About Me

Hi, I'm Amutheezan Sivagnanam. I recently earned my Ph.D. in Informatics at Penn State, where I built AI tools that help buses run on time, vehicles find the best routes, and ambulances reach people faster.
My research combines deep reinforcement learning with classic optimization and real-world data so that systems can make smart decisions in seconds while keeping costs down.
Along the way, I've published first-author papers at ICML, AAAI, and IJCAI, released open-source code for others to build on, and collaborated with industry partners to turn research ideas into working prototypes.
Research Experience
Lab: Applied Artificial Intelligence Lab (AAILab)
Supervisor: Dr. Aron Laszka
Duties:
- Led research projects funded by the U.S. Department of Energy (DOE) and the National Science Foundation (NSF), introducing cost- and energy-efficient solutions to tackle real-world problems
- Analyzed current state-of-the-art solutions and identified research gaps in existing solution approaches, leading to the development of innovative strategies for real-time decision-making
- Introduced novel problem formulations and mathematical models to address these challenges, while ensuring inherent real-world constraints
- Proposed artificial intelligence–based solutions to tackle real-world problems and successfully deployed them in relevant industries
- Published research findings in AI conferences (ICML) and assisted in preparing slides for presenting results at DOE and NSF meetings
Research Projects:
- Multi-Agent Reinforcement Learning with Hierarchical Coordination for Emergency Responder Stationing (Published in ICML-24)
- Dynamic Vehicle Routing Problem with Prompt Confirmation of Advance Requests (Published in ICCPS-26)
Lab: Resilient Networks and Systems Lab (RNSLab)
Supervisor: Dr. Aron Laszka
Duties:
- Spearheaded research projects funded by DOE and NSF, leading to advancements in energy-efficient technologies
- Focused on understanding real-world decision-making problems and identified gaps in existing solution approaches, leading to the development of novel methodologies for enhanced decision-making
- Proposed novel problem formulations and mathematical models and formulated problem statements to effectively address the research limitations in prior research efforts
- Applied artificial intelligence-based solution approaches to real-world problems and successfully deployed them in relevant industries
- Published research findings in AI conferences (AAAI, IJCAI) and assisted in preparing slides for presenting results at DOE and NSF meetings
Research Projects:
- Minimizing Energy Usage in Transit Agencies Operating with Mixed-Fleet of Vehicles (Published in AAAI-21)
- Offline Vehicle Routing with Online Bookings (Published in IJCAI-22)
- The Benefits of Vulnerability Discovery and Bug Bounty Programs (Presented in WEIS-21, Published in WWW-23)
Engineering Experience
Team: Post Trade Team
Reporting to: Mr. Sujith Gunawardana
Duties:
- Developed application software using Object-Oriented principles, enhancing code maintainability and scalability
- Implemented agile development practices (Scrum) to improve team collaboration and project delivery speed
- Developed software solutions using Java, Python, and C++, improving system performance and reliability
- Introduced Unit Testing for Libraries in Post Trade C++ Code
- Modified database structures and tested using BDD-based testing, ensuring data integrity and system functionality
- Developed a dynamic scripting object (DSO) for front-end end-to-end testing using Java, enhancing test coverage and efficiency
- Developed a new report generation system for the testing framework, automating email dispatch at the end of regression
- Contributed to code integration and deployment plans, ensuring seamless software updates and minimizing downtime
- Worked on Front-End Development for both Product and Solution — Enhancement, Bug Fixing, Merging and Introducing new features
Team: Data Analytics Team
Reporting to: Mr. Anjana Fernando
Duties:
- Developed an HL7 Monitoring Solution by integrating WSO2 ESB, DAS, and BAM, enabling real-time and batch processing of healthcare data
- Developed an alert generation system analyzing descriptive HL7/FHIR data to monitor disease outbreaks, triggering timely email and SMS notifications
- Engineered a mechanism to evaluate hospital functionality by assessing admission and discharge messages, including bed and oxygen cylinder availability
- Implemented interactive dashboards using Jaggery, JavaScript, jQuery, Leaflet.js, and DataTables, featuring charts, maps, and tables
- Created Spark scripts for batch analytics and Siddhi execution plans for real-time alerts
- Utilized HAPI library and test panel to simulate HL7 v2 messages and validate the monitoring pipeline end-to-end
- Packaged the entire monitoring solution as a Carbon Application (CApp), bundling event streams, receivers, publishers, and visualization artifacts
Education
Pennsylvania State University
F2022 – SU2025 · CGPA 4.00/4.00Ph.D., Informatics
Coursework: Data Mining
University of Houston
F2019 – SU2022 · CGPA 4.00/4.00M.Sc., Computer Science
Coursework: Machine Learning · Artificial Intelligence · Advance Numerical Analysis · Computer Architecture · Operating Systems · Cloud Computing
University of Moratuwa
2014 Jan – 2018 Jan · CGPA 3.81/4.20B.Sc. Engineering (Computer Science and Engineering)
Coursework: Data Mining · Intelligent Systems · Operational Research