Mr. Shyamakrishna Siddharth Chamarthy

Siddharth Chamarthy is an accomplished Engagement Manager at DIA Associates in Brooklyn, New York, where he focuses on leveraging machine learning to derive strategic insights from data. With a Master of Science in Mechanical Engineering from Columbia University, Siddharth specializes in predictive analytics, notably enhancing marketing strategies for sports organizations by categorizing fans based on their engagement and preferences. In his current role, he oversees complex data ingestion and database management projects, demonstrating strong technical skills in programming and robotics, particularly with Arduino. Prior to DIA Associates, he spent over four years as a Research Engineer at Quadrus Medical Technologies, where he led the development of innovative medical products, including a kidney injury prediction algorithm and an emergency ventilator. His work resulted in significant advancements in predictive healthcare technologies, achieving impressive accuracy rates in clinical predictions. Siddharth is also an active member of the IEEE EMBS, contributing to the Technical Committee on Cardiopulmonary Systems and Physiology-Based Engineering. His diverse skill set encompasses data analysis, system integration, and the development of advanced analytical solutions, which he applies to support both organizational goals and client needs. With over 1,249 connections on LinkedIn, Siddharth actively engages with the professional community, celebrating achievements and fostering collaboration. His commitment to innovation and excellence positions him as a key player in the intersection of technology, healthcare, and data analytics.Shyamakrishna Siddharth Chamarthy is an accomplished professional with extensive expertise in robotics, data science, machine learning, and biomedical research. With a Master of Science in Mechanical Engineering, specializing in Robotics and Controls from Columbia University, and a Bachelor of Technology in Mechanical Engineering from Amrita School of Engineering, he has consistently demonstrated proficiency in cutting-edge technologies. Currently serving as an Engagement Manager at DIAAssociates in New York City, he leads a team of data scientists and engineers in developing machine learning models for advanced marketing strategies, leveraging tools such as Python, PySpark, SQL, AWS Redshift, and Sagemaker. His contributions include rank-ordering sports fans based on scoring probabilities, optimizing pricing strategies using secondary resale market insights, and spearheading data visualization platforms utilizing ticketing analytics. Additionally, he is an IEEE EMBS Member of the Technical Committee on Cardiopulmonary Systems & Physiology-Based Engineering, actively involved in reviewing research papers and presenting findings at international symposiums. His research background is extensive, having worked as a Senior Research Engineer at Quadrus Medical Technologies, where he developed emergency smart ventilators, remote patient monitoring systems, and data acquisition tools. His work on lung emulators integrated with medical devices has significantly contributed to respiratory performance analysis and patient care. Siddharth has also demonstrated expertise in predictive healthcare analytics, implementing machine learning algorithms for predicting Acute Kidney Injury and kidney disease progression, achieving high accuracy using neural networks and gradient boosting techniques. Furthermore, he has developed electronic health records (EHR) data extraction applications using Python, FHIR, and SQL, integrating them with leading medical databases such as EPIC, Cerner, and Allscripts. His experience as a Graduate Researcher at Columbia University further highlights his proficiency in applied robotics, exoskeleton control, and augmented reality for gait training. Notable achievements include implementing real-time parameter estimation for lung models, designing control algorithms for robotic systems, and publishing impactful research in high-impact journals such as IEEE Transactions on Neural Systems and Rehabilitation Engineering and Chemical Engineering Science. Siddharth's technical acumen spans a broad spectrum of programming languages, simulation tools, and prototyping techniques, including Python, TensorFlow, C++, MATLAB, Simulink, SolidWorks, and ANSYS. His work in machine learning-driven applications, predictive analytics, and control systems has been instrumental in advancing research in healthcare, automation, and robotics. With numerous publications, contributions to open-source projects, and accolades such as an honorary mention at the NYC Media Lab for his AR feedback application on HoloLens, he continues to drive innovation at the intersection of machine learning, healthcare, and robotics. His projects, ranging from Kalman filter-based meteorite tracking to PID-controlled drone stabilization and brain-computer interface EEG signal classification, demonstrate a well-rounded expertise in AI-driven systems and control engineering. His strong leadership in research and applied technology makes him a valuable contributor to the fields of robotics, biomedical engineering, and artificial intelligence-driven analytics.

• Keras
• PySpark
• Redshift
• C++
• C
• SQL
• Python
• Linux
• C#
• Data Analysis
• Matlab
• Data Science
• Solidworks
• MATLAB
• AutoCAD
• Arduino
• Tensorflow
• Raspberry Pi
• Git
• Simulink
• Inventor
• Blender
• Arduino IDE
• Cura
• ROS
• AWS Sagemaker
• Fusion360
• 3D Builder
• Visualization Tool Kit
• ANSYS CFD
• ANSYS CFX
• ANSYS ICEM-CFD
• ANSYS MECHANICAL APDL
• Simplify3d
• Sli3er
• PrusaSlicer
• HL7 Fundamentals
• Computational Motion Planning
• Sequence Modeling
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