Curriculum Vitae

[Resume] : [Research] : [Engineering]

Education

• Ph.D. in Informatics, Pennsylvania State University, 2025 (anticipated)
• M.S. in Computer Science, The University of Houston, 2022
• B.S. in Computer Science and Engineering, University of Moratuwa, 2018

Research Focus

Artificial Intelligence, Machine Learning, Deep Reinforcement Learning, Optimization, Operational Research

Languages and Tools

Research experience

• 2019/09 - Present - Graduate Research Assistant
  • The University of Houston, Pennsylvania State University
  • Supervisor: Dr. Aron Laszka
  • Duties included:
    • Introduced novel mathematical models for combinatorial optimization problems in transit domain.
    • Introduced novel deep-reinforcement learning based solution approach to solve those problems.
    • Published research works in conferences (ICML, AAAI, IJCAI, WWW) and journals (ACM).

Engineering experience

• 2018/01 - 2019/07: Software Engineer
  • LSEG Technology (formerly MillenniumIT)
  • Duties included:
    • Introduced unit testing for libraries in Post Trade C++ Code.
    • Performed database changes for Post Trade products for Singapore Stock Exchange and validated with Behavior Driven Development (BDD) testing approaches using Java.
    • Worked on CI/CD of the Post Trade product with Python and Git.
    • Practiced Agile-based development throughout the entire period of work.
• 2016/07 - 2016/12: Software Engineering Intern
  • WSO₂ Lanka PVT Limited
  • Duties included:
    • Implemented alert generation mechanism, which provides email and SMS when a disease spreads wide by analyzing the description.
    • Implemented alert generation mechanism, which could determine the functional state of hospitals (i.e., number of beds available, number of Oxygen cylinders available) based on the admission and discharge messages.

Publications

Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing

Sivagnanam, A., Pettet, A., Lee, H., Mukhopadhyay, A., Dubey, A., & Laszka, A. (2024). Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing. In Proceedings of the 41 st International Conference on Machine Learning, (ICML 2024)

The Benefits of Vulnerability Discovery and Bug Bounty Programs: Case Studies of Chromium and Firefox

Atefi, S., Sivagnanam, A., Ayman, A., Grossklags, J., & Laszka, A. (2023, May). The Benefits of Vulnerability Discovery and Bug Bounty Programs: Case Studies of Chromium and Firefox. In Proceedings of the ACM Web Conference, (pp 2209–2219), ACM

Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit

Sivagnanam, A., Kadir, SU., Mukhopadhyay, A., Pugliese, P., Dubey, A., Samaranayake, S., & Laszka, A. (2022, July) "Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit. In Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (pp. 3933-3939)

Data-Driven Prediction and Optimization of Energy Use for Transit Fleets of Electric and ICE Vehicles

Ayman, A., Sivagnanam, A., Wilbur, M., Pugliese, P., Dubey, A., & Laszka, A. (2021). Data-driven prediction and optimization of energy use for transit fleets of electric and ICE vehicles. ACM Transactions on Internet Technology (TOIT), 22(1), 1-29.

Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

Sivagnanam, A., Ayman, A., Wilbur, M., Pugliese, P., Dubey, A., & Laszka, A. (2021, May). Minimizing energy use of mixed-fleet public transit for fixed-route service. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, No. 17, pp. 14930-14938).

Talks

Offline Vehicle Routing Problem with Online Bookings: A Novel Problem Formulation with Applications to Paratransit

July 29, 2022

Talk at Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI-22), Vienna, Austria

On the Benefits of Bug Bounty Programs: A Study of Chromium Vulnerabilities

June 29, 2021

Talk at The 20th Annual Workshop on the Economics of Information Security (WEIS 2021), Virtual Workshop

Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

May 18, 2021

Talk at Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-21), Virtual Conference

Projects

Emergency Responder Stationing

The Benefits of Vulnerability Discovery and Bug Bounty Programs

Offline Vehicle Routing Problem with Online Bookings (Applications: Paratransit Operations)

Minimizing Energy Use of Mixed-Fleet Public Transit for Fixed-Route Service

Workshops

On the Benefits of Bug Bounty Programs: A Study of Chromium Vulnerabilities

Sivagnanam, A., Atefi, S., Ayman, A., Grossklags, J., & Laszka, A. (2021). On the Benefits of Bug Bounty Programs: A Study of Chromium Vulnerabilities. In Workshop on the Economics of Information Security (WEIS) (Vol. 10).