Akarsha Sehwag

fos4X

Data Scientist

Working as a data scientist at fos4X (rotor-blade sensing in wind-turbines) in Analytical Software and Model(ASM) team to provide smart monitoring solutions to the customer.

Airtel XLabs

Associate Data Scientist

Worked at the R&D segment of the fourth largest mobile network operator in the world. I joined as a Trainee in Data Science Team, and worked on a high-impact project; Segmentation of over 300 Million customers in order to perform experiments on relevant customer group, to make data-informed strategies and improve our customer journey. I also contributed to Network Site Planning, to predict the next most suitable location for cell tower/site.

UnternehmerTUM

Artificial Intelligence Intern

Interned as an AI Engineer at Digital Product School (a program by UnternehmerTUM) as a part of a cross-functional, international, culturally-diverse team wherein we learned to apply Agile development principles (and design thinking) to build our Minimum Viable Product(MVP). Our product lets foreign tourists experience a city based on their interests through personalized tours guided by an autonomous (Level 4) car. We also generated useful insights from user interviews & product testing.
Company sponsors: Audi, BMW and ADAC. Reference: Dr. Afsaneh Asaei (AI head of UnternehmerTUM)

Stanford University

Data Analysis Intern

• Predict time series data on national level and map it to all the states. Achieved state-of-the-art results. (Journal in writing)

• Predicted change in contribution and productivity of STEM workers in the financial sector using NLP models. Reference: Dr.Christos

• Worked with Prof. Prithwiraj Choudhury from Harvard Business School on the analysis & predictions of salary variations w.r.t. country and companies.

IIIT Delhi

Teaching Assistant (Algorithm Design and Analysis)

Teaching Assistant for a class of 250+ students. I was responsible for:

• Making questions for Quizzes and Assignments.

• Checking the answer sheets (Assignments and Exams).

• Taking tutorials once a week for practice.

• Assisting the visually impaired student.

Image Analysis and Biometrics Lab

Undergraduate Researcher

Worked on three major research projects:

• Attribute Classification in Low Resolution: Inspired by real-life datasets involving as small as 32*32 face image resolution, I used Multi-Task Convolutional Neural Networks to improve accuracy of the state-of-the-art models in Attribute Classification.

• Morphing using GANs: Created a new architecture for Generative Adversarial Network to take in two face image inputs instead of noise vector and generate a morphed image of the two.

• Fooling Presentation Attack Detection Algorithms: Work described in the publications section.