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Personal profile

Academic Biography

Dr Diptangshu Pandit (Max) is a Senior Lecturer in Computer Game Design. He focuses teaching mainly the technical side of the games development using Unreal Engine and visual scripting. He has a PhD in applied artificial intelligence for biomedical signal processing. He holds both bachelors and masters degree in Computer Science and Engineering. Before joining Teesside, he was teaching at Northumbria University for 2 years in computer and information sciences department. His work is mostly focused on machine learning and evolutionary optimisation algorithms and their use in various domains including game development. 

Summary of Research Interests

His research interests include, but not limited to the following areas;

  • Machine Learning and it’s applications.
  • AI in computer games.
  • Bio-medical signal processing.
  • Evolutionary optimization.
  • Brain Computer Interface.
  • Deep learning.

Education/Academic qualification

PhD, Northumbria University

Apr 2014Jun 2017

Fingerprint Dive into the research topics where Max Pandit is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 3 Similar Profiles
Electrocardiography Engineering & Materials Science
Classifiers Engineering & Materials Science
Lead Engineering & Materials Science
Feature extraction Engineering & Materials Science
Simulated annealing Engineering & Materials Science
Neural networks Engineering & Materials Science
Global optimization Engineering & Materials Science
Noise abatement Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2014 2018

103 Downloads (Pure)

A scattering and repulsive swarm intelligence algorithm for solving global optimization problems

Pandit, D., Zhang, L., Chattopadhyay, S., Lim, C. P. & Chengyu, L., 15 Sep 2018, In : Knowledge-Based Systems. 156, p. 12-42 31 p.

Research output: Contribution to journalArticle

Open Access
File
Global optimization
Scattering
Swarm intelligence
Simulated annealing
4 Citations (Scopus)

Classifier ensemble reduction using a modified firefly algorithm: An empirical evaluation

Zhang, L., Srisukkham, W., Neoh, S. C., Lim, C. P. & Pandit, D., 1 Mar 2018, In : Expert Systems with Applications. 93, p. 395-422 28 p.

Research output: Contribution to journalArticle

Classifiers
Statistical tests
Benchmarking
Composite materials
7 Citations (Scopus)
73 Downloads (Pure)

A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm

Pandit, D., Zhang, L., Liu, C., Chattopadhyay, S., Aslam, N. & Lim, C. P., 1 Jun 2017, In : Computer Methods and Programs in Biomedicine. 144, p. 61-75 15 p.

Research output: Contribution to journalArticle

Open Access
File
Electrocardiography
Lead
Detectors
Computational efficiency
Feature extraction

Noise Reduction in ECG Signals Using Wavelet Transform and Dynamic Thresholding

Pandit, D., Zhang, L., Liu, C., Aslam, N., Chattopadhyay, S. & Lim, C. P., 2017, Emerging Trends in Neuro Engineering and Neural Computation. Bhatti, A., Lee, K. H., Garmestani, H. & Lim, C. P. (eds.). Singapore: Springer Singapore, p. 193-206 14 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

Noise abatement
Electrocardiography
Wavelet transforms
Signal to noise ratio
Signal processing
4 Citations (Scopus)

Improved abnormality detection from raw ECG signals using feature enhancement

Pandit, D., Zhang, L., Aslam, N., Liu, C. & Chattopadhyay, S., 24 Oct 2016, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016. Du, J., Liu, C., Li, K., Wang, L., Tong, Z., Li, M. & Xiong, N. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 1402-1406 5 p. 7603383

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Electrocardiography
Classifiers
Decision trees
Support vector machines
Feature extraction