About

The Quick Stats

Hi, I’m Sadiksha! I am a Computer Science major with a Mathematics minor in the Honors program at Louisiana Tech University, originally from Nepal. I have always had a deep, burning curiosity about how a computer’s brain actually works at its absolute baseline—and how math acts as the secret language that ties it all together. But while I am incredibly passionate about analyzing systems and numbers, outside of class I am much more focused on the creative, warm, and human side of life.

My Escapes and Hobbies

My brain is powered by a continuous rotation of chocolates, hot donuts, dumplings, and basically any spicy food I can find. When I am not studying, you can usually find me exploring my favorite creative outlets and outdoor escapes:

• The Great Outdoors: I have an absolute love for traveling, especially when it involves majestic mountains, fresh rain, and water. I am really not a fan of freezing winters or scorching summers, but a misty, rainy day in the mountains is my perfect element.
• Crocheting: I love stitching up cozy little creations on my couch. It is my favorite way to unwind, slow down, and make something tangible with my hands.
• Dancing: Dancing is the ultimate way for me to reset my mind and get moving. I love channeling spatial awareness, rhythm, and physical energy into choreography.

Big, Bold Goals

I always set my sights high and have a very clear picture of where I want to go next:

The European Connection: My dream is to live and work in Europe. I am actively building my academic portfolio to bridge into a top-tier European graduate school program for the 2028-2029 academic year.

The AI/ML Pathway: I want to work as an AI/ML systems engineer, focusing on the smart frameworks that make modern technology run smoothly.

My Approach to Systems and Ethics

To me, building responsible technology is not about high-level policy or superficial guidelines. It is a strict engineering requirement. I prioritize security-first design and deterministic validation because trustworthy systems must be auditable from the silicon upward. Working with low-level hardware optimizations and cybersecurity pipelines has taught me that true ethics means building transparent and verifiable systems. If an optimization benchmark cannot be independently reproduced, or if a model acts as an un-auditable black box, then it fails both technically and ethically. This is why my research emphasizes reproducibility, why I document hardware decisions, and why I choose tools that prioritize transparency.