Aadesh Bagmar
Software Engineer II at Microsoft
Microsoft | Ex-Netflix | Ex-Soroco | UMD | NIT Surat
Aadesh is a graduate student at the University of Maryland, College Park (UMCP). He has worked as a Senior Software Engineer for three years in backend and data science technologies. Having handled terabyte-scale datastores, engineered analytical tools and solved open-ended problems, he is a complete engineer. 

He was an initial employee at Soroco where he helped them build their platform from ground-up for measuring employee productivity in performing software-related tasks. He has led teams and has the ability to build software that scales. He likes learning and working on challenging problems irrespective of the domain. 

He interned at Netflix this summer with their Customer Trust team. His project was on the automatic creation of rules to identify fraudulent behavior.

Aadesh has a Computer Science background from undergraduate education and is majorly focusing on Distributed Systems and Security for his Master's study.

He represented University of Maryland as a Security Scholar in RSAC 2020.
Microsoft
https://www.linkedin.com/company/microsoft
United States
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Software Engineer II
University of Maryland
https://www.linkedin.com/company/university-of-maryland
Research intern with the SEAM lab at UMD.
College Park, Maryland, United States
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Graduate Research Assistant
University of Maryland
https://www.linkedin.com/company/university-of-maryland
CMSC 424: Database Design
College Park, Maryland, United States
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Graduate Teaching Assistant
University of Maryland
https://www.linkedin.com/company/university-of-maryland
As a part of the SEAM lab, I am working on building a "Platform for structured discussions and peer review" under the guidance of Dr. Jim Purtilo. The project involves application of methods and techniques from Decision Making, Psychology and Human-Computer Interaction. The scale of the project also poses many engineering challenges. 

Team: https://seam.cs.umd.edu/team
College Park
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Graduate Research Assistant
Netflix
https://www.linkedin.com/company/netflix
Working with the Customer Trust Team. I am helping the team identify signals for Account Takeover and implementing models to detect fraudulent events. Created a statistical model to automatically identify ever-changing rules to identify fraudsters. 

On the side, I am working on a library to improve developer productivity to help them code faster in their Big Data Infrastructure. The library will soon be integrated in Netflix's core data science platform and will benefit more than 500 developers.
Los Gatos, California, United States
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Security Engineer
Soroco
https://www.linkedin.com/company/soroco-pvt-ltd
- Led a team of engineers to solve the problem of "Automated Discovery of Automatable processes" under the guidance of Dr. George Nychis and Shankar Natarajan. We applied this technology to measure human productivity while performing software related tasks and for finding automation opportunities.

- Built scalable and sophisticated tools, pipelines and methods to measure employee productivity and automation opportunities with high accuracy.

- Worked on building an analysis pipeline to process hundreds of millions of data points to discover repetitive sequences. Implemented and evaluated various clustering, data scrubbing and frequent pattern mining techniques on the collected datasets.

- Designed the system to be secure and GDPR compliant. Performed various tests using automated tools and did vulnerability analysis to ensure production-grade security. Used cryptography in a creative way to enable deleting of data (amounting to terabytes) within seconds of a request from the client.

- Built our own in-house deployment pipelines. Worked majorly on creating the entire end to end infrastructure to make this possible. The tool helped in setting up a server from scratch, building an environment for tools to run and managed automatic updates to more than 20 Microservices.

- Assisted various other teams in the organization by helping with brainstorming, code reviews, deciding the product roadmap and writing technical specifications. 

- Helped the organization with interviews, setting recruitment tests, and by going on on-campus recruitment drives.
Bangalore
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Senior Software Engineer - Backend / Core Platform
Soroco
https://www.linkedin.com/company/soroco-pvt-ltd
Bangalore
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Software Engineer - Backend / Core Platform
Tata Research Development and Design Centre (TRDDC)
https://www.linkedin.com/company/tata-research-development-and-design-centre-trddc
- Summer research intern under the guidance of Dr. Ehtesham Hasan and Dr. Swagat Kumar at the Multimedia and Robotics Lab, TCS Innovation Centre, Delhi.

- Worked on building an agent using LIDA (Learning Intelligent Distributed Agent), a
biologically inspired cognitive architecture to solve the problem of SLAM (Simultaneous Localisation and Mapping). It was a unique research problem where an autonomous agent was modeled on the human reaction system.

- I was the only undergraduate student to receive this internship in 2015. Was awarded 4/4 for the performance.
Gurgaon, India
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Summer Research Intern - Algorithms
National Institute of Technology Surat
https://www.linkedin.com/company/national-institute-of-technology-surat
- Worked on a project titled "Real-Time Facial Expression Recognition using Eigen Face Model" under the guidance of Dr. M.A.Zaveri. 

- The project was successful as it managed to achieve an accuracy of 96%. A research paper on the same topic was presented at the Section of Information Technology and Computer Science, Indian Science Congress, the University of Mumbai in January 2015.
Surat
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Summer Research Intern - Computer Vision
Master of Science - MS
Computer Science
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University of Maryland
https://www.linkedin.com/school/university-of-maryland/
Bachelor of Technology (B.Tech.)
Computer Engineering
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National Institute of Technology Surat
https://www.linkedin.com/school/national-institute-of-technology-surat/
12th Standard
High School/Secondary Diplomas and Certificates
Nath Valley School
Cutting Edge Visionaries
Committee member
The problems associated with open-ended group discussion are well-documented in sociology research. We seek to alleviate these issues using technology that autonomously serves as a discussion moderator. Building on top of an extensible framework called Diplomat, we develop a "conversational agent", ArbiterBot to promote efficiency, fairness, and professionalism in otherwise unstructured discussions. To evaluate the effectiveness of this agent, we recruited university students to participate in a study involving a series of prompted discussions over the Slack messenger app. The results of this study suggest that the conversational agent is effective at balancing contributions across participants, encouraging a timely consensus and promoting a higher coverage of topics. We believe that the results motivate further investigation into how conversational agents can be used to improve group discussion and cooperation.
Analyzing the Effectiveness of an Extensible Virtual Moderator
Proceedings of the ACM on Human-Computer Interaction
https://dl.acm.org/doi/10.1145/3492837
The vulnerability of the Lottery Ticket Hypothesis
has not been studied from the purview of Membership Inference Attacks. Through this work, we
are the first to empirically show that the lottery
ticket networks are equally vulnerable to membership inference attacks. A Membership Inference Attack (MIA) is the process of determining
whether a data sample belongs to a training set
of a trained model or not. Membership Inference
Attacks could leak critical information about the
training data that can be used for targeted attacks.
Recent deep learning models often have very large
memory footprints and a high computational cost
associated with training and drawing inferences.
Lottery Ticket Hypothesis is used to prune the networks to find smaller sub-networks that at least
match the performance of the original model in
terms of test accuracy in a similar number of iterations. We used CIFAR-10, CIFAR-100, and
ImageNet datasets to perform image classification tasks and observe that the attack accuracies
are similar. We also see that the attack accuracy
varies directly according to the number of classes
in the dataset and the sparsity of the network. We
demonstrate that these attacks are transferable
across models with high accuracy.
Membership Inference Attacks on Lottery Ticket Networks
ICML Workshop
https://arxiv.org/pdf/2108.03506.pdf
In this work, we add to the rich history of decision-support system research by implementing and evaluating a pilot implementation of a novel system, which we call Decidio. Our tool was integrated into a pre-existing decision-making process regularly conducted by 9 teams of undergraduate students. We find an overall positive response to Decidio based on the results of a tool evaluation survey that we conducted after our experiment. Furthermore, we conduct a Big-Five Factor personality survey of participants and associate personalities with interactions recorded by our tool. We find that the students who demonstrate leadership behaviors through their interactions score higher in extraversion and lower in conscientiousness than other students. Our analysis also reveals that agreeableness is strongly correlated with dissimilarity between group ranking outcomes and initially indicated individual preferences.
Decidio: A Pilot Implementation and User Study of a Novel Decision-Support System
Springer: International Conference on Group Decision and Negotiation
https://link.springer.com/chapter/10.1007%2F978-3-030-48641-9_14
The popularity of Python has risen rapidly over the past 15 years. It is a major language in some of the most exciting technologies today. This popularity has led to a large ecosystem of third party packages available via the pip package registry which hosts more than 200,000 packages. These third party packages can be reused by simply importing the package after installing using package managers like pip. The ease of reuse of third party software comes with security risks putting millions of users in danger. In this project, we study the ecosystem to analyze this threat.

The mature ecosystem of Python has multiple weak spots that we highlight in our project. First, we demonstrate how trivial it is to exploit the Python ecosystem. Then, we systematically analyze dependencies amongst packages, maintainers and publicly reported security issues. Most attacks are possible only if users install malicious packages. We thus try to analyze and evaluate different methods used by attackers to force incorrect downloads. We quantify our ideas by estimating the potential threat that can be caused by exploiting a popular Python package. We also discuss methods used in the industry to defend against such attacks.
I Know What You Imported Last Summer: A study of security threats in the Python ecosystem
Arxiv
https://www.arxiv-vanity.com/papers/2102.06301/
A technique to analyse and classify Facial Expression successfully. The abstract can be found in the Proceedings of the Indian Science Congress, Section of Information Technology including Computer Science, University of Mumbai.
Real Time Facial Expression Recognition
Section of Information Technology, Indian Science Congress, University of Mumbai
Part of a three member winning team at Cairn India's annual competition Amazing Champions of Energy. A presentation making and delivering competition for suggesting energy reforms to the government. Awarded Rs. 1 Lakh.
Cairn India
Winners at Cairn India's ACE III
Part of a 5 member winning team at a hardware hackathon organized at Center for Innovation, Incubation and Entrepreneurship, Indian Institute of Management, Ahmadabad.
CIIE, IIM Ahmedabad
Winners at Make-a-thon
IMO
Ranked 1 in the school in International Mathematics Olympiad.
Advanced Database Architecture
CMSC 624
Graduate Security
CMSC 818O
Human Computer Interaction
CMSC838J
Algorithm Analysis and Design
CO303
Computer Networks
CO307
Data Structures
CO203
Database Management System
CO204
Discrete Mathematics
MH2013
Microprocessor and Interfacing Technology
CO301
Principles of Programming Languages
CO305
Theoretical Computer Science
CO202
In this work, we explore the potential of reinforcement learning to learn a policy for buffer management. In particular, we propose a Q-Learning based framework focusing on page replacement task for predictive workloads. During the execution of a workload and when the buffer is full, our system proposes a page in the buffer for eviction. Our system learns from past execution and creates a generalized, easy to implement a solution that databases can adopt. Our simulation results demonstrate that our approach outperforms existing algorithms in certain cases suggesting the benefit of bringing modern learning-based techniques into traditional database system design
Buffer Pool management with Reinforcement Learning
https://github.com/cardwizard/DatabaseDeepQL
Interactive multiplayer gaming has always been an active area of development. However, most games rely on external devices for input, such as a keyboard, mouse, PS4 controllers, etc. These devices support a limited set of actions including button presses or joystick movements and are often lacking motion-sensing capabilities. In addition to this, most of these devices are expensive ($50-$60). Smartphones on the other hand are ubiquitous and consist of a rich set of sensors that let users control and interact with the environment. In our research, we show how a smartphone can be used as a low-latency input device for playing real-time multiplayer games. We show that information from smartphone sensors can be used to do basic motion sensing. Our method allows users to perform natural actions, such as steering a wheel, as opposed to keypresses while playing racing games in order to provide a more immersive gaming experience.
Corona Partybox: Turning your mobile phone into a gaming controller
https://github.com/cardwizard/CoronaPartyBox
This project was funded by Office of Naval Research. A poster on the same topic was a finalist at RSA conference 2020. 

A paper is under review at USENIX Security 2020.
Empirical Study of PyPI
https://github.com/cardwizard/vulnerable-python-ecosystem
A model of databases where no one needs to entity trusts the other. The model also allows hosting as a service model where an untrusted client can query data from an untrusted publisher who gets paid for amount of data retrieved.
SafeDB Architecture and Structure -- A move towards Decentralized Internet
https://github.com/cardwizard/UntrustedContractor
QuickUI is a tool to instantly create a usable UI from any python file which has a CLI created using the Argument Parser.
Quick UI
https://github.com/cardwizard/QuickUI
Utility to help search within a set of jupyter notebooks I worked on creating a simple magic function to help us make this search easy and search across notebooks present in the current directory. It uses whoosh in the back-end to speed up the search. The code iterates through every cell in every notebook in your current directory.
Jupyter Search Magic
https://github.com/cardwizard/JupyterSearch
Created a browser extension (pushed to the chrome store) which summarizes a given blob of text into the most relevant pieces. If a user installs this extension, he can select large blobs of text on his screen and a summary will be shown on the side bar.
Text Summarizer
https://github.com/cardwizard/Summarizer
Created a library for easily operating and visualizing Elliptic Curves
Elliptic Curves Visualizer
https://github.com/cardwizard/EllipticCurves
Taking a bus? Check BusBuzz - a mobile app that buzzes you the current location and expected head count in your bus
Bus Buzz
https://github.com/cardwizard/HackInout
Second Runners-up at InOut 3.0.

When a patient arrives at a clinic, the MedConnect mobile app scans his/her Aadhar card and retrieves all the related past medical data. The medical personnel posted in the local clinic, or other authorized personnel can have access to all this data while making a diagnosis for a particular patient through a web dashboard. This data gets stored in a centralized server and can be accessed by a medical personnel with access even if the patient travels outside his local region.

Other features include:

The dashboard can be used to give various insights including what types of diseases are common in a region and adjoining areas, thus deciding what stock of medicines should be available in stock at nearby medical stores. Insights can also be gained towards preventing epidemics.

It can also provide analysis and visualizations about various classes of diseases and can help in tracking their sources.

The mobile application also indicates whether a particular villager can take benefit of a government policy ('Yojna') to avail medicare benefits.
Med Connect
https://devpost.com/software/medconnect-ds1utn
A smart attendance software was developed which combines Computer Vision and Databases. The project involved Face Recognition being implied to mark a students presence in classroom. 
Entry Time and Exit Time of a student is noted and according to the time interval, his attendance is marked in respective lectures. 
The data is then stored to a file, which is retrieved by a database handling system.This can be used by an administrator who can Query it to extract relevant information. 
The project works completely in real time. 
Technologies used:
Database managed using SQLite.
Face Recognition using Eigen Face models in OpenCV Libraries.
GUI using Qt C++.
Smart Attendance (OpenCV, Qt C++, SQLite3)
https://github.com/cardwizard/Smart-Attandence
Owing to a lot of recent thefts at our hostels, a simple camera based system was developed using OpenCV libraries. The intrusion detector uses contour mapping and background subtraction for checking possible trespassers. If something suspicious if found, it snaps a photograph and mails it to the owner using SSMTP.
Intrusion Checker
https://github.com/cardwizard/Intrusion-check
An OpenCV project to control and move around web pages by just moving your eyes. The system uses Haar Cascades for eye detection, Otsu's method for Eye-ball detection. It uses simple transforms and linux utilities to scroll through web-pages. 
The working can be seen here: https://www.youtube.com/watch?v=GRRLHxzkbtY
Eye Scroller
https://github.com/cardwizard/Eye-Scroller
A large number of car accidents occur due to drunken driving/driver fatigue. A system to keep driver fatigue/unusual behavior was built. It checks for non-periodic blinking rate to analyse this. Working can be seen here: https://www.youtube.com/watch?v=NGCRkPrcQkQ
Driver Fatigue Monitor
https://github.com/cardwizard/Sleepy-Face-Detection
A project built for the use of differently-abled. Control your computer mouse by minute head movements. Under development stage.
Mouse Control using Head Movement
https://github.com/cardwizard/Mouse-Control
A software system using OpenCV libraries and basic mathematical modelling to analyze and classify Human Expressions was developed. It uses Eigen Face Model for creating individual expression models and Euclidean Distance for classification. The system showed a 96% accuracy for user created Databases. The project was funded by Research and Consultancy Division, NIT Surat.
The demonstration can be seen here: https://www.youtube.com/watch?v=wotYK6CmyuM
Facial Expression Recognition
https://github.com/cardwizard/Facial-Expression-Recognition
Scrum Alliance
bcert.me
980627
Certified ScrumMaster® (CSM®)
http://bcert.me/swxbewudo
https://www.linkedin.com/in/thakeraj
Los Angeles, CA
Raj Thaker
Google | Supplyframe | Amazon AWS | JPMorgan Chase | USC ICT  | MS-CS: USC
https://www.linkedin.com/in/aarushi-arya
Cranberry Township, PA
Aarushi Arya
Software Engineer at Google | MS in CS |
https://www.linkedin.com/in/varunsinghai
Washington DC-Baltimore Area
Varun Singhai
Software Engineer @ Google
https://in.linkedin.com/in/darshit-patel-37176ba5
Bengaluru
Darshit Patel
Software Engineer II at Microsoft
https://www.linkedin.com/in/ishitaverma17
San Francisco Bay Area
Ishita Verma
Software Engineer at Adobe
https://in.linkedin.com/in/kushagra-dixit-34381262
Delhi, India
Kushagra Dixit
Software Development Engineer-1 at OYO
https://www.linkedin.com/in/mahaleamit
San Mateo, CA
Amit Mahale
Data @ Netflix
https://www.linkedin.com/in/srivatsan-srinivasan
Cranbury, NJ
Srivatsan Srinivasan
Computer Science and Statistics Student at University of Maryland, College Park
https://www.linkedin.com/in/samyadeep-basu-20816174
United States
Samyadeep Basu
CS PhD at UMD |  Prev: Applied Scientist @ Microsoft AI
https://www.linkedin.com/in/naman-awasthi
College Park, MD
Naman Awasthi
Graduate Research Assistant at University of Maryland - College of Computer, Mathematical, and Natural Sciences
https://www.linkedin.com/in/varunin
Cambridge, MA
Varun Kumar
Senior Applied Scientist @ Alexa || UMD CS Alumni
https://www.linkedin.com/in/paaras-bhandari
College Park, MD
Paaras Bhandari
MS CS @ University of Maryland
https://www.linkedin.com/in/rushabhushah
College Park, MD
Rushabh Shah
Computer Science at UMD
https://www.linkedin.com/in/rohanchandra30
College Park, MD
Rohan Chandra
Applied Research Intern at NVIDIA
https://www.linkedin.com/in/wenbingbai
San Francisco Bay Area
Wenbing Bai
Senior Software Engineer at Netflix, ex-Cruiser
https://www.linkedin.com/in/daniel-holten-5a9250162
Rockville, MD
Daniel Holten
Software Development Instructor at Capital One
https://www.linkedin.com/in/shaila-zaman
Houston, TX
Shaila Zaman
Computer Science Ph.D. Student | Machine Learning | Affective Computing | Scholar @ GHC, Tapia, Grad Cohort
https://www.linkedin.com/in/akriti-anand
Greater Seattle Area
Akriti Anand
Software Development Engineer at Amazon
https://www.linkedin.com/in/mdagar
New York, NY
Monika Dagar
Data Scientist at Intuit
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I am very pleased to share that I joined Apple this week as a Field Design Engineer. It was a long journey to this day and I cannot be more excited…
Liked by Aadesh Bagmar
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As we approach the ☃️ holiday season and a🍾 New Year, might I propose new 💼  employment at 📊 🧱 Databricks. We are 🦸 assembling a 🥇 dream team…
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Photo
Internships and Interns
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SQL Careers
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Machine Vision, Computer Vision, Image Processing in India
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S. V. National Institute of Technology Surat
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2020 Netflix Interns
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AI Tribune
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Computer Vision and Pattern Recognition
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Computer Vision
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OpenCV Computer Vision
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Computer programming knowledge
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