Sanchita Goswami
I'm a
About Me
I am an aspiring entrepreneur, passionate coder, and dedicated researcher with a profound interest in Data Science, AI, and Machine Learning. My journey is a fusion of technology, innovation, and research, where I strive to create transformative solutions that bridge the gap between ideas and impact. Beyond the realm of technology, I am also an investor and stock market analyst, constantly exploring strategic avenues for financial growth and sustainability.
Curiosity fuels my quest for knowledge, drawing me toward the intricate mysteries of nature and space science. Innovation is at the heart of my endeavors, driving me to develop intelligent systems and forward-thinking solutions that contribute to a more advanced and efficient world. Currently, I am deeply invested in self-development and mental refinement, continuously honing my skills, perspectives, and approach toward challenges.
With an analytical yet creative mindset, I embrace every opportunity with optimism and precision. My vision extends beyond conventional boundaries, integrating aesthetics with functionality to craft solutions that redefine possibilities. Whether through pioneering AI models, strategic investments, or cutting-edge research, I am committed to shaping the future with ingenuity and excellence.
Data Analyst & Researcher
I have a strong foundation in Data Science, AI, and Machine Learning, with expertise in Deep Learning, Computer Vision, and Natural Language Processing. My work involves building high-precision models that extract valuable insights from complex datasets, optimizing performance through advanced algorithms and techniques. I have developed AI-driven solutions for diverse domains, including environmental sustainability, healthcare, and industrial automation, integrating neural networks and generative AI to solve real-world challenges efficiently.
- Birthplace: West Bengal, India
- City: Aalen , Germany
- Degree: Graduate
- Email: sng000613@gmail.com
Beyond technical proficiency, my approach to research is driven by curiosity, innovation, and a problem-solving mindset. I thrive on exploring interdisciplinary applications, combining AI with fields like semiconductor optimization and renewable energy. My ability to analyze patterns, optimize models, and develop data-driven strategies allows me to contribute effectively to research and innovation. With a strong commitment to continuous learning and improvement, I aim to push the boundaries of AI-driven advancements, making impactful contributions to both academia and industry.
Projects - AiML
Hackathons - Data Science & AiML
Research Publications - Interdisciplinary work
Conferences attended
Skills
I have expertise in programming (Python, AI/ML, Deep Learning, Image Processing, Computer Vision, NLP), data science model development, and research-driven innovation. With experience in mentoring, teaching Python for IoT, and guiding students in AI projects, I excel in knowledge sharing and technical leadership. Additionally, I have hands-on experience in investment analysis, business strategy, and interdisciplinary research.
Resume
I am a dynamic problem-solver with a strong technical foundation in AI, ML, and data-driven innovation. My experience spans across research, software development, and real-world AI applications, complemented by my expertise in investment strategy and business analytics. I have successfully led and mentored multiple projects, fostering innovation and collaboration. With a passion for transforming ideas into impactful solutions, I strive to bridge technology and business for a smarter, data-driven future.
Summary
Data & ML Analyst
Results-driven Data and ML Analyst with expertise in developing high-precision AI models, extracting actionable insights from complex datasets, and driving data-driven innovation across diverse industries.
- Aalen, Baden-Württemberg, Germany
- sng000613@gmail.com
Education
M.Sc. in Advanced Materials & Manufacturing
2025 - 2027
Hochschule Aalen, Aalen, Germany
• Focus areas : Lithium-ion Batteries, Image Processing, ML/DL
• Master's Thesis at IMFAA Research Institute
Bachelor of Computer Science & Engineering (Spcl. in Data Science)
2025 ( International Semester Exchange )
Hochschule Aalen, Aalen, Germany
• Focus areas : Magnets, Image Processing, ML/DL
• Research Project at IMFAA Research Institute
Bachelor of Computer Science & Engineering (Spcl. in Data Science)
2021 - 2025
Presidency University, Bengaluru, India
• CGPA : 8.0
• Key Focus : Data Science, AiML, Deep Learning, NLP, Reinforcement Learning
Professional Experience
Research Assistant
2025 - 2027
Hochschule Aalen, Germany
- Currently working as a Research Assistant in Germany, contributing to interdisciplinary research projects across applied AI and materials-focused domains.
- Developing and optimizing Image Processing pipelines and Machine Learning / Deep Learning models, including data preprocessing, feature extraction, model training, and performance evaluation.
- Conducting research involving magnet-based systems and battery technologies, supporting experimental analysis, data-driven modeling, and system-level understanding.
- Executing data annotation and labeling workflows to generate high-quality datasets for supervised and semi-supervised learning tasks.
- Applying research and development methodologies, including experimental design, benchmarking, validation, and iterative optimization of algorithms and models.
- Collaborating within a research environment to translate experimental findings into scalable, reproducible research outputs.
JRF and Mentor
2023 - 2024
Presidency University, Bengaluru, India
- Conducted advanced research in AI, ML, and computer vision, contributing to innovative projects across multiple domains.
- Mentored 60+ students in IoT, AI, and Raspberry Pi applications, guiding them through hands-on projects and technical problem-solving.
- Co-guided two French exchange students on AI/ML-driven IoT innovations during their semester at the university.
- Acquired professional expertise in Microsoft Excel and PowerPoint, enhancing data analysis, visualization, and presentation skills.
- Assisted in maintaining and managing a database of over 600 students, ensuring streamlined operations and project tracking.
- Organized and administered major events, including the World’s Largest Expo 2023, coordinating 2600+ students.
- Developed AI-based models for railway safety, medical diagnostics, environmental monitoring, and industrial automation.
- Worked on interdisciplinary research, integrating deep learning, BCI technology, semiconductor optimization, and sustainable energy solutions.
- Collaborated with faculty and researchers to publish studies in AI-driven healthcare, smart automation, and human-computer interaction.
- Received a monthly stipend while contributing to high-impact projects and assisting in the university's innovative research initiatives.
Achievements
As a passionate and driven computer science engineer, I have dedicated my journey to exploring the intersection of AI, ML, and data science, with a strong focus on computer vision, image processing, and NLP. My expertise spans across deep learning, neural networks, and generative AI, where I have developed high-precision models for real-world applications. I have actively contributed to cutting-edge research, interdisciplinary innovations, and industrial advancements, integrating AI with IoT, automation, and semiconductor optimization. Beyond technical development, I have mentored students, collaborated on international projects, and played a key role in managing large-scale events and databases. With a keen interest in renewable energy, finance, and investment, I aim to bridge the gap between technology and business, driving impactful solutions for a smarter and more sustainable future.
- All
- 2022
- 2023
- 2024
Projects
I have actively contributed to a diverse range of projects spanning AI, ML, Deep Learning, Computer Vision, Image Processing, and IoT, with a strong emphasis on real-world applications. My work focuses on developing optimized models for predictive analytics, environmental sustainability, workplace safety, healthcare, and smart infrastructure. I have leveraged neural networks, NLP, and generative AI to create high-accuracy solutions for automation, surveillance, and decision-making. Additionally, I have explored interdisciplinary research, integrating AI with semiconductor optimization and renewable energy to enhance efficiency. Through hands-on experience, I have designed and implemented innovative solutions that bridge technology with societal impact, ensuring precision, scalability, and real-time adaptability.
Gen AI Bot for Investment Planning
Developing a Gen AI bot designed to assist users in planning their investments. The bot should understand the customer's financial status and goals through a detailed questionnaire and provide personalized investment strategies.
OncoRTT Model
Late-stage drug development failures are usually a consequence of ineffective targets. Thus, proper target identification is needed, which may be possible using computational approaches. In this work, we developed OncoRTT, a deep learning (DL)-based method for predicting novel therapeutic targets. OncoRTT is designed to reduce suboptimal target selection by identifying novel targets based on features of known effective targets using DL approaches.
Sentimental Analysis of Social Media
This project analyzed sentiment across Amazon, Facebook, and Twitter. Differentiating user behaviors and platform functionalities were highlighted. Valuable insights were gained for enhancing user engagement and satisfaction. Future research could explore more platforms and advanced techniques.
High School Data Analysis
High School Data Analysis with respect to various parameters including family constraints
Cryptographic Algorithm
Contains multiple approach algorithm including traditional as well as modern Encryption and Decryption techniques
Python Documentary
An easy approach to grasp Python concepts with various code snippets
ISARC 2023 Construction Sustainibility
Creating a Prediction Model with utmost accuracy to achieve highest Compressive Strength in cement based on multiple features composed in a dataset of a huge amount of data
Market Basket Analysis
Market basket analysis is used by companies to identify items that are frequently purchased together. Market basket analysis is frequently used by restaurants, retail stores, and online shopping platforms to encourage customers to make more purchases in a single visit. This is a use-case of data science in marketing that increases company sales and drives business growth and commonly utilizes the Apriori algorithm.
IPL Sold Price Prediction
IPL sold price prediction analysis in ML involves using machine learning models to predict the auction prices of players based on various factors such as past performance, player statistics, team requirements, and market trends. By leveraging algorithms like regression, decision trees, or deep learning, the model identifies patterns in historical auction data to estimate a player's probable bid price. Features like batting average, bowling economy, strike rate, and player popularity contribute to price prediction accuracy. This analysis helps franchises make data-driven decisions and optimize their bidding strategies.
Prediction for Heart Disease
Heart disease prediction analysis in Machine Learning involves using algorithms to analyze medical data and identify patterns that indicate the likelihood of heart disease. By training models on datasets containing patient information such as age, blood pressure, cholesterol levels, and lifestyle factors, ML can help in early detection and risk assessment. Techniques like logistic regression, decision trees, and deep learning improve prediction accuracy. This aids healthcare professionals in making informed decisions, enhancing preventive care, and reducing mortality rates.
Pima Indians Diabetes Database-Analysis
This dataset is originally from the National Institute of Diabetes and Digestive and Kidney Diseases. The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset.Several constraints were placed on the selection of these instances from a larger database. In particular, all patients here are females at least 21 years old of Pima Indian heritage.
German Credit Data Analysis
German credit data analysis using the Gini Index measures the discriminatory power of a credit scoring model in distinguishing between good and bad borrowers. The Gini Index, derived from the Lorenz curve, quantifies inequality, where a higher value indicates better predictive accuracy. In credit risk assessment, it helps evaluate the effectiveness of classification models by comparing cumulative true positive and false positive rates. The German credit dataset, commonly used in machine learning, contains attributes like age, credit amount, and payment status to predict default risk. By applying the Gini Index, analysts can optimize credit decision-making and improve financial risk management.
MBA Salary Prediction
Simple Linear Regression Using (OLS) Ordinary Least Squares method. Developing a regression model to predict Salary based on Percentage in Grade 10.
IBM Attrition Data Analysis
What are the demographic, employment, and performance-related factors associated with employee attrition, and how do these factors contribute to the overall attrition rate in the company? Additionally, what insights can be derived from analyzing the dataset to understand the patterns and potential reasons behind employee attrition?
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An intelligent educational bot designed to simplify online resource organization and enhance study planning, providing structured guidance for efficient learning.
SPIRIT - Solar Powered Bot
SPIRIT is an innovative solar-powered robotic vehicle designed for precision agriculture. It seamlessly integrates digging, planting, cutting, and spraying functions, ensuring efficiency and accuracy in farming tasks. Equipped with a robust battery backup, SPIRIT operates uninterrupted, even in low-light conditions. Its sleek yet functional design embodies modern engineering while remaining cost-effective, making advanced agricultural automation accessible and sustainable.
EduBot
A smart educational bot crafted to streamline online resource management and optimize study planning, ensuring a well-structured and effective learning experience.
Patient Case Similarity
Our proposed model processes unstructured symptom descriptions, transforming them into meaningful features using NLP techniques like TF-IDF vectorization. With a combination of BiLSTM layers and attention mechanisms, the system not only delivers accurate predictions but also enhances interpretability by identifying key symptoms influencing diagnostic outcomes. This innovation paves the way for more precise, efficient, and scalable Clinical Decision Support Systems.
Research Publications
I have actively contributed to research in AI, ML, and interdisciplinary fields, focusing on innovative applications that drive real-world impact. My work spans deep learning, computer vision, NLP, and data-driven optimization, exploring solutions for automation, healthcare, environmental sustainability, and industrial advancements. By integrating AI with domains like semiconductor optimization, renewable energy, and human-computer interaction, I have aimed to enhance efficiency, accuracy, and decision-making across various sectors. Through collaborations, mentorship, and hands-on experimentation, I have refined my expertise in developing high-precision models and intelligent systems that address complex challenges.
Enhancing Medical Diagnosis Through Deep Learning: A Novel Approach to Patient Case Similarity Using Bidirectional LSTM with Attention Mechanism
JNRID - JOURNAL OF NOVEL RESEARCH AND INNOVATIVE DEVELOPMENT · Jan 20, 2025
This research introduces a deep learning approach for medical diagnosis automation using BiLSTM with an attention mechanism. It processes unstructured symptom descriptions through NLP techniques like TF-IDF and sequential text processing. The model, featuring a 128-unit BiLSTM layer and dropout-regularized dense layers, achieved 90.51% accuracy on a symptom-disease dataset. The attention mechanism enhances interpretability by highlighting crucial symptoms influencing diagnosis. This study demonstrates the potential of attention-based deep learning in improving clinical decision support systems.
Revolution of Artificial Intelligence in Computational Chemistry Breakthroughs
Chemistry Africa · May 31, 2024
The paper explores AI’s transformative role in computational chemistry, enabling chemists to process large datasets, optimize reactions, and design new molecules efficiently. It reviews advancements in ML techniques, hardware, and algorithms that enhance precision in chemical research. The study highlights emerging AI trends and their impact on accelerating discoveries. It also examines AI integration into 14 key chemistry software and databases. This synergy underscores AI’s potential to revolutionize chemical science.
14. Ambient assisted living through passive brain-computer interface technology for assisting paralyzed people
ELSEVIER · Jan 23, 2025
The book "Artificial Intelligence Applications for Brain-Computer Interfaces" explores advancements, challenges, and future prospects of noninvasive BCIs. It covers multimodal signal processing, neuro-rehabilitation, cognitive workload assessment, and ambient assisted living. The book highlights how BCIs connect the brain with external devices, analyzing neural signals through machine-intelligent models. Each chapter presents problem statements, methodologies, and related research, making it a valuable resource. It serves researchers, academicians, and professionals in BCI, prosthetics, computer vision, and mental state estimation.
Contact
Feel free to reach out to me for collaborations, research discussions, or professional opportunities in AI, ML, and data-driven innovation. I am always open to engaging in meaningful conversations, whether it's about interdisciplinary research, industry applications, or innovative projects. You can connect with me via email or LinkedIn, and I’d be happy to discuss how we can work together to drive impactful solutions.
Address
Aalen, Baden-Württemberg, Germany
Email at
sng000613@gmail.com