Oliver Alvarado Rodriguez

Oliver Alvarado Rodriguez

Ph.D. Candidate

New Jersey Institute of Technology


Oliver Alvarado Rodriguez is currently a computer science Ph.D. candidate at NJIT in Newark, NJ. He performs research under the supervision of Dr. David Bader. He received his B.S. in computer science with a minor in mathematics from William Paterson University in Wayne, NJ in May 2020 with summa cum laude honors. During his undergraduate studies, he was a member of the Honors College, a part of the Upsilon Pi Epsilon honor society for computing and information disciplines, and was also awarded the Omicron Omega award for excellence in computer science. His research interests involve the design and implementation of algorithms in the areas of high-performance analytics, data science, and graph analytics. He has also dabbled with some cryptographical and computer security research during his undergraduate studies. He was awarded a best paper presentation award at the 2020 BDML/ICAIP conference for his presentation on the paper titled “A Study of Machine Learning Inference Benchmarks” done in collaboration with Dev Dave and under the tutelage of Dr. Weihua Liu and Dr. Bogong Su. Oliver recently served as the student keynote speaker at the Spring 2022 meeting of the Academic Data Science Alliance, where he presented the keynote talk: “Enabling Exploratory Large-Scale Graph Analytics through Arkouda.”

  • High Performance Computing
  • Massive-Scale Analytics
  • Data Science
  • Ph.D. in Computer Science, expected 2024

    New Jersey Institute of Technology

  • B.S. in Computer Science, 2020

    William Paterson University

Recent Publications

Quickly discover relevant content by filtering publications.
(2023). Arachne: An Open-Source Framework for Interactive Massive-Scale Graph Analytics. In IPDPS.

PDF Cite

(2022). Arachne: An Arkouda Package for Large-Scale Graph Analytics. In HPEC.

PDF Cite

(2022). Interactive Graph Analytics in Arkouda. In Massive Graph Analytics.

Cite DOI Buy

(2022). Adapting Arkouda for Enabling Large Scale Graph Algorithms. In IPDPS.


(2021). Enabling Exploratory Large Scale Graph Analytics through Arkouda. In HPEC.


Recent Experience

For complete work history refer to my curriculum vitae.

Research Assistant
May 2021 – Present New Jersey
Designed, implemented, and analyzed algorithms for high performance graph and data analytics. Explored the research process from literature review through algorithm design, implementation, and performance optimization.
Teaching Assistant
Sep 2020 – Apr 2021 New Jersey
Instructed lab sessions for 50+ students to demonstrate the practicability of topics learned in lecture. Provided extra tutoring for 20+ students who struggled with the material presented in both lab and lecture
Data Science Intern
Jun 2020 – Aug 2020 New Jersey
Researched machine learning classification algorithms best suited for text data. Created an API that pulled pertinent information from databases, predicted sex given at birth for insurance leads, and returned a new table for their sales team. Managed project through Chubb’s enterprise GitHub and worked on an Agile software development schedule. Presented progress weekly to supervisor and larger data science team.

Honors & Awards

SC22 Student Travel Awards
Travel grant award to attend The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC) 2022. Acceptance rate of <20%.
Mathematics Research Community Participant
Week-long workshop solving problem(s) related to hypergraphs. Acceptance rate of <50%.
Omicron Omega Award for Excellence in Computer Science
Awarded to the highest-GPA graduating senior in computer science.
Upsilon Pi Epsilon International Honor Society
Admittance to computer science students who maintain at least a B average in all courses.

Recent & Upcoming Talks and Tutorials

Listed here are talks and tutorials at conferences, workshops, etc. that are not tied to a specific publication.