Danish Athar

dathar [at] purdue [dot] edu

danish8athar [at] gmail [dot] com

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I am a graduate student in Computer Engineering (CE) at Purdue University, West Lafayette, Indiana, USA. I recently graduated with a B.S. in Computer Science (High Distinction, cGPA: 3.80/4.00) from Lahore University of Management Sciences (LUMS) in Pakistan.

I am part of the Purdue Internet and Systems Lab (Purdue-ISL) where I am working under the supervision of Dr. Sanjay Rao on problems related to Traffic Engineering in Datacenters and WANs. Specifically, I am trying to leverage machine learning and optimisation techniques to optimise traffic routing.

Previously, I have been part of the Networks and Systems research group during my undergraduate studies at LUMS, collaborating on projects in browser caching, web affordability, and LLM-based automation of network operations. There, I was primarily advised by Dr. Zafar Ayyub Qazi alongwith Dr. Ihsan Ayyub Qazi and Dr. Zartash Afzal Uzmi.

My research interests include distributed systems, networking algorithms for ML, and the intersection of ML and AI with networked systems. My previous research work includes projects on AI-enabled smarter, semantic web browser caching and LLM-based IP geolocation from reverse DNS hostnames.

I am always looking for research collaborations or internship roles in the areas of networking, distributed systems, AI applications and software engineering for Summer and Winter breaks. Please feel free to reach out if you have any opportunities or suggestions!

Education

  • Purdue University, West Lafayette, Indiana, USA
    Graduate Student, Electrical and Computer Engineering (ECE)
    August 2025 - Present
  • Lahore University of Management Sciences (LUMS), Lahore, Pakistan
    B.S. in Computer Science; cGPA: 3.8/4.0 (Graduated with High Distinction)
    Sep. 2021 - June 2025

Publications

Research Experience

I have also worked on the following projects:
  • Small Model Syndrome: Treatable with Prompting?
    Course Project for ECE57000: Artificial Intelligence. Study inspired by MedPrompt, done for much smaller model sizes. Shows that small generalist models can rival fine-tuned specialist models when guided by effective prompting. [PDF]

  • L³R: Leveraging Language to Locate Routers!
    Undergraduate senior project at LUMS (PK) in collaboration with RIPE (NL) and GEODE (FR). Proposed a multi-agentic framework for IP geolocation and additional information retrieval using reverse DNS hostnames and large language models (LLMs). Evaluated the method on real-world hostname datasets from CAIDA used in previous geolocation research, matching and beating state-of-the-art techniques that require a lot more manual input. [PDF]

  • Embedding The Truth: Approximate Caching for Fact Checking
    Course Project for CS6303: Topics in Large Language Models. Explored the feasibility of reusing fact-checking claims across organizations and languages to improve efficiency and reduce costs. Used an approximate caching approach with multilingual embeddings in a vector database to identify recurring claims. [PDF]

  • Utilising LLMs for Streamlined Analysis of PTA Datasets
    Course project for the Topics in Internet Research course at LUMS. Idenitified ways for efficient analysis of Pakistan Telecommunication Authority (PTA) datasets using LLMs. [PDF]

  • A Framework for Improving Web Affordability and Inclusiveness
    Assisted the authors of this paper. Conducted a user study with 35 participants comparing web page quality and UX for Opera Mini, Brave and HBS-based affordable web frameworks. [Link to published paper (SIGCOMM 2023)]

Teaching Experience

  • Graduate Teaching Assistant, Purdue University
    • ECE36800: Data Structures (Fall 2025, Spring 2026)
  • Head Teaching Assistant, LUMS
    • CS-582: Distributed Systems (Fall 2024)
  • Teaching Assistant, LUMS
    • CS-382: Network-Centric Computing (Spring 2025)
    • CS-382: Network-Centric Computing (Spring 2024)
    • CS-100: Introduction to Programming (Fall 2023 and Summer 2023)
  • Teaching Assistant, FutureTech
    • Served as the teaching assistant for the FutureTech (for more info on the Decoding The Internet module: a details site I made for my FutureTech students) sessions held at LUMS in summers of 2023 and 2024.
  • On-Site Instructor, CodeKids PK
    • Taught programming concepts to young learners using block-based and no-code platforms.

Work Experience

  • On-Site Instructor, CodeKids PK (June 2024 – July 2024)
    • Taught fundamental programming concepts to 20 young learners using block-based and no-code coding platforms, achieving a 95% satisfaction rate in post-class surveys.
  • Programming Intern, SenPi (Remote) (June 2022 – September 2022)
    • Worked on web development using the MERN stack.
  • Content Advisor, SenPi (January 2020 – December 2023)
    • Guided the development of high-quality educational content and instructional design, including strategic content planning, curriculum design, market research, and assessment design.
  • Content Development Specialist, OED Pakistan (Lahore) (October 2020 – October 2021)

Other Projects

  • Distributed Key-Value Store | Golang
    • Developed a fault-tolerant distributed key-value store using the Raft consensus algorithm, including leader election and log replication.
  • Distributed Hash Table | Python
    • Created a distributed hash table using socket programming, supporting a peer-to-peer model with failure tolerance.
  • Command Line Shell | C
    • Implemented a basic shell replicating UNIX shell functionalities, including pipelining and command chaining.
  • Basic File System | C
    • Implemented a simplified version of a UNIX file system that organizes memory into superblocks, inodes, and data blocks.
  • Second Time Around | MERN Stack
    • Developed a web application for a marketplace featuring auctions and donations with ML-powered recommendations.

Skills

  • Programming Languages: C, C++, Python, Golang, JavaScript, Haskell, TypeScript, HTML
  • Technologies & Tools: Agent Development Kit (ADK by Google), Android Debug Bridge (ADB), Android Studio, Appium, Bash, CAIDA’s Hoiho, ChromeDevTools, Docker, Figma, Git, Gurobi, LaTeX, LangChain, MatPlotLib, MongoDB, NumPy, OpenCV, Pandas, Postman, PyAutoGUI, PyTesseract, React, RIPE Atlas toolkit, SciKit, Selenium, Socket Programming, SQL, WebPageTest, Wireshark

Awards

  • Graduation with High Distinction award at LUMS for outstanding academic performance during my undergraduate studies.
  • Dean's Honor List placement for all my years of study at LUMS.

Misc

  • In addition to problem-solving, I absolutely love cars and racing.
  • Returnal, a rogue-like game that counts on your failures for progress, is the hardest game I have completed, but has also been my most enjoyable gaming experience in recent times!
  • I also play a lot of League of Legends :D