Sayak Mukhopadhyay
@sayakmukhopadhyay
I am a Decision Scientist specializing in ML, computer vision, and AI deployments for real-world systems.
IndiaWhat I'm looking for
I am a Decision Scientist and machine-learning practitioner who builds end-to-end AI solutions and automation for industry and research problems, focusing on computer vision, model deployment, and data-driven decisioning.
My work spans production deployments—such as a Streamlit ML application on Azure and a supply-chain lead-time automation flow—to research breakthroughs. I developed an AUV dock-detection system achieving a 97% success rate and a 93% 3D pose estimator, contributed to multiple peer-reviewed publications, and hold a published patent.
I seek roles where I can bridge research and production, deliver reliable ML systems, and drive measurable business and operational impact in collaborative, engineering-driven teams.
Experience
Work history, roles, and key accomplishments
Designing an end-to-end automation flow for lead time calculation and intelligent transportation method recommendation using SQL, Python, and AERA to optimize supply chain efficiency for a UK pharmaceutical client.
Analyst
TresVista
Jul 2024 - Apr 2025 (9 months)
Deployed a user-friendly ML GUI using Streamlit on Azure enabling clients to select tasks, choose models, upload datasets, and generate reports for classification, regression, and time series forecasting, improving accessibility for non-technical users.
Summer Intern
CSIR-CMERI
Jun 2023 - Jul 2024 (1 year 1 month)
Designed a 3D pose estimation system for AUV docking using OpenCV, achieving 93% accuracy in clean water conditions and integrating with multi-modal detection workflows.
Research Intern
CSIR-CMERI
Jan 2024 - Jun 2024 (5 months)
Applied machine learning and computer vision to improve underwater docking for an AUV, developing an object detection and 3D pose estimation pipeline that achieved a 97% success rate in varied turbid conditions.
Research Intern
SCAAI
Jan 2023 - Jun 2023 (5 months)
Researched disease prediction using a UMLS disease-to-symptoms mapping and trained neural networks achieving 98% accuracy, and deployed a user-facing model for symptom-based disease prediction.
Education
Degrees, certifications, and relevant coursework
Symbiosis Institute of Technology
Bachelor of Technology, Electronics and Telecommunication Engineering
Grade: 84%
Bachelor of Technology in Electronics and Telecommunication Engineering with an aggregate of 84%.
Guru Teg Bahadur Public School
Class XII (CBSE), Higher Secondary
Grade: 83%
Completed Class XII under the CBSE curriculum with an aggregate of 83%.
St. Peter's School
Class X (ICSE), Secondary Education
Grade: 88%
Completed Class X under the ICSE curriculum with an aggregate of 88%.
Availability
Location
IndiaAuthorized to work in
Job categories
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