- 5+ years of industry and research experience involving Machine learning and Neural networks projects in an Agile framework.
- 3.5+ years’ financial industry experience in developing highly scalable machine learning/deep learning-based payment applications and services.
- 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.
- 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, XGBoost, Theano, Keras, Scikit-learn, OpenCV, NumPy, Pandas, NLTK, MRTK, SAFe- Scaled Agile Framework, Weka, LaTeX, Mercurial, SourceTree, Jira, SVN, Clear Case, Pargon transaction simulator.
Database and Client/Server Technologies:
Hadoop, MySQL, Hive, NoSQL, MongoDB, 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.
- Research, develop and compare deep learning based Machine comprehension system for emotive natural language processing.
- 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, data science and ML development within an Agile framework.
- Analysis, and design for new project releases (which includes Apple Pay & Tokenization, EMV Release & enhancement, MiFID) and research analytic frameworks using machine learning techniques.
- Designed and developed a transaction research analytic Framework for EFT- Switching Processor interface and card authorization.
- Use statistical modeling and data analysis techniques to evaluate new features for transaction research analysis, behavioral data analysis, and fraud detection.
- Recommend functional approaches to address business requirements of payment solution through workflow diagrams, data models, the architectural process diagram for projects - ApplePay, Tokenization, EMV.
- Develop SQL scripts to extract data from the transaction database to create control groups for statistical analysis and modeling of the transactions for ROI patterns after new product deployment.
- Conduct EDA in tandem with cross-functional teams from Visa, Mastercard and relevant entities to implement various payment solution products; maintaining PCI compliance standards.
- Develop, test, and deploy algorithms for predicting and gaining insight on account holder and transaction patterns (Classification, Time series data analysis, and A/B Testing).
- 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 the top 3% of employee performance for 3 years running, awarded with back to back promotions.
- Training and Mentoring resources in the team.
- Programming Language: Python, C++, TAL, and TACL.
|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|