In this age of Data science, a large portion of current research in applied mathematics is focused on developing machine learning methodologies to extract information in pertinent data , this include research in abstract and linear algebra, optimization theory and applied statistics, also, a lot of current interest in applied mathematics is in enrichment of mathematical foundations of Quantum information theory.
The best way a researcher can improve the quality of research in the research institution of which he/she is a part is by sincere and dedicated research and development initiatives, however, interacting with colleagues and helping them with insights on their research problems, is also another useful way to improve the overall research environment and also enlightening the researcher himself/herself by discussion with other research personnel.
The following Some Industrial Mathematics Programs and Workshops, which explains the trends of industrial Math.
MSc Program in Industrial Mathematics at the University of British Columbia http://www.iam.ubc.ca/industry/msc.html
The Harvey Mudd College Mathematics Clinic http://www.math.hmc.edu/clinic/clinic.intro.html
BSc program in Industrial Mathematics at the University of South Carolina http://www.usca.sc.edu/academic/Majors/IndustrialMath.html
MSc program in Mathematical Information Sciences for Industry at the University of Illinois at Chicago http://www.math.uic.edu/~hanson/MISI.html
Industrial Mathematics at Worcester Polytechnic Institute, Worcester, MA http://www.wpi.edu/Academics/Depts/Math See also their Center for Industrial Mathematics and Statistics http://www.wpi.edu/~cims/reu/index.htm
Professional Master of Science in Industrial Mathematics at Michigan State University http://www.math.msu.edu/Graduate/msim/\#MTH843
Industrial Mathematical Modelling for Graduates and Industrial Problem Solving Workshops organized by the Pacific Institute for Mathematical Sciences http://www.pims.math.ca/industrial/
Mathematical Problems in Industry Workshops, organized by D. Schwendeman of Rensselaer Polytechnic Institute, Troy, NY. http://www.math.rpi.edu/Faculty/Schwendeman/Workshop/MPI.html