John Hodge work email
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John Hodge personal email
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As a forward-thinking Senior Applied Scientist (machine learning engineer) at Amazon and former Senior Principal RF Engineer at Northrop Grumman, I bring over a decade of expertise in RF engineering, machine learning, and electromagnetics. With a Ph.D. in Electrical Engineering focused on Electromagnetics and Metamaterials from Virginia Tech, my career has been a testament to innovation and practical application in academia and industry. My experience includes innovative applications of generative artificial intelligence (AI) techniques to solve challenging technical problems. At Amazon, I helped develop the RFID-Enabled 'Just Walk Out' technology and capacitance sensors, delivering meaningful improvements in event detection accuracy and system efficiency. These projects enhanced customer experiences in retail environments and showcased the potential of intelligent technology in large-scale applications.My tenure at Northrop Grumman was marked by my technical leadership on the wideband phased array antenna system for aerospace applications and the groundbreaking development of a low-power, high-efficiency Ka-band antenna array. These contributions have met stringent performance standards and propelled defense and communication technology advancements.I push the boundaries of technology to solve complex problems and am continually seeking opportunities to apply my skills and knowledge. I'm always looking to grow my personal and professional network. Feel free to connect via LinkedIn or contact me directly at john.hodge.linkedin@gmail.com.Check out my work samples and hobby projects here: github.com/jman4162Technical Skills:Languages: Python, MatlabLibraries: NumPy, SciPy, PyTorch, Scikit-Learn, Pandas, AutoGluonDeveloper Tools: VS Code, PyCharm, Git, AWS (S3, SageMaker), InfluxDBFoundation and Large Language Models (LLM): ViT, Llama, BERTRF Modeling & Simulation: HFSS, Maxwell, CST, FEKO, TICRA, ModelCenter, ADS, SPICE Udacity Nanodegrees: Deep Learning with PyTorch, Machine Learning Engineer, Computer Vision, Natural Language Processing (NLP)Amazon Machine Learning University Courses: Day One Machine Learning, Computer Vision [Course Project Champion], Time Series Forecasting, Transformers for Computer Vision, ML for Leaders GenAI, Fine-tuning LLMs, Advanced Prompt Engineering for LLMs
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AmazonAmazonSeattle, Wa, Us
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Senior Applied Scientist (Machine Learning Engineer) | Amazon Web Services (Aws)Amazon May 2024 - PresentSeattle, Wa, UsAs a senior applied scientist and technical leader in the Amazon Web Services (AWS) Hardware Engineering Data Science & Analytics (DS&A) group, I leverage machine learning (ML) and big data analytics to address complex challenges that ensure the efficient operation of AWS data centers globally.My role involves developing and driving the machine learning technical vision, strategy, and implementation for AWS Hardware. I provide technical leadership in machine learning, including large language models (LLMs), natural language processing (NLP), and computer vision (CV).Key responsibilities include:- Leading team members to build and drive the data science and machine learning efforts for product development and operations.- Developing and implementing machine learning models and methodologies such as neural networks, recommendation systems, and Bayesian classification.- Ensuring the scalability and performance of our systems.- Collaborating across AWS to maintain the highest safety, security, and operational efficiency standards.
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Senior Applied Scientist (Machine Learning Engineer)Amazon Dec 2021 - May 2024Seattle, Wa, UsAs a Senior Applied Scientist at Amazon, I spearheaded significant initiatives within the cutting-edge realms of machine learning, capacitance sensing, and RFID technology, notably enhancing retail and event experiences. My primary contributions include:- Leadership in RFID Technology Deployment: I helped pioneer the development and implementation of RFID-Enabled 'Just Walk Out' technology, significantly boosting efficiency and customer satisfaction in NFL and MLB stadium retail stores. This technology led to a 60% increase in customer throughput, an 85% rise in transaction volumes, and a remarkable 112% growth in sales.- Innovations in Capacitive Sensing: As the technical lead for the frugal event detector project, my team achieved over 98% accuracy in real-time detection of shopping events using Bayesian machine learning algorithms during prototype testing. This role involved enhancing prototype sensor hardware and optimizing detection algorithms to ensure robust and scalable deployment.- Collaborative Research and Development: I directed a collaborative research initiative with the University of Washington, focusing on wireless power transfer technologies for retail applications. This project increased wireless transfer efficiency, demonstrating the potential of integrating advanced power solutions in consumer spaces.- Machine Learning and Algorithm Optimization: I led science efforts that substantially reduced error rates and improved system efficiency through strategic enhancements to antenna configurations. I also worked with a team to implement an attention-based transformer model for event detection.These experiences have equipped me with a profound expertise in applying advanced algorithms to real-world problems, optimizing system performance, and leading innovative projects that bridge the gap between theoretical research and practical application.
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Senior Principal Rf EngineerNorthrop Grumman Aug 2020 - Dec 2021Falls Church, Va, UsDesign & analysis of wideband phased array antenna systems for radar, electronic warfare (EW), and communication systems. Performs RF lead, systems engineering, and modeling & simulation roles. Applies machine learning, model-based systems engineering (MBSE), and multidisciplinary design, analysis, & optimization (MDAO) techniques to develop the next generation of RF sensor systems. -
Antenna & Rf Hardware EngineerNorthrop Grumman Apr 2016 - Aug 2020Falls Church, Va, UsAntenna & RF Design Engineer:- Design & analysis of wideband phased array antennas across various NG product lines- Performs antenna radiator & reflect-array design using HFSS, CST, FEKO, ADS, TICRA GRASP, and Matlab- Analysis of Active Electronic Scanning Array (AESA) antenna systems including digital beamforming (DBF)- Selected to Northrop Grumman's Mentoring the Technical Professional (MTP) programModel-Based Engineering (MBE) Lead on Business Capture Effort:- Applies analytical Model-Based Systems Engineering (MBSE) and Multidisciplinary System Design Optimization (MSDO) techniques to the design of complex phased array antenna system design to support business capture efforts- Linking hardware engineering performance models to system-level, mission-level, and financial cost modeling & simulation to support trade studies- Developed multidisciplinary Integrated Antenna Model framework to perform combined system trades and analysis of multifunction RF systems using disparate engineering performance and cost models- Integrates disparate engineering models using ModelCenter, Matlab, and Python- Presented "An Integrated Radar Model Solution for Mission Level Performance and Cost Trades" at the 2017 Defense + Security Conference (https://spie.org/Publications/Proceedings/Paper/10.1117/12.2261754) - Applying machine learning techniques to complex system design Co-founder of Internal Innovation Group InventNG:- Organized internal innovation hackathon competitions on Deep Learning and Additive Manufacturing- Participant teams have received ~$100k in follow-on innovation funding
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Antenna & Rf Hardware Engineer (Pdp)Northrop Grumman Aug 2014 - Apr 2016Falls Church, Va, UsCompleted Northrop Grumman's rotational Professional Development Program (PDP):Rotation #3: Monolithic Microwave Integrated Circuit (MMIC) Design Engineer- Design and analysis of microwave circuits in the GHz range- Utilizes modeling tools including HFSS, Cadence, ADS, and others- Working on range of circuit technologies include SiGe, GaN, GaAs, and othersRotation #2: Algorithms & Exploitation Systems Engineer- Used machine learning algorithms including neural networks to solve computer vision and object recognition problems- Developed internal software analysis tools using Objective-C and C/C++- Machine learning algorithm development and analysis using C/C++, Python, and Matlab- Analyzed large amounts of big data using statistical pattern recognition resulting in deliverables to customerRotation #1: RF Antenna Engineer- Worked as an antenna engineer in the RF Aperture Division- Design and analysis of Active Electronic Scanning Array (AESA) antenna technologies- Performs HFSS electromagnetic modeling and antenna test data analysis using MATLAB
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Graduate Research AssistantU.S. Army Ccdc Army Research Laboratory Jun 2012 - May 2014Adelphi, Md, Us- Metamaterial and antenna research as part of the Antenna & RF Technology Integration Team with Professor Amir Zaghloul- Performs analysis of electromagnetic structures using HFSS, CST, and FEKO electromagnetic simulation software packages to study negative index materials- Physical characterization of electromagnetic structures in an anechoic chamber -
Hardware Engineering InternNorthrop Grumman Electronic Systems Jun 2013 - Aug 2013Falls Church, Va, Us- Technical intern in Monolithic Microwave Integrated Circuit (MMIC) Design Group within RF Devices & Packaging Technology- Assists team of engineers in MMIC design group to create low noise amplifiers (LNA), high power amplifiers (HPA), mixers, switches, and bias and control circuitry, using GaAs pHEMT, mHEMT and HBT, GaN, InP, Si, and SiGe technologies- Performs microwave modeling and 3-D electromagnetic analysis of components using HFSS, ADS, and AWR Microwave Office- Analyzes microwave device components in various parts of the MMIC design process including circuit simulation (ADS and AWR), layout (Cadence and AutoCad), test, and foundry interface
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Pratt Undergraduate Research Fellow - Cummer LabDuke University Jan 2011 - May 2012Durham, North Carolina, Us- Selected as Pratt School of Engineering Undergraduate Fellow- Atmospheric electricity and terrestrial gamma-ray flash research studying high-energy processes in lightning- Developed MATLAB codes to streamline meaningful analysis of terabytes of remote sensing data on the radiation signatures of over 650,000 lightning flashes from all over the United States -
Summer Intern - University Of South Carolina Photonics & Microelectronics LaboratoryUniversity Of South Carolina Jun 2009 - Aug 2009Columbia, Sc, Us- Studying properties of materials such as AlGaN and GaN used to fabricate ultraviolet light emitting diodes (UV-LEDs)- Designed wet chemical etching techniques to perform parametric analysis of dislocation densities in silicon wafers- Experience using atomic force microscopy (AFM) and x-ray diffractometer equipment
John Hodge Skills
John Hodge Education Details
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Duke UniversityControl Systems -
Virginia TechElectrical And Electronics Engineering
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Virginia TechElectrical And Electronics Engineering
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UdacityDeep Learning
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The University Of QueenslandPhysics
Frequently Asked Questions about John Hodge
What company does John Hodge work for?
John Hodge works for Amazon
What is John Hodge's role at the current company?
John Hodge's current role is Amazon.
What is John Hodge's email address?
John Hodge's email address is jh****@****dge.com
What schools did John Hodge attend?
John Hodge attended Duke University, Virginia Tech, Virginia Tech, Udacity, The University Of Queensland.
What are some of John Hodge's interests?
John Hodge has interest in Leadership, Applied Physics, Machine Learning, Statistics, Investing/finance, Electromagnetics, Antennas, Signal Processing, Software Engineering.
What skills is John Hodge known for?
John Hodge has skills like Matlab, Electromagnetics, Antennas, Simulations, Rf, Python, Ansys, Microwave Engineering, Software Engineering, Java, Data Analysis, Signal Processing.
Who are John Hodge's colleagues?
John Hodge's colleagues are Irfan Masood, Venkata Prem Chand Adari, Mohammadali Niknamian, Felix Kipngetich, Sribin K, Humod Alharthi, Calvin R..
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