Yunis ahmad L.

Yunis ahmad L.

CTO Data Scientist & Principal Software Engineer

New Delhi , India

Experience: 20 Years

Yunis ahmad

New Delhi , India

CTO Data Scientist & Principal Software Engineer

54179.6 USD / Year

  • Immediate: Available

20 Years

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About Me

In charge of a major portion of offshore delivery for 20 projects and 50 resources. 2.Running multiple practices and projects in emerging technologies inclusive of computer vision, NLP, AI, ML, Robotics and Healthcare. 3.Responsible for ramping up...

Microsoft Project/ SQL Server/Oracle/Mongo DB Core Java/Eclipse/LINUX, PYTHON, R, AZURE, KERAS, TENSOR FLOW, THEANO, PYTORCH MLP, CNN, RNN, LSTM, GRU, RBM, DBN, Autoencoders, SOM, Capsule Networks, Hopfield Networks, Neuro Fuzzy Inference, IBM WATSON Implementations, AWS & GCPGPU Processing of large-scale ML models using CUDA & PYTORCH/ Swarm optimisation & Fuzzy Logic Natural Language Processing/Ling pipe, Genetic Algorithms, Deep Learning MATLAB/Robotics/LabVIEW/Azure/SAS/Python/Java/C/C++ MS.NET/J2EE/Angular JS /C# ML Artificial Intelligence/Neural Networks Semantic/Syntactic Analysis  WSAD/AIX/C/C++/MSVC++/Rational XDE/DB2SP Client/Clear Case/Clear Quest Java/J2EE /J2EE/WSAD/AIX/C/C++/MSVC++/JUnit/ JBUILDER 5.0/ RATIONAL ROSE/RATIONAL REQUISITE PRO/OOAD/RUP Autoencoders, Neurofuzzy inference (Mamdani & Sugeno), Reinforcement Learning, Restricted Boltzmann’s Machines & Deep Belief Networks, CNN, Capsule Networks, Nested LSTM’s, RNN, LSTM & GRU, Generative Adversarial Networks (GAN’s), Siamese Networks, Teacher Networks

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Portfolio Projects

Description

I have been working on engineering, machine learning and artificial intelligence for the past 20 years now in professional and personal capacity. My experiments with AI started in 1995 when I was doing my master’s in civil engineering from BITS Pilani. One of the projects I was engaged in was the optimisation of traffic networks using Neural Networks. Later I did my master’s project and thesis in Real Coded Genetic algorithms for Engineering Optimisation. This was done under the supervision of Professor P. Balasubramanian. He provided the relevant guidance and support for me to complete my master’s project and thesis in the Computer Aided Design cell of National Informatics Centre CGO complex Delhi. Though I went on to work in the IT industry, my endeavours with AI have been continuing ever since. I have used GA's and Neural Networks for multiple problem-solving areas in the last 20 years in my career. The tools that I specifically specialise in are Python & MATLAB and its toolboxes.

I have used MATLAB & Python for a wide range of problems inclusive of regression, curve fitting, deep learning and time series analysis. Additionally, have worked on tools like Mathcad, Maple and SAS. Lately I completed a project on Market Segmentation for an insurance brand using SAS 9.2. I have a deep passion for Analytics and Data Mining inclusive of Machine learning and AI. Have explored most of the projects in MATLAB File exchange and am a regular visitor of the MathWorks Collaboratory.

Have good hands on knowledge of Kinematics and Dynamics as also Mathematical modelling and Control Systems. Used the State Space model to design a wide variety of complex robots using the Lego Mindstorms robotics kits. Computer Vision and 3 modelling using Kinect and MATLAB has been explored in multiple projects by me and my team. My experiments in Robotics started almost 14 years back when I started working on the Lego Mindstorms RCX. Later, graduated to the NXT and now the EV3. Have created a wide variety of simple and complex models programmed in Java, LabVIEW and MATLAB. Ballbots and Two wheeled Inverted pendulum carts are some other models that I have worked on.

Have also specialised in Computer Vision based programs and Algorithms using PIXY. I have been training final year engineering students on Robotics in multiple engineering institutes by organising Lego Mindstorms workshops. I have developed a deep interest and experience in Natural Language Processing using Java, Python and .NET. Have created multiple prototypes for automating many pain areas for auditors in the Audit space for one of the big 4 professional services organisations in the world. Have created smart diff programs and Latent Sematic Inversion based searches not limited to Lucene based but also other complex search algorithms.

I am an avid learner of Engineering mathematics and Numerical Analysis. Also have deep interest in Optimisation and Operations Research. In NLP space, I have worked on the following packages and much more: Lucene, Stanford NLP, Weka, Mallet, Ling Pipe, Java, Python. Raspberry Pi and Arduino based models have been researched by me in my endeavours in the Microprocessor space. Have created multiple models using the same.

I also have deep expertise in 3 d modelling, virtual reality and augmented reality using UNITY. I believe I can use my knowledge of Internet of things and sensors to solve very complex practical problems.

Qualification wise, I have a Bachelor’s in engineering and master’s in engineering from one of the top 5 Engineering colleges in India. Additionally, I also have a post graduate certificate in Artificial Intelligence & Machine Learning, which completed a few years back. I am a technologist at heart with more than 20 years of work experience in the IT industry. Have had brief exposures to work outside of the country as well.

There are a wide variety of projects in MATLAB, Simulink, Raspberry Pi and Lego Mindstorms which have been implemented by me in my personal and professional capacity. These include a wide variety of domains like Robotics, Numerical analysis, scientific mathematics and Artificial Intelligence. In the field of AI, I have been exploring usage of Neural Networks, Genetic Algorithms and machine learning. In MATLAB and Simulink, I and my team are using the various MATLAB tool boxes to explore usage in a wide variety of engineering problems and their solutions.

In Lego Mindstorms I have created basic to complex models including Line Follower, Simultaneous Localization (SLAM) & Mapping, Rubix cube solver etc. Additionally, I am adept in usage of concepts like Lyapunov Stability and Kalman filter for financial modelling, Ballbots and kinematics of two wheeled stable robots (Inverted Pendulums).

I have a keen interest in mathematical modelling and am very comfortable with undergraduate and graduate level Engineering courses. In my experience in professional capacity, I have worked extensively on Numerical Analysis, Optimization, Operations Research, Linear Algebra, Topology, Differential Equations, Control Systems, Predicate Calculus, Chaos Theory and Financial Modelling. I have projects on Engineering Optimization using real coded genetic algorithms and a variety of projects on use of Neural Networks for Stock market, indices and various other predictions. I have also worked on multiple projects on Digital Signal Processing and Image Processing using MATLAB (Image Processing Toolbox). Have exposure to using all MATLAB toolboxes. I have also used open source fuzzy logic software JUZZY for various fuzzy modelling problems. Rule based engines for Natural language processing and decision-based systems have been used as well. I have used Simulink widely for learning models and simulation of a variety of problems. Recently I worked on a neuro fuzzy model for text inference-based learning. This is still in a pilot phase. I also have pertinent exposure to JBPM on Eclipse to create financial and scientific workflows.

I am dedicated, hardworking and diligent. Have the right attitude and this is something that I have been wanting to do for a long time in my career. I believe, given the right exposure and break, I can work beyond expectations. I have passion for science and technology and am confident that given a chance I can work on some major breaks on the technology front.

The latest problem statement of the solution developed by me was the auto routing of Incidents to the right resolution group based on incident description. This work was done for an international client. I used Bidirectional GRU and Attention with Context to solve this problem. With a training data of around 70,000 records, the model gave an accuracy of more than 86 %. We intend to use incremental learning on the model in the long run to improve accuracy. Additionally, this used Word2Vec, genism, Keras and NLTK.

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Description

Delivery project executive for DBS.

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Description

Multiple projects for Bharti Airtel client

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Description

Prcing of Fidelity Mutual Funds application

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