About Me

Amutheezan Sivagnanam

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

Pennsylvania State University

Graduate Research Assistant

https://www.psu.edu/

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)

University of Houston

Graduate Research Assistant

https://www.uh.edu/

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

LSEG Technology

Software Engineer

https://www.lseg.com/

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

WSO2 Lanka (Pvt) Ltd

Software Engineering Intern

https://wso2.com/

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 4.00/4.00

Ph.D., Informatics

Coursework: Data Mining

University of Houston

F2019 – SU2022 · CGPA 4.00/4.00

M.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 3.81/4.20

B.Sc. Engineering (Computer Science and Engineering)

Coursework: Data Mining · Intelligent Systems · Operational Research

Skills

Languages
Python · C/C++ · Java
AI / ML
PyTorch · TensorFlow · Keras · Hugging Face · Scikit-learn
Optimization
CPLEX · Gurobi · Mosek · Google OR-Tools
Data & Visualization
pandas · Spark · matplotlib
Libraries
SciPy · NumPy · Ray · RLLib · OpenAI Gym
Databases
SQLite · MySQL · OracleDB · MongoDB
DevOps & Cloud
Git · Docker · AWS (SageMaker, EC2, Lambda, S3)