (knowledge updated to at least C++11), a solid mathematical foundation, writing skills, and teamwork and communication abilities.
(Preferred) Familiarity with parallel and distributed programming tools such as C++ multithreading library (or Pthreads), MPI, ZeroMQ, OpenMP, CUDA.
(Preferred) Ability to efficiently read and extract key techinques and contributions from algorithm and system papers, and to present them with slides during group meetings.
(Best) Some knowledge of the cutting-edge topics in database or systems, publication of the relevant papers in top venues, and the ability to independently propose novel and effective research ideas.
* Track 2: Deep Learning
(Basic) Deep understanding of machine learning and deep learning concepts, familiarity with Python/NumPy programming, a solid mathematical foundation, writing skills, and teamwork and communication abilities.
(Basic) Familiarity with deep learning programming tools such as PyTorch or TensorFlow 2.0, and Jupyter notebook.
(Basic) Ability to efficiently read AI papers (model design, learning paradigms, and application adaptation), and to extract key techinques and contributions, and to present them with slides during group meetings.
(Basic) Capability to design neural network models, loss functions, learning paradigms, etc., for a given application and to quickly implement the proposed models for experiments.
(Preferred) Proficiency in using IDEs like Visual Studio/PyCharm for writing and debugging large-scale deep learning projects, and experience in the training and tuning of large models.
(Best) Some knowledge of the cutting-edge topics in AI, publication of relevant papers in top venues, and the ability to independently propose novel and effective research ideas.
=== Interview Process ===
Please send your resume and transcript (for Master's students, please include your undergraduate transcript) to [log in to unmask] to schedule a Zoom interview.
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