Pranjal Kandhari
M.Sc. Student in Computer and Information Science
University of Konstanz · Algorithmics Group
I am a master's student at the University of Konstanz specializing in Algorithmics, working under Prof. Dr. Sabine Storandt. My research focuses on algorithm engineering for dynamic graphs, particularly k-center problems on sparse dynamic graphs. I am broadly interested in the design and empirical evaluation of algorithms for graph optimization problems under dynamic settings.
Research
Algorithm Engineering for k-Center on Sparse Dynamic Graphs
Advisor: Prof. Dr. Sabine Storandt · University of Konstanz
Designed and implemented dynamic variants of k-center algorithms in C++ for node-update dynamic graphs, extending classical static approaches to incremental, decremental, and fully dynamic models.
Approximation Algorithms for k-Center in Sparse Graphs
Advisor: Prof. Dr. Sabine Storandt · University of Konstanz
Implemented in C++ and experimentally evaluated the Maximal Distance-r Independent Set, Gonzalez, and α-approximate Gonzalez algorithms across varied sparse graph instances.
Research Interests
- Dynamic Graph Algorithms
- Approximation Algorithms
- Algorithm Engineering & Empirical Evaluation
- Graph Theory & Optimization
- Parameterized Complexity
Publications
Together Apart: Decoding Support Dynamics in Online COVID-19 Communities
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Academic Experience
The Algorithmics Group appointment spans both experience categories; responsibilities are grouped by focus.
Department of Computer and Information Science, University of Konstanz
Research Assistant — Teaching
- Teaching Assistant for Algorithm Engineering; graded assignments and provided feedback on parallelization, memory-aware algorithms, and parameterized complexity.
Max Planck Institute of Animal Behavior
Research Assistant
- Designed and implemented interactive behavioral-analysis games in Python to study collective human decision-making patterns.
- Built and deployed the game infrastructure on Heroku for hundreds of simultaneous online players, collecting interaction data for analysis.
- Programmed ChatGPT-powered agents and conducted comparative studies of human players, AI agents, and intra-AI interactions.
- Tech: Python, LLM APIs
IIIT Hyderabad — Precog Lab
Research Associate
- Worked under Dr. Ponnurangam Kumaraguru at Precog Lab, using Cox regression, BERT topic modelling, and Reddit data from Pushshift and PRAW to analyze support duration and patterns in online COVID-19 communities.
- Built a time-series dataset of Indian crime statistics through large-scale web scraping with Scrapy, data extraction with Camelot, and data cleaning in Python.
Engineering Experience
The Algorithmics Group appointment spans both experience categories; responsibilities are grouped by focus.
Department of Computer and Information Science, University of Konstanz
Research Assistant — Roubikon Engineering
- Built Roubikon (demo, GitLab), an AWS-deployed, multi-criteria route planner for users with mobility constraints. It computes paths over OpenStreetMap road graphs using user-weighted surface type, elevation, and distance objectives.
- Reduced nearest-neighbour snapping latency from 200 ms to 1.5 ms (>100×) with a grid-based spatial index, and packaged graph extraction, indexing, and route planning as a pip-installable Python library that can set up a new city in under 10 minutes.
- Added synchronized street-level route-video rendering, GPX export, a mobile-responsive interface, and an LLM-based parser for converting free-text requests into routing parameters.
- Tech: Flask, Python, JavaScript, Leaflet, AWS
Amazon
Software Development Engineer I
- Built a Plan Document Comparator that introduced anomaly detection between plans, using depth-first search on graph database schemas to compare documents and highlight differences.
- Created availability and latency alarms and email notifications for critical endpoints using iGraph.
- Ensured backward compatibility between a new and an existing API in Java, enabling downstream consumers to migrate without service disruption.
- Tech: Java
Goldman Sachs
Software Engineer (converted from internship)
- Configured GitLab CI/CD pipelines for test-suite execution.
- Developed test cases for evolving product features and Bash scripts that automated test-case table generation.
- Automated more than 200 quality-management scenarios for the Marcus product using Cypress and Cucumber.
- Tech: JavaScript, Cypress, Java
Projects
Feedback Vertex Set — Algorithm Engineering
Grade: 1.0Implemented and analyzed exact (parameterized), approximation, and heuristic algorithms in C++ for the NP-complete Feedback Vertex Set problem. Parallelized the implementations with OpenMP and experimentally evaluated their scalability across multiple graph instances.
GitHub →Efficient Route Planning — Hierarchical Hub Labeling
Implemented canonical, heuristic, and greedy Hierarchical Hub Labeling algorithms and skeleton-dimension computation in C++. Validated shortest-path queries against Dijkstra on thousands of randomized tests and evaluated the algorithms on PACE and road-network instances; heuristic HHL delivered the fastest normalized query time, more than 100% faster than Dijkstra.
GitLab →Smart Traffic Light Management System
Designed a system to reduce waiting time for emergency vehicles by leveraging drivers' mobile GPS data. The system dynamically adjusts signal timings based on real-time vehicle positions.
Springer Publication →Education
University of Konstanz
M.Sc. in Computer and Information Science · Specialization: Algorithmics
Thesis: Algorithm Engineering for k-Center on Sparse Dynamic Graphs
Advisor: Prof. Dr. Sabine Storandt
Selected Coursework: Randomized Algorithms, Algorithm Engineering, Database System Architecture and Implementation, Approximation Algorithms, Efficient Route Planning Techniques, Distributed Systems, Introduction to Machine Learning, Machine Learning and Optimization Seminar
Bharati Vidyapeeth's College of Engineering
B.Tech. in Computer Science and Engineering
Skills & Awards
Programming
Python, C++17/20, Java, JavaScript
Frameworks & Tools
Flask, NumPy, Pandas, Matplotlib, STL, Leaflet, JUnit, Serenity BDD, Cucumber, Cypress, AWS, GitLab CI/CD, Bash, iGraph
Research & Algorithms
Algorithm Design & Analysis, Approximation Algorithms, Dynamic Graph Algorithms, Graph Theory, Optimization, Data Structures, Empirical Algorithmics
Won 1st place among 700 teams; awarded $20,000 in government funding for further research. · Jul 2018