Dr. Ahilan kanagasundaram

SUMMARY

• Accomplished machine learning expert with experience in proposing novel solutions and developing state-of-the-art systems for different applications. 

• Proficient in predictive modelling, data processing, data mining, and scripting languages, including Python.

• Holding Australian and Sri Lankan Citizenship.

TECH STACK

● Python        ● Linux environments        ● Keras          ● Deep Learning
● Keras          ● Scikit-learn                         ● SQL            ● Pandas   
● PySpark      ● Cloud                                  ● PyTorch     ● Signal Processing

EDUCATION

Queensland University of Technology (Apr 2010 – Nov 2014)
Australia
Ph.D (Machine Learning & Speech Processing)

University of Peradeniya (Feb 2004 – May 2008)
Sri Lanka                          
B.Sc. Engineering Honors - Electrical & Electronic Engineering
GPA: 3.80/ 4.00

WORK EXPERIENCE

Senior Lecturer & Machine Learning Specialist (Sep 2016 - Present)
University of Jaffna                           

• Developed time series and deep learning models to accurately forecasting the load demand and solar PV power generation

• Worked with other developers in a team to develop speaker verification and speaker diarization technologies for commercial applications

• Developed machine learning based autism spectrum disorder detection system

• Developed state-of-the-art deep learning-based speaker profiling systems

• Proposed innovative approach to identify whether customer can pay the loan or not using speech utterance

• Developed machine learning based automatic wind turbine maintenance scheduling system

Machine Learning Researcher (Nov 2014 – Sep 2016)
Queensland University of Technology      

• Proposed machine learning algorithms to improve the performance of speaker verification system in dataset mismatch and noisy conditions

• Evaluated algorithms on terabytes of training data using parallelized routines and Sun Grid Engine (SGE)

• Coordinated research projects within the SAIVT research program

Ph.D internship (Nov 2012 - Apr 2013)
Autonomous University of Madrid        

• Analyzed the insights of short utterance speech data using visualization and statistical approaches

• Proposed novel machine learning approaches to compensate the unwanted variations

CERTIFICATIONS

• Deep Learning Specialization – Coursera

• Sequence Models – Coursera

• Convolutional Neural Networks – Coursera

• Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization – Coursera

• Neural Networks and Deep Learning – Coursera

• Structuring Machine Learning Projects - Coursera

KEY ACCOMPLISHMENTS

• Participated Speakers in The Wild (SITW) Challenge (2nd place in raking in the main core-core track)

• Participated DIHARD speaker diarization challenge I and II

• AHEAD research, innovation and commercialization grant

• 2 local patents and 1 international patent