Darshan Batavia

AI Researcher

India9 yrs 10 mos experience

Highly Stable

Key Highlights

Ph.D. in Computer Science with expertise in image processing.
Developed algorithms for topological image analysis.
Passionate about data-driven insights in crypto trading.

Stackforce AI infers this person is a Quantitative Researcher specializing in Fintech and Algorithmic Trading.

Contact

Skills

Core Skills

Quantitative ResearchComputer ScienceSignal Processing

Other Skills

Algorithm DevelopmentAlpha GenerationAnalytical SkillsComputer VisionCreative Problem SolvingData ScienceDigital Image ProcessingFinanceFinancial ModelingGraph Signal ProcessingImage DenoisingImage ProcessingLaTeXMachine LearningPattern Recognition

About

Quantitative Researcher in crypto trading | Exploring data-driven insights for market success. Passionate quantitative researcher specialising in mid frequency trading. With a strong foundation in quantitative finance and data analysis, I thrive on unmasking the market movements through my algorithms. The curiosity of unraveling market patterns fuels me to develop innovative strategies that helps navigate trading in the dynamic and ever-evolving markets. Previously, I completed my Ph.D. in computer science from Technical University Vienna, Austria with an academic experience of 5+ years in image processing, signal processing, and pattern recognition. I am skilled in python, Matlab, machine learning, and quantitative research.

Experience

Self-employed

Quant

Feb 2024 – Present · 2 yrs 1 mo · Remote

Nexo

Quantitative Researcher

Sep 2022 – Mar 2024 · 1 yr 6 mos

Vienna university of technology

2 roles

PHD Candidate

Promoted

Oct 2018 – Jul 2022 · 3 yrs 9 mos · Vienna, Austria

My research work is in the area of topological image analysis and pattern recognition. Currently, I am developing an algorithm reinforced with theory for irregular image pyramids. The reconstructed image from the image pyramid preserves the topological content and high-frequency texture information of the image. The algorithm and related theory can be used in different image processing applications such as multi-resolution image segmentation, topological image analysis, contour detection, solving stereo correspondence, decomposition of 2D space into cells called slope regions. I am also interested in merging machine learning algorithms with my current research to attain better results and widen the scope of applications to other fields.

Image ProcessingPattern RecognitionAlgorithm DevelopmentQuantitative ResearchComputer Science

Pre.Doc. University Assistant

Jun 2018 – Jun 2022 · 4 yrs · Vienna, Austria

Subjects assisted:
Pattern Recognition, Digital Image processing, Scientific works, special issues in Computer Vision.

Dhirubhai ambani institute of information and communication technology

2 roles

Teacher Assistant

Aug 2015 – May 2017 · 1 yr 9 mos

Contributed as a Teaching Assistant in the following subjects:
Signal Processing, Probability and Statistics, Analog and Digital communication

Masters Student

May 2015 – Aug 2017 · 2 yrs 3 mos

M.Tech in Information and Communication Technology (ICT) with specialization in Signal Processing. My master's research focused on estimating (w/o deep learning) the graph topology (graph Laplacian matrix) for the graph signals with the prior assumption that signals have a sparse representation in the frequency domain. The research falls under algebraic graph signal processing. For application purposes, we demonstrated image denoising for all three classes of images - natural, piecewise smooth (depth map), and texture images. It was observed that the algorithm performs better for texture images as compared to the natural and piecewise-smooth images. I had a successful publication and presentation in the IEEE International Workshop on Multimedia Signal Processing (MMSP) 2017 - Luton, London.

Signal ProcessingGraph Signal ProcessingImage DenoisingQuantitative Research