Rutgers University ISE 招收全奖博士生
14110
Ahmed Aziz Ezzat is an Assistant Professor of Industrial and Systems Engineering at Rutgers University. He received his Ph.D. in Industrial and Systems Engineering at Texas A&M University in 2019, and his B.Sc. degree in Industrial and Management Engineering in Alexandria, Egypt, in 2013. His broad research interests are in the areas of spatio-temporal data and decision sciences, probabilistic forecasting, quality and reliability engineering, with focus on energy analytics (data science for renewable energy) and materials informatics (data science for materials engineering). Dr. Aziz Ezzat’s work has been published in leading journals such as The Annals of Applied Statistics, Technometrics, IEEE Transactions on Sustainable Energy, among others. His awards include the 2022 IISE DAIS Teaching Award, the 2020 IIF-SAS® research award, the 2020 Rutgers OAT Teaching Award, the 2019 ISEN Outstanding Graduate Student at Texas A&M, and the IISE Sierleja Memorial Fellowship in 2014. At Rutgers, Dr. Aziz Ezzat leads the Renewables & Industrial Analytics (RIA) research group. The research and educational activities at RIA have been supported by several grants, including from the National Science Foundation (NSF), NJ Economic Development Authority, Institute of International Forecasters and SAS corporation, and the Rutgers Energy Institute. He is a member of IISE, IEEE-PES, and INFORMS.
Successful applicants would have strong (and demonstrated) skills in at least one or some of the following: (1) statistics/mathematics, data science/AI/ML, optimization/operations research; and (2) programming experience in at least one of Python, R, MATLAB (samples from prior projects or a GitHub repository will be looked at favorably). Prior research experience (e.g., a thesis or working/published research article) is a plus, but not required. Additional preferred skills include experience in machine learning, forecasting and time series analysis, and mathematical programming (e.g., mixed integer optimization). Typical applicants will have one or more university-level degrees in industrial/mechanical engineering, statistics, computer science, or a related field.
Interested applicants can email their resumé/CV, UG/MS transcripts, along with any other relevant material (e.g., sample projects or papers) to Prof. Aziz Ezzat (1point3acres.com) with the title (PhD applicant – RIA Group). Applicants should also include information in their CV about their progress towards meeting the ISE PhD admission requirements. In the email, applicants can also express why they are interested in applying to this position, how/why do they think they can contribute to RIA’s research, and their future goals/plans as PhD researchers.
For more detail, please see attached file.
drive.google.com
Successful applicants would have strong (and demonstrated) skills in at least one or some of the following: (1) statistics/mathematics, data science/AI/ML, optimization/operations research; and (2) programming experience in at least one of Python, R, MATLAB (samples from prior projects or a GitHub repository will be looked at favorably). Prior research experience (e.g., a thesis or working/published research article) is a plus, but not required. Additional preferred skills include experience in machine learning, forecasting and time series analysis, and mathematical programming (e.g., mixed integer optimization). Typical applicants will have one or more university-level degrees in industrial/mechanical engineering, statistics, computer science, or a related field.
Interested applicants can email their resumé/CV, UG/MS transcripts, along with any other relevant material (e.g., sample projects or papers) to Prof. Aziz Ezzat (1point3acres.com) with the title (PhD applicant – RIA Group). Applicants should also include information in their CV about their progress towards meeting the ISE PhD admission requirements. In the email, applicants can also express why they are interested in applying to this position, how/why do they think they can contribute to RIA’s research, and their future goals/plans as PhD researchers.
For more detail, please see attached file.
drive.google.com
