Master’s in Data-Enabled Computational Engineering and Science

Outcomes and Career Success

Outcomes and Career Success

Career Outcomes

Brown University DECES master's program graduates are highly competitive in academic and industry markets. Outcomes that our recent graduates achieved:

  • Acceptance into PhD Program (i.e., MIT, Yale, Brown University): 60% of Graduates 
  • Acceptance into National Lab or Industry Positions (e.g., Spatial Genomics, Hellenic Army Center, AI and Data Science Fellow): 40% of Graduates

Source: LinkedIn and Alumni Survey
 

Testimonials

Kento Abeywardane

Kento AbeywardaneBackground

  • Chemical Engineering ScB
  • Selected DECES to build skills/confidence in Computational Engineering
  • DECES outcome to to obtain Industry position (e.g., pharmaceutical) or acceptance into PhD program

DECES Experience

  • Summer internship in industry position
  • Completed Thesis
  • Focus on completing computational engineering courses

Outcomes

  • Multiple industry and PhD offers
  • Selected MIT PhD program
     

Ke Ma

Ke MaBackground

  • Utilized DECES as a transitional masters to build skills/confidence in Computational Engineering
  • Selected DECES due to world renowned faculty (Yuri Bazilev, George Karniadakis) and that the small program builds strong relationships with faculty and peers

DECES Experience

  • Computational engineering courses built strong skills that are used in his solid mechanics PhD

Outcomes

  • Brown University PhD (Solid Mechanics)
  • Pursue tenured professor track or industry position
     

Niko Bhatia

Niko BhatiaBackground

  • D1 Athlete (Water Polo)
  • Undergraduate Engineering degree
  • Did not have time to focus on computer science (software, computational) since engineering is so rigorous and time consuming

DECES Experience

  • Interdisciplinary approach is emphasized by the founding professors 
  • Built strong software and computational skills through project driven classes
  • Professors can provide deep insights into relevant research topics
  • Excellent breadth and depth of courses
  • Loved living in downtown Providence

Outcomes

  • Industry valued the Master’s degree
  • Selected interdisciplinary engineering/software position at Spatial Genomics
  • One of the few people who can solve problems with an interdisciplinary (e.g., engineering, software) approach engineering
     

Nikhil Kadivar 

Nikhil KadivarBackground

  • Bachelor of Technology in Mechanical Engineering from Indian Institute of Technology
  • Research Engineer at Bosch India for two years

DECES Experience

  • Strong desire to move away from industry to a PhD program. Confirmed this desire through the courses, conducting research with a professor, completing his thesis
  • Computational engineering courses built strong skills that are used in his solid mechanics PhD
  • Appreciated the interdisciplinary nature of the program
    • Could take courses in data science, applied math, engineering, science (e.g., biology), computer science 
    • Enjoyed the “luxury to choose any course”
    • Worked closely with peers and professors
  • Developed strong presentation skills in his courses and defended his thesis. Received excellent feedback/support from peers and professors.

Outcomes

  • PhD student working with Prof. George Karniadakis at Brown University. 
  • Research interest on computational modeling and simulation using numerical methods and scientific machine learning for cardiovascular biomechanics.