A very warm welcome to my personal portfolio. more of a phenomenal college website!!

This is just a fun project and is not intended to copy any college website or cause any harm. The content, style and language used here are for portfolio purposes only. Enjoy exploring!

I, Robin Bansal, have started Doctor of Philosophy (Ph.D.) in Computer Science and Engineering at the Indian Institute of Information Technology (IIIT) Guwahati from November 2025. At IIITG, I am engaged as Junior Research Fellow (JRF) on a MeitY‑sponsored project under the guidance of Dr. Radhika Sukapuram, Assistant Professor, Department of CSE. My long‑standing passion for technology, systems, and problem‑solving gradually evolved into a deeper interest in research, system optimisation, and algorithmic design — ultimately leading me to pursue a PhD to explore these domains further and contribute to meaningful, impactful innovations.

(Of course I needed a PhD to become the Director of IITB. This place may be Butibori, not Bombay — but we don’t run on “low qualifications, high confidence.” We run strictly on “high sarcasm, low budget.”)

I completed my B.Tech in Computer Science and Engineering from the Indian Institute of Information Technology (IIIT) Nagpur in May 2025 with a CGPA of 7.23. My undergraduate journey was defined by hands‑on learning and system‑level thinking, during which I immersed myself in data science, software engineering, and machine learning through continuous learning and practical application. This process strengthened my technical foundations and significantly enhanced my problem‑solving abilities.

Till October 2025, I worked as a Software Engineer at Thriveni Transport and Logistics Private Limited (formerly Lloyds Surya Private Limited), a joint venture between Lloyds Metals and Energy Limited (LMEL) and Thriveni Earthmovers Private Limited (TEMPL) . I joined the company at the very beginning of the project as the third employee after the VP and Manager in July 2024. The goal was clear, to transform LMEL’s traditional, manual logistics operations into a fully digital, structured, analytics-driven ecosystem capable of becoming a major logistics player in the Vidarbha region.

My role here was exceptionally broad, multidisciplinary, and foundational. I began by conducting in-depth research into mining-origin load patterns, identifying opportunities for optimizing return loads, and analysing inefficiencies in the existing truck market. I wrote requirement documents for new innovations, collaborated with survey agencies, and collected historical operational data from LMEL and TEMPL. Using Excel, Power BI, and structured databases, I analysed trends, generated visual insights, and designed operational logic to support decision‑making. Over the course of a year, I contributed to building the organisation’s digital logistics infrastructure from the ground up — studying global logistics models (Rivigo, VRL, Delhivery, Indian Railways, Uber, Swiggy), understanding their operational algorithms, exploring new innovations in logistics like Trailer Swapping and Relay modelling, and tailoring solutions to our constraints. I deeply analysed the company’s logistics challenges, designed algorithms to match our requirements, and contributed significantly to software module design, architectural decisions, and operational workflows. Developed it with team in 4 months and delivered Phase 1 of the project in Sept 2025, marking a major milestone in the company’s digitalisation roadmap.

Prior to this, from May 2024 to July 2024, I completed a Project Internship at IIIT Guwahati, sponsored by the Science and Engineering Research Board (SERB). The project focused on optimizing edge service caching to reduce latency in networked systems. By implementing a solution that strategically divided cache between public and private storage, we achieved up to a 36.24% improvement in latency and reduced operational costs by over 83%. This project allowed me to dive deeper into advanced algorithms, multithreading, and system optimization, providing a strong foundation in real-time systems.

Alongside my internships, I developed several personal projects exploring machine learning, systems, and algorithmic research. One notable project is my Deep Q‑Network (DQN) stock trading system, where I built a reinforcement learning framework in PyTorch trained on AAPL (2020–2022) using experience replay, target networks, and epsilon‑greedy exploration. I incorporated RNN/LSTM/GRU architectures and over twenty technical indicators (SMA, EMA, MACD, RSI, VWAP, ATR, Bollinger Bands), and developed a Python trading simulator with transaction costs, drawdown penalties, and risk‑aware constraints. The system achieved a +60.89% testing return compared to an 8.45% baseline, demonstrating the potential of reinforcement learning for financial risk optimisation.

Beyond technical work, I have embraced leadership roles during my time at IIIT Nagpur. I am also an active member of the DotSlash Club, competitive programming club, where I collaborate with fellow students to enhance problem-solving skills and promote a culture of coding excellence on campus.

Reflecting on my journey, I recognise how each experience — from competitive programming and research internships to system‑level engineering work — has shaped my interest in research, optimisation, and algorithmic design.

Looking ahead, I am excited about the opportunities that lie within computing and technology. I aspire to apply my skills to meaningful research and real‑world engineering problems that advance both academic understanding and practical innovation.

Thank you for taking the time to explore my portfolio. I hope to continue growing and learning, and I look forward to any opportunities that may come my way.

Mr. Robin Bansal

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“All izzz well” - Robin Bansal