Akash Adhikari

AI Researcher

Bengaluru, Karnataka, India6 yrs 11 mos experience

Highly Stable

Key Highlights

Expert in Machine Learning and Data Analysis.
Developed autonomous AI systems for quantitative research.
Strong background in statistical modeling for sports analytics.

Stackforce AI infers this person is a Sports Analytics and Machine Learning expert with a focus on data-driven decision making.

Contact

rajaadhikari23@gmail.com LinkedIn

Skills

Core Skills

Machine LearningData AnalysisStatistical Data AnalysisApplied MathematicsStatistical ModelingProbability Theory

Other Skills

C++Computer VisionConvolutional Neural Networks (CNN)Deep LearningMathematical ModelingMicrosoft ExcelMicrosoft OfficeProbabilityPython ProgrammingScikit-Learn

Experience

Wolfe research, llc

Senior Quant Researcher

Dec 2024 – Present · 1 yr 3 mos · Remote

Developing an autonomous AI research analyst to orchestrate full-cycle quantitative research : capable of autonomous planning, reasoning and action across the entire research lifecycle.

Data AnalysisMachine LearningPython ProgrammingStatistical ModelingDeep Learning

Ericsson

2 roles

Senior Machine Learning Engineer

Mar 2022 – Dec 2024 · 2 yrs 9 mos

Machine Learning Engineer

Jul 2020 – Feb 2022 · 1 yr 7 mos

University of manitoba

Mitacs Globalink Research Intern

May 2019 – Jul 2019 · 2 mos · Winnipeg, Manitoba, Canada

Non Parametric estimation of goal scoring rate in extra-time in a soccer match

Statistical Data AnalysisApplied Mathematics

Society for industrial and applied mathematics (siam)

General Secretary

Jul 2018 – Oct 2019 · 1 yr 3 mos · IIT(ISM) Dhanbad

National research university — higher school of economics

Summer Research Sports Analyst

May 2018 – Jul 2018 · 2 mos · Moscow, Russian Federation

Università degli studi di padova

Bowling strategy building in limited overs Cricket matches : An application of Statistics

Jun 2017 – Jun 2017 · 0 mo · Venice Area, Italy

Presented research paper on predictive modeling in MathSport International
2017 Conference, Padua, Italy (University of Padua, Italy)
The project involved developing of a cumulative probability model to analyze bowling
performance for cricket team in limited over cricket match. Ball-by-Ball data of ten
different bowlers belonging to the top rated countries in the game was analyzed.
Performance Indicator for a bowler in the form of probability to take wickets given
number of runs he concede(RBW) or the number of balls he delivers(BBW) was designed.
The purpose of research was to build a model for cricket teams to strategize bowling
performance.