2026 Philip K. Chan: 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	49	5757	5592	2617	2524	113	16724

Overview

Philip K. Chan is affiliated with the Florida Institute of Technology in the United States. Their research spans multiple disciplines, prominently focusing on Medicine and Computer Science, with significant contributions in subfields such as Artificial Intelligence, Psychiatry and Mental Health, Pulmonary and Respiratory Medicine, Oncology, and Astronomy and Astrophysics.

Their main research topics include:

Domain Adaptation and Few-Shot Learning
Anomaly Detection Techniques and Applications
Bipolar Disorder and Treatment
Solar and Space Plasma Dynamics
Cancer Immunotherapy and Biomarkers
Advanced Malware Detection Techniques
Adversarial Robustness in Machine Learning

Philip K. Chan has published extensively, with recent papers covering a range of topics in both medical and computational sciences. Notable papers include:

A Randomized, Placebo-Controlled Pilot Study of Quetiapine-XR Monotherapy or Adjunctive Therapy to Antidepressant in Acute Major Depressive Disorder with Current Generalized Anxiety Disorder, 2025, Psychopharmacology Bulletin
A Machine Learning Approach to Predicting SEP Events Using Properties of Coronal Mass Ejections, 2022, Space Weather
Real-world outcomes in patients with metastatic renal cell carcinoma treated with first-line nivolumab plus ipilimumab, 2021, Journal of Clinical Oncology
Representation Learning with Function Call Graph Transformations for Malware Open Set Recognition, 2022, 2022 International Joint Conference on Neural Networks (IJCNN)
Feature Decoupling in Self-supervised Representation Learning for Open Set Recognition, 2022, arXiv (Cornell University)

Their frequent publication venues reflect a diverse engagement with both medical and technological research areas:

arXiv (Cornell University)
British Journal of Urology
Psychopharmacology Bulletin
Space Weather
Journal of Clinical Oncology

Philip K. Chan collaborates regularly with several researchers, including Jingyun Jia, B.D. Kelly, David E. Kemp, and Carla Conroy. These collaborations are evident in multiple joint publications across various topics.

Best Publications

Toward accurate dynamic time warping in linear time and space

Stan Salvador;Philip Chan

2468
Citations
Distributed data mining in credit card fraud detection

P.K. Chan;W. Fan;A.L. Prodromidis;S.J. Stolfo

1406
Citations
AdaCost: Misclassification Cost-Sensitive Boosting

Wei Fan;Salvatore J. Stolfo;Junxin Zhang;Philip K. Chan

934
Citations
Determining the number of clusters/segments in hierarchical clustering/segmentation algorithms

S. Salvador;P. Chan

884
Citations
Cost-based modeling for fraud and intrusion detection: results from the JAM project

S.J. Stolfo;Wei Fan;Wenke Lee;A. Prodromidis

812
Citations
An analysis of the 1999 DARPA/lincoln Laboratory evaluation data for network anomaly detection

Matthew V. Mahoney;Philip K. Chan

791
Citations
Learning nonstationary models of normal network traffic for detecting novel attacks

Matthew V. Mahoney;Philip K. Chan

573
Citations
Toward scalable learning with non-uniform class and cost distributions: a case study in credit card fraud detection

Philip K. Chan;Salvatore J. Stolfo

541
Citations
Learning Patterns from Unix Process Execution Traces for Intrusion Detection

Wenke Lee;Saivatore J. Stolfo;Philip K. Chan

533
Citations
JAM: java agents for meta-learning over distributed databases

Salvatore Stolfo;Andreas L. Prodromidis;Shelley Tselepis;Wenke Lee

505
Citations
Systems for knowledge discovery in databases

C.J. Matheus;P.K. Chan;G. Piatetsky-Shapiro

481
Citations
Real time data mining-based intrusion detection

Wenke Lee;S.J. Stolfo;P.K. Chan;E. Eskin

451
Citations
FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space

Stan Salvador;Philip K. Chan

417
Citations
Meta-learning in distributed data mining systems: Issues and approaches

Andreas L. Prodromidis;Philip K. Chan

396
Citations
Using artificial anomalies to detect unknown and known network intrusions

Wei Fan;M. Miller;S.J. Stolfo;Wenke Lee

326
Citations
PHAD: packet header anomaly detection for identifying hostile network traffic

Matthew V. Mahoney;Philip K. Chan

311
Citations
Experiments on multistrategy learning by meta-learning

Philip K. Chan;Salvatore J. Stolfo

295
Citations
Learning rules for anomaly detection of hostile network traffic

M.V. Mahoney;P.K. Chan

286
Citations
A comparative evaluation of voting and meta-learning on partitioned data

Philip K. Chan;Salvatore J. Stolfo

275
Citations
Credit Card Fraud Detection Using Meta-Learning: Issues and Initial Results 1

Salvatore J. Stolfo;David W. Fan;Wenke Lee;Andreas L. Prodromidis

272
Citations
Advances in Distributed and Parallel Knowledge Discovery

Hillol Kargupta;Philip Chan

268
Citations

Frequent Co-Authors

Salvatore J. Stolfo Columbia University

Wenke Lee Georgia Institute of Technology

Hillol Kargupta University of Maryland, Baltimore County

Wei Fan Tencent (China)

Debasis Mitra Columbia University

Eleazar Eskin University of California, Los Angeles

Carla E. Brodley Northeastern University

Ouri Wolfson University of Illinois at Chicago

Zoran Obradovic Temple University

Vipin Kumar University of Minnesota

External Links

Personal website of Philip K. Chan Google Scholar page

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