- 5+ years of industry and research experience involving Machine learning and Neural networks projects in an Agile framework.
- Strong background and passion in Cognitive science, Natural language processing, Computer vision, and Deep Learning Architectures.
- A solid foundation of the mathematics behind AI, Machine Learning algorithms, data structures, linear algebra and convex optimization techniques.
- Can distill highly technical knowledge and techniques to collaborators outside the problem domain, utilizing strong communications, excellent brand awareness, and interpersonal skills.
- Proven track record delivering high impact, enterprise-grade, scalable, secure & reliable software systems.
- 3.5+ years’ industry experience in developing highly scalable machine learning/deep learning-based applications and services.
- Ability to work on data mining, data science projects with application engineering, quality engineers, and product management.
Master of Science, Applied Cognition and Neuroscience, UT Dallas
Specialization: Computational Modelling and Intelligent Systems Aug 2016 – May 2018
Bachelor of Technology, Computer Science Engineering, Cochin University of Science and Technology, Cochin, India
Specialization: Machine learning and Swarms Intelligence Sep 2008 - Jul 2012
Favorite Topics/Top Skills:
Cognition-based Computational Modelling, Artificial intelligence (AI), Machine learning, NLP, Computer vision, Mixed reality.
OS/Platforms: AR-Augment reality (Microsoft HoloLens), VR-Virtual Reality (Oculus and HTC Vive), Linux, Windows, HP Nonstop Kernel
Scripting and Programming Languages: C, C++, Python, C#, Java, MATLAB, TAL, TACL, HTML, CSS, Groovy, PHP.
Software Tools/ Framework:
Jupyter Notebook, Pycharm, Visual Studio, Unity, IBM SPSS, Wamp, Git, Adobe Brackets, MS-Office, Tensorflow, Theano, Keras, Scikit-learn, OpenCV, NumPy, Pandas, NLTK, MRTK, SAFe- Scaled Agile Framework, Weka, LaTeX, Mercurial, SourceTree, Jira, SVN, Clear Case.
Database and Client/Server Technologies:
MSSQL, MySQL, Apache, SQL/MP, Enscribe, MS-Access
Center for Modeling and Simulation Laboratory, UT Dallas as Research and Development Engineer March 2017 - 20
- As a Research engineer, assist and contribute to the exploratory study for the creation of an advanced neural network based cognitive framework that will power the research and move the team closer to the goal of creating world-class virtual humans.
- Led a team of 5 programmers to research and develop highly saleable distributed systems of Neural Networks for Natural language processing and Human Action Recognition systems, utilizing compiling data on body language, facial cues, and other physiological information in VR (Oculus, HTC Vive) /AR (Microsoft HoloLens) platforms. All neural networks are developed in-house from scratch.
- Analyze, design, and develop real-time VR and AR software for advanced prototypes and user experiences.
- Bridging the gap between technical and research requirement by collaborating with other teams including 3D modelers, animators, research designers and other programmers.
- Guided the undergraduate researchers with the development, coding, debugging, and maintenance of cognitive-based research architecture, design and execution of experiments, and technological resources.
Mathematical Analyses of Artificial Neural Networks Laboratory, UT Dallas as Graduate Research Assiatant Dec 2016 - Dec 2017
- Work on research projects involving cognitive process modeling and machine learning, under the supervision of Dr. Richard Golden.
- Compiled noteworthy results for basic machine learning model to device efficient model generalization methods based on AIC.
Accenture as Senior Software Engineering Analyst Dec 2012 - Jul 2016
Dec 2015- Jul 2016 Senior Analyst Software Engineering
Mar 2014- Nov 2015 Analyst Software Engineering
Dec 2012- Feb 2014 Associate Software Engineering
- Work in cross-functional project teams that include research, development, and support within an Agile framework.
- Analysis, design, and development for new project releases (which includes Apple Pay & Tokenization, EMV Release & enhancement, MiFID I, MiFID II European financial market regulative) and research/automation frameworks using machine learning techniques.
- Use machine learning and statistical modeling techniques to develop and evaluate algorithms to improve performance, quality, and accuracy.
- Develop, simulate, test, and improve algorithms for predicting transaction pattern across time and demography.
- Participate in product research & design meeting to review and provide input on research requirements, product designs, and potential problems.
- Collaborate with the other stakeholders, devise the research objective and development strategies in line with the scope and Mathematical feasibility of AI Systems.
- Led/Supervised an Agile team of 15 Developer, Analyst, Tester, and Trainees.
- Ranked in top 3% of employee performance for 3 years running, awarded with back to back promotions.
- Training and Mentoring resources in the team.
- Programming Language used: Python, C++, TAL, and TACL.
- Designed and developed a Machine Learning based Research Framework for EFT- Switching Processor interface, resulting in
- 50 % reduction in the overall testing effort and
- Automated online preproduction pilot testing with external payment entity like VISA and Mastercard.
- Accenture Financial Services Idea of the year-2014-15.
|Python 101 for Data Science-IBM||Deep Learning Fundamentals-IBM||Deep Learning with TensorFlow-IBM|
|GANs and Variational Autoencoders-Udemy||Modern Deep Learning in Python-Udemy||Recurrent Neural Networks in Python-Udemy|
|Machine Learning by Stanford University-Coursera||pandas for Data Science-Linkedin|