2026 Panos Kalnis: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	55	4282	4164	18	18	199	13361

Overview

Panos Kalnis is affiliated with King Abdullah University of Science and Technology in Saudi Arabia. Their research spans multiple aspects of computer science, with a focus on artificial intelligence, signal processing, computer vision and pattern recognition, molecular biology, and information systems. Their scholarly output includes 40 publications in the field of computer science and 20 specifically in artificial intelligence.

The scientist's research covers a range of topics including:

Topic Modeling
Data Management and Algorithms
Advanced Graph Neural Networks
Sparse and Compressive Sensing Techniques
Natural Language Processing Techniques
Human Mobility and Location-Based Analysis
Recommender Systems and Techniques

They have published articles in several notable venues, among which are:

arXiv (Cornell University)
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the ACM on Management of Data
The VLDB Journal
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Their recent papers include the following:

"Top-k term publish/subscribe for geo-textual data streams", 2020, The VLDB Journal
"A Universal Question-Answering Platform for Knowledge Graphs", 2023, Proceedings of the ACM on Management of Data
"ChatGPT versus Traditional Question Answering for Knowledge Graphs: Current Status and Future Directions Towards Knowledge Graph Chatbots", 2023, arXiv (Cornell University)
"Rethinking gradient sparsification as total error minimization", 2021, arXiv (Cornell University)
"Towards Controlling the Transmission of Diseases: Continuous Exposure Discovery over Massive-Scale Moving Objects", 2022, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence

Frequent collaborators of Panos Kalnis include:

Shuo Shang
Lisi Chen
Christian S. Jensen
Reham Omar
Aritra Dutta

Best Publications

Private queries in location based services: anonymizers are not necessary

Gabriel Ghinita;Panos Kalnis;Ali Khoshgozaran;Cyrus Shahabi

1070
Citations
Preventing Location-Based Identity Inference in Anonymous Spatial Queries

P. Kalnis;G. Ghinita;K. Mouratidis;D. Papadias

983
Citations
PRIVE: anonymous location-based queries in distributed mobile systems

Gabriel Ghinita;Panos Kalnis;Spiros Skiadopoulos

587
Citations
On discovering moving clusters in spatio-temporal data

Panos Kalnis;Nikos Mamoulis;Spiridon Bakiras

586
Citations
Efficient OLAP Operations in Spatial Data Warehouses

Dimitris Papadias;Panos Kalnis;Jun Zhang;Yufei Tao

489
Citations
Privacy-preserving anonymization of set-valued data

Manolis Terrovitis;Nikos Mamoulis;Panos Kalnis

449
Citations
Mizan: a system for dynamic load balancing in large-scale graph processing

Zuhair Khayyat;Karim Awara;Amani Alonazi;Hani Jamjoom

417
Citations
Fast data anonymization with low information loss

Gabriel Ghinita;Panagiotis Karras;Panos Kalnis;Nikos Mamoulis

382
Citations
GraMi: frequent subgraph and pattern mining in a single large graph

Mohammed Elseidy;Ehab Abdelhamid;Spiros Skiadopoulos;Panos Kalnis

376
Citations
Quality and efficiency in high dimensional nearest neighbor search

Yufei Tao;Ke Yi;Cheng Sheng;Panos Kalnis

321
Citations
In-Network Computation is a Dumb Idea Whose Time Has Come

Amedeo Sapio;Ibrahim Abdelaziz;Abdulla Aldilaijan;Marco Canini

299
Citations
On the Anonymization of Sparse High-Dimensional Data

G. Ghinita;Yufei Tao;P. Kalnis

277
Citations
MobiHide: A Mobilea Peer-to-Peer System for Anonymous Location-Based Queries

Gabriel Ghinita;Panos Kalnis;Spiros Skiadopoulos

260
Citations
Indexing spatio-temporal data warehouses

D. Papadias;Yufei Tao;P. Kanis;Jun Zhang

232
Citations
Similarity evaluation on tree-structured data

Rui Yang;Panos Kalnis;Anthony K. H. Tung

224
Citations
Scaling Distributed Machine Learning with In-Network Aggregation

Amedeo Sapio;Marco Canini;Chen-Yu Ho;Jacob Nelson

189
Citations
An adaptive peer-to-peer network for distributed caching of OLAP results

Panos Kalnis;Wee Siong Ng;Beng Chin Ooi;Dimitris Papadias

189
Citations
User oriented trajectory search for trip recommendation

Shuo Shang;Ruogu Ding;Bo Yuan;Kexin Xie

189
Citations
Personalized trajectory matching in spatial networks

Shuo Shang;Ruogu Ding;Kai Zheng;Christian S. Jensen

186
Citations
Trajectory similarity join in spatial networks

Shuo Shang;Lisi Chen;Zhewei Wei;Christian S. Jensen

184
Citations
Location Diversity: Enhanced Privacy Protection in Location Based Services

Mingqiang Xue;Panos Kalnis;Hung Keng Pung

179
Citations
Authenticated join processing in outsourced databases

Yin Yang;Dimitris Papadias;Stavros Papadopoulos;Panos Kalnis

174
Citations

Frequent Co-Authors

Nikos Mamoulis University of Ioannina

Gabriel Ghinita Hamad bin Khalifa University

Christian S. Jensen Aalborg University

Dimitris Papadias Hong Kong University of Science and Technology

Kai Zheng University of Electronic Science and Technology of China

Vladimir B. Bajic King Abdullah University of Science and Technology

Marco Canini King Abdullah University of Science and Technology

Kian-Lee Tan National University of Singapore

Mourad Ouzzani Qatar Computing Research Institute

Yufei Tao Chinese University of Hong Kong

External Links

Wikipedia of Panos Kalnis Personal website of Panos Kalnis Google Scholar page

If you think any of the details on this page are incorrect, let us know.

Related Online Degrees & Career Pathways

If you’re exploring Computer Science in the USA, it’s important to know your options for online study and future career paths. Many students are drawn to the fastest degree to get online to quickly enter the tech field with strong job prospects and competitive salaries.

Specializations such as artificial intelligence are becoming increasingly popular. Choosing the best AI masters programs online can provide a significant edge in this growing industry, while allowing you to balance flexibility and affordability.

Looking ahead, students should consider the best college degrees for the future. Degrees that focus on emerging technologies, data science, and cybersecurity are expected to remain in high demand as industries evolve.

For those seeking a faster path to advancement, pursuing an easy masters degree might be the solution. These programs offer a balance between academic rigor and manageable workloads, supporting career growth in areas related to Computer Science.