CV

Liam Schramm CV

Contact

email: schrammlb2 at gmail dot com

web: liamschramm.com

Career Goals

  • Research and teaching career in Computer Science
  • PhD in Computer Science
  • Research interests: machine learning and robotics, especially reinforcement learning and planning. 

EDUCATION

Rutgers University, New Brunswick, New Jersey      August 2018 to present

  • PhD Program: Computer Science (Advisor: Dr. Abdeslam Boularias)
  • Admitted to candidacy for PhD, April 2020
  • Masters of Science: Computer Science, October 2022
  • Programming:
    • Highly proficient: Python, Java
    • Moderately proficient: BASH, C, C++, Fortran and Haskell
    • Some programming experience: VPython, Mathematica, LabVIEW, BASIC, TensorFlow, parallel computing

Bard College, Annandale-On-Hudson, NY      August 2014 to May 2018

  • Bachelors of Arts: Joint Degree Physics & Computer Science, with significant upper level Math
  • Thesis: Convolutional neural networks and the quantum many-body problem.
  • Scholarships:
    • Distinguished Scientist Scholar (Bard College; 2014-2018)
    • Oak Ridge National Laboratory SULI internship (2018)
    • National Science Foundation REU recipient (UCCS 2016, CMU 2017)
    • Distinguished Scientist Scholar Summer Research internship (Bard College; 2015)
    • National Merit Scholar (2014)
    • SEG Foundation/Marathon Oil Scholar (2014-2015)

Statistics: GPA: grad 3.82, undergrad 3.75 (167 hours); GRE: Quantitative 169, Verbal 170, Writing 5

OTHER AWARDS, HONORS AND SCHOLARSHIPS

  • ESEC/FSE 2017 Student Research Competition, 2nd Place, Paderborn, Germany, September 2017
  • SWAN 17 NSF Travel Grant
  • National AP Scholar (10 exams, average score 4.7)
  • Salutatorian (2 out of class of 318; GPA 4.61; college: 29 credits), Oak Ridge High School
  • Competitively awarded research internships and training programs:
    • Science Laboratory Undergraduate Intern (SULI), Oak Ridge National Lab, 2018
    • REU Software Engineering (REUSE) internship, Carnegie Mellon University, 2017
    • REU Machine Learning internship, University of Colorado, Colorado Springs, 2016
    • Math/Science Honors Thesis Program, Oak Ridge High School, 2013-2014
    • Governor’s School for Computational Physics, Austin Peay University, 2013
    • University of Tennessee Physics research internship, 2012-2014

WORK EXPERIENCE

Graduate Assistant, CS Department, Rutgers – Spring 2019 to present
Robot Learning Lab
Projects: Multiple project relating to reinforcement learning and planning
Advisor: Dr. Abdeslam Boularias

Teaching Assistant, CS Department, Rutgers – Fall 2021
198:440 Introduction to Artificial Intelligence course
Supervisor: Dr. Abdeslam Boularias

Teaching Assistant, CS Department, Rutgers – Summer 2021
198:440 Introduction to Artificial Intelligence course
Supervisor: Edgar Granados

Teaching Assistant, CS Department, Rutgers – Fall 2018
198:112 Data Structures course
Supervisor: Dr. Seshadri Venugopal

SULI Research Intern, Oak Ridge National Laboratory – Summer 2018
Geographic Information Systems Technology unit (Dept. of Energy sponsored program)
Project: Boosting GANs for Unsupervised Feature Learning
Mentor: Dr. Dalton Lunga, Oak Ridge National Laboratory

REU Research Intern, Carnegie Mellon University – Summer 2017
REUSE: REU in Software Engineering (NSF sponsored program)
Project: Classifying test executions for automatic program repair
Mentor: Dr. Claire Le Goues, Carnegie Mellon University

Directed Research, Bard College – Fall 2016
Project: Automatic program repair using learned heuristics
Mentor: Dr. Claire Le Goues, Carnegie Mellon University

REU Research Intern, University of Colorado, Colorado Springs – Summer 2016
REU Machine Learning: Theory and Applications (NSF sponsored program)
Project: Improving performance of automatic program repair using learned heuristics
Mentor: Dr. Kristen R Walcott Justice, University of Colorado, Colorado Springs

DSS Research Intern, Centre de Physique Théoretique, Aix-Marseille Université, France – Summer 2015
Distinguished Scientist Scholar Research Program (Bard College scholarship)
Project: Investigation of semiclassical approximation of the Bell states.
Mentor: Dr. Hal Haggard, Bard College

Tutor, Computational Physics Course, Bard Physics Department – Spring 2015
Instructor: Dr. Nick Lanzillo, Bard College

Research Intern, Physics Department, University of Tennessee Knoxville -2012 – 2014
Project: Simulation of chromosomal activity within E. coli cell.
Mentor: Dr. Jaan Mannik, University of Tennessee

Research Intern, Math/Science Honors Thesis Program, ORHS – 2013 – 2014
Project: Computational method to locate oil drill bits in real time with sensor data.
Mentor: Dr. Leonard Gray, retired, Oak Ridge National Laboratory

Classroom Assistant, AP Computer Science (2 sections), ORHS. 2013 – 2014
Supervisor: Mr. Keith Jackson, ORHS

REVIEWER, PROGRAM COMMITTEE MEMBERSHIP

  • Conference on Neural Information Processing Systems (NeurIPS): reviewer 2019, 2022
  • International Conference on Robotics and Automation (ICRA): reviewer 2020, 2022, 2023
  • Conference on Robot Learning (CoRL): reviewer 2021, 2022; program committee member 2021
  • International Conference on Machine Learning (ICML): reviewer 2021
  • International Conference on Learning Representations (ICLR): reviewer 2022

(Publications, papers, and presentations listed separately.)