Joydeep Mukherjee

Joydeep Mukherjee

Assistant Professor
CSSE , California Polytechnic State University

   About Me    |    Contact    |    Research    |    Publications    |    Teaching    |    Service    |    News  

About Me

I am an Assistant Professor in the department of Computer Science and Software Engineering at California Polytechnic State University (Cal Poly), San Luis Obispo, USA. My research interests include Software performance engineering, Cloud computing and Internet-of-Things. Before joining Cal Poly, I worked as a post-doctoral fellow in York University, Toronto with Dr. Marin Litoiu. Prior to this, I completed my Ph.D. and M.Sc. degrees from University of Calgary, Canada, under the supervision of Dr. Diwakar Krishnamurthy. I received a Bachelor's degree in Computer Science and Engineering from National Institute of Technology (NIT) Durgapur, India.

I am also an Adjunct Assistant Professor in the Department of Electrical & Software Engineering at University of Calgary, Canada. In this role, I co-supervise graduate students and participate in research programs with other faculty members in the department.

I am currently looking for graduate and undergraduate students to work with me in Cal Poly (you can look my research interests on this site). If you're interested, please email me or meet me at my office to discuss potential projects and research opportunities.

Contact

Address: Room: 14-219, Frank E. Pilling Building
San Luis Obispo, California 93405
Email: jmukherj [AT] calpoly.edu
Phone: +01-805-756-2824

Research

My research interest is in the general area of performance evaluation of software systems. Specifically, the research topics I am currently interested in are -

Software performance is a crucial aspect of enterprise applications. In absence of proper software management techniques, applications will suffer from bad performance triggered by unidentified performance bottlenecks and will scale poorly due to the lack of proper capacity planning. In my research, I develop scalable and cost-optimized techniques for managing application performance. My research investigates automated runtime modelling techniques that can be used to manage the performance of applications such as cloud-based Web services, video streaming services and industrial IoT applications. I focus on research problems that are academically rigorous and has immediate practical relevance in the industry. To this end, I have a long history of academic collaboration with premiere industry research laboratories such as Hewlett-Packard (HP) Labs, Palo Alto, USA and IBM Center for Advanced Studies (CAS), Toronto, Canada.

Selected Publications

ICPE 2024 Disambiguating Performance Anomalies from Workload Changes in Cloud-Native Applications
CASCON 2023 Detecting Software Anomalies Using Spectrograms and Convolutional Neural Network
SEAMS 2023 Towards a Robust On-line Performance Model Identification for Change Impact Prediction
ICPE 2022 Evaluating the Scalability and Elasticity of Function as a Service Platform
ICPE 2022 Machine Learning based Interference Modelling in Cloud-Native Applications
ICPE 2021 A Framework for Developing DevOps Operation Automation in Clouds using Components-off-the-Shelf
IEEE Cloud 2020 RAD: Detecting Performance Anomalies in Cloud-based Web Services
ICAC 2019 EMU-IoT - A Virtual Internet of Things Lab
IEEE TNSM 2019 PRIMA: Subscriber-Driven Interference Mitigation for Cloud Services
IEEE ACC 2018 Performance Management via MPC for Web Services in Cloud
IEEE IWQoS 2018 Subscriber-Driven Cloud Interference Mitigation for Network Services
IEEE TNSM 2017 Subscriber-Driven Interference Detection for Cloud-Based Web Services

Click here to see a detailed list of publications.


Teaching

CSC 357 Systems Programming 2023, 2024
CSC 410, 570 (Graduate Class) Software Evaluation 2023, 2024
CSC 305 Individual Software Design and Development 2022, 2022
CSC 101 Fundamentals of Computer Science 2021

Service

Conference Organizer

Program Committee

Reviewer

News


Updated: April 2022