aditya thakur
Senior Firmware Engineer at Enel X
senior firmware engineer enel x
graduate student electrical engineering department missouri university science technology . passion find trend variety data set use analyze property world . expert development implementation electronic appliance thorough knowledge machine learning , embedded system , control application lead innovate new thing improve existing technology .
Enel X
https://www.linkedin.com/company/enelx
San Carlos, California, United States
https://media-exp1.licdn.com/dms/image/C4D0BAQHJx61RKJp0Lw/company-logo_100_100/0/1519900455741?e=1655942400&v=beta&t=xYNhcRmwvpOCpc4T46VeoFMgrwjyaOB2rLsl4ZffVI8
Senior Firmware Engineer
Enel X
https://www.linkedin.com/company/enelx
• Acquisition of EMotorwerks into Enel X Emobility in September 2019
• Worked on ucOS II based RTOS to design firmware for EVSE's
• Developed methodology to do Over-the-air (OTA) Updates for the system.
San Carlos, California, United States
https://media-exp1.licdn.com/dms/image/C4D0BAQHJx61RKJp0Lw/company-logo_100_100/0/1519900455741?e=1655942400&v=beta&t=xYNhcRmwvpOCpc4T46VeoFMgrwjyaOB2rLsl4ZffVI8
Firmware Engineer
eMotorWerks, Inc
https://www.linkedin.com/company/electric-motor-werks-inc-
• Worked on Firmware of Charging Stations for Electric Vehicles to control and monitor the Energy supplied to EV's.
• Wrote Device Drivers to talk with RFID, Wifi and Bluetooth/BLE modules by means of SPI and UART to support Authentication, Wifi Provisioning and Payment Gateway support
• Developed Firmware and Production scripts in Embedded C and Python to automate programming, configuration and Calibration of Charging stations
San Francisco Bay Area
https://media-exp1.licdn.com/dms/image/C4D0BAQEH85w2f8WqOw/company-logo_100_100/0/1519920757646?e=1655942400&v=beta&t=X8xbysy_r1Bx8VfAnXiKGNsEDTqDmhd4TNls2oxK6jU
Firmware Engineer
Missouri University of Science and Technology
https://www.linkedin.com/company/missouri-university-of-science-and-technology
• Taught Control systems laboratory sessions for up to 30 students
• Supervised implementation of control systems in computers using MATLAB, LabVIEW & Simulink
• Instructed as teachers assistant and graded all coursework and administered tests
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Research topic – A subsystem to solve differential equations for controls and image processing
• Designed a computationally inexpensive algorithm for Mono-cam pseudo stereo-vision algorithm to extract world features and design an environment on-board
• Built a test-bed on PC/104 and PCIe hardware for testing control systems applications using obtained features
Greater St. Louis Area
https://media-exp1.licdn.com/dms/image/C4D0BAQFRrbXLE-AmfQ/company-logo_100_100/0/1642089790943?e=1655942400&v=beta&t=Ine4USrNpGC6JtSAV9pIDwdfdOUoKkZ58Pqo9sDjsU4
Graduate Research and Teaching Assistant
Reliance
https://www.linkedin.com/company/reliance
• Worked on plant-wide installation of Salmoiraghi’s new product handling system
• Implemented new interface for batch code of older PLC machines with old Bar-code scanners to avoid replacement of hardware and to save the cost of replacement
Navi Mumbai
https://media-exp1.licdn.com/dms/image/C4D0BAQH2BVoPsZOvJg/company-logo_100_100/0/1585115801797?e=1655942400&v=beta&t=4D4RuWsDWOXLm2NXhyMhVbYJLgPsOuTAwnk0S7dlOII
Electrical Engineering Intern
Master of Science (M.S.)
Graduate Teaching Assistant							Jan 2016 – Present
•Taught Control systems laboratory sessions for up to 30 students
•Supervised implementation of control systems in computers using MATLAB, LabVIEW & Simulink
•Instructed as teachers assistant and graded all coursework and administered tests
Graduate Research Assistant							Oct 2015 – Present
Research topic – A subsystem to solve differential equations for controls and image processing
•Designed a computationally inexpensive algorithm for Mono-cam pseudo stereo-vision algorithm to extract world features and design an environment onboard
•Built a test-bed on PC/104 hardware for testing control systems applications using obtained
Electrical and Electronics Engineering
https://media-exp1.licdn.com/dms/image/C4D0BAQFRrbXLE-AmfQ/company-logo_100_100/0/1642089790943?e=1655942400&v=beta&t=Ine4USrNpGC6JtSAV9pIDwdfdOUoKkZ58Pqo9sDjsU4
Missouri University of Science and Technology
https://www.linkedin.com/school/missouri-university-of-science-and-technology/
Machine Learning Nanodegree
Machine Learning
https://media-exp1.licdn.com/dms/image/C560BAQGAbiASb657Fg/company-logo_100_100/0/1639683820896?e=1655942400&v=beta&t=VoAj7tltPTdUB0DrFxCI7Tut4a3ckoMlfyLkHDu8OyU
Udacity
https://www.linkedin.com/school/udacity/
Bachelor of Engineering (BE)
• Technical Head Of Robotics Club
• 2nd Runner Up In Robocon India 2013
• Organized Events such as Robotics Workshops, Band Competitions,
Electronics and Communications Engineering
https://media-exp1.licdn.com/dms/image/C4E0BAQEFsIyAZyuMwA/company-logo_100_100/0/1519904707827?e=1655942400&v=beta&t=W-Kse5HEzNqSoNXrXJgS7favNQUQjMZ5bBZniXvxrqA
University of Pune
https://www.linkedin.com/school/university-of-pune/
Compromised smart meters sending false power consumption data in Advanced Metering Infrastructure (AMI) may have drastic consequences on the smart grid»s operation. Most existing defense models only deal with electricity theft from individual customers (isolated attacks) using supervised classification techniques that do not offer scalable or real time solutions. Furthermore, the cyber and interconnected nature of AMIs can also be exploited by organized adversaries who have the ability to orchestrate simultaneous data falsification attacks after compromising several meters, and also have more complex goals than just electricity theft. In this paper, we first propose a real time semi-supervised anomaly based consensus correction technique that detects the presence and type of smart meter data falsification, and then performs a consensus correction accordingly. Subsequently, we propose a semi-supervised consensus based trust scoring model, that is able to identify the smart meters injecting false data. The main contribution of the proposed approach is to provide a practical framework for compromised smart meter identification that (i) is not supervised (ii) enables quick identification (iii) scales classification error rates better for larger sized AMIs; (iv) counters threats from both isolated and orchestrated attacks; and (v) simultaneously works for a variety of data falsification types. Extensive experimental validation using two real datasets from USA and Ireland, demonstrates the ability of our proposed method to identify compromised meters in near real time across different datasets.
Towards Fast and Semi-supervised Identification of Smart Meters Launching Data Falsification Attacks
ASIACCS2018
https://dl.acm.org/citation.cfm?id=3196551
Compromised smart meters reporting false power consumption data in Advanced Metering Infrastructure (AMI) may have drastic consequences on a smart grid's operations. Most existing works only deal with electricity theft from customers. However, several other types of data falsification attacks are possible, when meters are compromised by organized rivals. In this paper, we first propose a taxonomy of possible data falsification strategies such as additive, deductive, camouflage and conflict, in AMI micro-grids. Then, we devise a statistical anomaly detection technique to identify the incidence of proposed attack types, by studying their impact on the observed data. Subsequently, a trust model based on Kullback-Leibler divergence is proposed to identify compromised smart meters for additive and deductive attacks. The resultant detection rates and false alarms are minimized through a robust aggregate measure that is calculated based on the detected attack type and successfully discriminating legitimate changes from malicious ones. For conflict and camouflage attacks, a generalized linear model and Weibull function based kernel trick is used over the trust score to facilitate more accurate classification. Using real data sets collected from AMI, we investigate several trade-offs that occur between attacker's revenue and costs, as well as the margin of false data and fraction of compromised nodes. Experimental results show that our model has a high true positive detection rate, while the average false alarm rate is just 8%, for most practical attack strategies, without depending on the expensive hardware based monitoring.
Statistical Security Incident Forensics against Data Falsification in Smart Grid Advanced Metering Infrastructure
ACM Codaspy 2017
http://dl.acm.org/citation.cfm?id=3029833&CFID=914599625&CFTOKEN=18097688
ABU Robocon
2nd Runner Up - National Robocon 2013
Autonomous Mobile Robots
EE 5380
Computational Intelligence
EE 5310
Digital Control
EE 5300
Embedded Processor System Design
CPE 5160
Linear Control Systems
EE 6300
Neural Netwrks For Controls
EE 5320
Optimal Control and Estimation
EE 6310
Real-Time Systems
CPE 5170
Computer Networks
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Digital Signal Processing
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Electronic Product Design
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Embedded Systems and RTOS
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Microcontroller and Applications
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VLSI Design and Technology
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Reinforced Learning
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Supervised Learning
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Unsupervised Learning
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Created a Prediction model for Monsoon using 60 years of Atmospheric Data
Added factors affecting monsoon to the model such as Indian Ocean Dipole effect, ENSO, etc.
Obtained model gave above 90% accurate results
Monsoon rainfall Onset and Intensity prediction Model
https://github.com/astvd3/Monsoon-Prediction-Model
Reviewed unstructured data to understand the patterns and natural categories that the data fits into. Used multiple algorithms and both empirically and theoretically compared and contrasted their results. 
Made predictions about the natural categories of multiple types in a dataset, then checked these predictions against the result of unsupervised analysis.
Creating Customer Segments
https://github.com/astvd3/creating_customer_segments
Identified the factors that affect a consumer to become potential defauter. 
Trained and tested several supervised machine learning models on a given dataset to predict how likely a consumer is to default. 
Implemented a GUI for the convenience of both the Credit card users and the service provider.
Potential Credit Card Defaulter Classifier
https://github.com/astvd3/Credit-defaulter-classifier
Applied reinforcement learning to build a simulated vehicle navigation agent in Python. 
This project involved modeling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties
Train a Smartcab How to Drive
https://github.com/astvd3/Training-smartcab
Investigated the factors that affect a student's performance in high school. 
Trained and tested several supervised machine learning models on a given dataset to predict how likely a student is to pass. 
Selected the best model based on relative accuracy and efficiency
Building a Student Intervention System
https://github.com/astvd3/student-intervention-system
Built a model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. 
Identified the best price that a client can sell their house utilizing machine learning.
Predicting Boston Housing Prices
https://github.com/astvd3/boston_housing_price_prediction
• Designed and implemented MP3 player using 8051 micro-controller.
• supported SD card FAT 16/32 FILE TYPE.
• Implemented I2C, SPI protocols for communication between microcontroller,SD card and MP3 decoder.
Intel MCS-51 Microconroller based MP3 player
•	Developed a robot platform to solve a chicken n' egg problem in autonomous robots, where a robot placed in an unknown environment starts to recognize and map the world around itself
•	Implemented a navigation algorithm to test the extracted and created world with the support of Encoders and On-board sensors while estimating its current position
Self-Localizing and Relocating Robot Platform
• proposed a scheme to recognize the entire set of handwritten English characters andnumbers by the use of Artificial Neural Networks.
• Tests were conducted with various Training algorithms, activation functions and Network Architectures to find a network with best performance index
Handwriting Recognition Using Supervised  Neural Networks
• Created a neural network based weather model in MATLAB, learning from 2 years of historical weather data, giving out up to 92% accurate weather forecasts
• Produced the network that it calibrates itself from the obtained and calculated data
• Implemented a GUI to visualize the ongoing weather predictions.
Configurable Self-learning Adaptive Weather Model
• Built a cost effective quadcopter platform from scratch, Obtained product was found to be with 60% reduction in cost of building
• Obtained Quadrotor was found to be navigating perfectly in Waypoint navigation mode and headless modes
• Implemented an ability to generate a 3D Map by extracting features from world around itself using single camera
A Waypoint navigated Quad-rotor platform.
https://skinnysatan.wordpress.com/2015/01/14/building-a-quadcopter-from-scratch-diy-part-1/
• Developed a master-slave swarm based networking concept for connecting electric modules
• Hosted a wireless server on a micro-controller with 16KB of memory and was connected to all household appliances
Home Automation system
• Created a cost effective solution was for an electric measurement instrument. 
• Implemented speech recognition and processing onboard on a microcontroller having processing speed of 16MHz
Multi-Lab tool with onboard Speech Processing and recognition
https://hackaday.io/project/1057-dmm-that-listens-and-talks
• Developed a wearable sensor glove with multiple sensors attached to it to perform a certain tasks on multiple motor controlled applications
• Ported the project later on to be able to work with the gesture recognition through image processing
• Published the project on multiple technical blogs like Atmel corps, Hackaday, etcetera
Hand Gesture Operated Motorized Vehicle for Warehousing and transport.
http://blog.atmel.com/2013/08/20/this-motorized-skateboard-is-controlled-by-hand-gestures/
Federal Communications Commission
Extra
Amateur Radio License
Coursera
www.coursera.org
4DJSP2Q4A6WZ
Applied Plotting, Charting & Data Representation in Pytho
https://www.coursera.org/account/accomplishments/verify/4DJSP2Q4A6WZ
Coursera
www.coursera.org
H278Y66CRMEX
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
https://www.coursera.org/account/accomplishments/verify/H278Y66CRMEX
Coursera
www.coursera.org
M6JRHRHXCFVN
Introduction to Data Science in Python
https://www.coursera.org/account/accomplishments/verify/M6JRHRHXCFVN
Coursera
www.coursera.org
FY3G7CK5RZLH
Neural Networks and Deep Learning
https://www.coursera.org/account/accomplishments/verify/FY3G7CK5RZLH
Coursera
www.coursera.org
SS4FQSFXAFND
Structuring Machine Learning Projects
https://www.coursera.org/account/accomplishments/verify/SS4FQSFXAFND
Udacity
printer.udacity.com
Machine Learning Engineer Nanodegree
https://printer.udacity.com/certificate/nd009
https://www.linkedin.com/in/yves-jc-galang-0a879365
South San Francisco, CA
Yves JC Galang
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https://www.linkedin.com/in/triciacate
San Mateo, CA
Tricia Cate
HW Eng Mgr | EV Enthusiast
https://www.linkedin.com/in/jenyak
San Francisco Bay Area
Jenya Kirshtein
Product Manager - Energy Services at Enel X e-Mobility
https://www.linkedin.com/in/agnesfucompliance
San Francisco Bay Area
Agnes Fu
Regulatory Compliance Professional | Compliance Program Manger |  Certification Manager | Product Compliance Engineer | Homologation Engineer
https://www.linkedin.com/in/danielfeldman
New York, NY
Daniel Feldman
VP of Product Management, eMobility at Enel X
https://www.linkedin.com/in/tushar-mumbaikar-205339100
Richardson, TX
Tushar Mumbaikar
Graduate student at University of Texas at Dallas | ITM | Supply Chain Management | SAP EWM | SAP SD | SAP MM | SAP FI | SAP SD-FI, MM-FI, SD-MM & MM-WM Integration
https://au.linkedin.com/in/sharvari-bhuskute-943b977a
Greater Adelaide Area
Sharvari Bhuskute
Senior Transport Engineer at Mott MacDonald
https://in.linkedin.com/in/vishal-kanungo-221667177
Amravati
vishal kanungo
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https://in.linkedin.com/in/prajyot-borkar-73b71599
Pune
Prajyot Borkar
Student at Symbiosis institute of technology
https://in.linkedin.com/in/atish-kamble-8517938b
Pune
Atish Kamble
TCS - Assistant Manager
https://in.linkedin.com/in/sushil-patil-5096a1141
Pune
Sushil Patil
Design Engineer At Atlas Copco & Jr. Engineer at Actualize
https://in.linkedin.com/in/vermasunny741
Jamnagar
Sunny Verma
Senior Manager Operations at Reliance industries Limited
https://in.linkedin.com/in/shilp-agrawal-4828a399
Gurgaon
Shilp Agrawal
Management Consultant, Deloitte India
https://in.linkedin.com/in/fathimath-shahziya-a4501066
Kasaragod
Fathimath Shahziya
Senior Embedded Software Engineer at Robert Bosch Engineering and Business Solutions Vietnam
https://in.linkedin.com/in/vivek-devane-04991173
Hyderabad
Vivek Devane
Content Head and lead at EssentiallySports.com
https://www.linkedin.com/in/samrudha-karangale
Decatur, GA
Samrudha Karangale
Senior Firmware Engineer at Acuity Brands
https://www.linkedin.com/in/anushavbhatta
Austin, Texas Metropolitan Area
Anusha Venkatesha Bhatta
Senior Firmware Engineer at AMD
https://www.linkedin.com/in/bhumimistry
Milpitas, CA
Bhumi Mistry
Secure Software Engineer at NXP Semiconductors
https://www.linkedin.com/in/tanmay-sane-32a19228
Conyers, GA
Tanmay Sane
Firmware Engineer at Acuity Brands
https://www.linkedin.com/in/omkarnjoshi
Santa Clara, CA
Omkar J.
Firmware Engineer at COMET Technologies USA, Inc.
Liked by Aditya Thakur
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Best overall Level 2 charger in the market. Check out the JuiceBox.https://lnkd.in/diwx7J7P
https://in.linkedin.com/in/aditya-thakur-0a28149b
Mumbai
Aditya Thakur
Digital Manager at Mindshare | Ex-iProspect
https://in.linkedin.com/in/aditya-thakur-5b620ba0
Jabalpur
aditya thakur
Information Technology and Services Professional
https://in.linkedin.com/in/aditya-thakur-1033a013
New Delhi
Aditya Thakur
Regional Sales Head  at TRULYY INDIA HOTELS AND RESORTS PRIVATE LIMITED
https://in.linkedin.com/in/aditya-thakur-2624a843
Gurugram
Aditya Thakur
Project Manager at Orange Business Services
https://in.linkedin.com/in/aditya-thakur-a7496a88
Noida
Aditya Thakur
Biomechanics Research Group
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https://www.linkedin.com/groups/4611991
Embedded Technologies
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https://www.linkedin.com/groups/89333
Automation
https://media-exp1.licdn.com/dms/image/C4E07AQG3SeyuiJ4Z7Q/group-logo_image-shrink_92x92/0/1631004949948?e=1647691200&v=beta&t=zIMWX6QbmfxYrRFV_2lPOYUcCoD9wZPKMwaQLc8K_Q8
https://www.linkedin.com/groups/68581
ARM Based Group
https://media-exp1.licdn.com/dms/image/C4E07AQEuI1n5ti8VmQ/group-logo_image-shrink_92x92/0/1631001277118?e=1647691200&v=beta&t=I2aZvNmTCUQzYpziqPluaiQ88wYiEUMrDV9dyIDOaWY
https://www.linkedin.com/groups/85447
Electronics Industry Worldwide
https://media-exp1.licdn.com/dms/image/C4D07AQGag9ggq43Gtg/group-logo_image-shrink_200x200/0/1631377164368?e=1647691200&v=beta&t=zz0u2LsGN8PUIwfmvo04Rw3l_ooM4S8T0LSEFdSTZJQ
https://www.linkedin.com/groups/3249049
Machine Learning and Data Science
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https://www.linkedin.com/groups/4298680
Udacity Alumni Network
https://media-exp1.licdn.com/dms/image/C4D07AQFKSYRiYIMk8A/group-logo_image-shrink_200x200/0/1631361427903?e=1647691200&v=beta&t=JsW-p4lCPV6vICQn0qdI87EorfXG8ifWZyjEQJedquE
https://www.linkedin.com/groups/8209939