Hello! I'm Srijan Reddy
Welcome to My Site!
Bio
My Story
As a natural born go-getter, my passion has continuously driven me to expand my knowledge, experience, and relationships. With a strong background and diverse skill set, I’m confident in the creative ideas and successful solutions I bring to the table. Keep exploring my site to learn more information about me, and reach out directly with any questions.
Education
- B.Tech Honors with Specialization in AI and ML
- CGPA: 8.73
Internships
§ Researching ways to improve the consistency of an Imitation Learning agent using Lipschitz costs
§ Researching a novel idea that could help hybrid RL/IL agents learn from motion capture data
§ Currently 6th on the leaderboard amongst 80+ teams in the ongoing NeurIPS competition, MineRL
§ Worked under Dr. Balaraman Ravindran (Head of RBCDSAI), to train an RL agent to play Minecraft
§ Augmented Affable’s business offering by co-developing Facebook influencer dashboard UI
§ Improved user experience for Affable’s core product via new chat and payment functionalities
§ Achieved a 50% decrease in SDLC time by breaking a monolith frontend into microservices
§ Migrated about 45% of the main pages in the frontend codebase from AngularJS to Angular
Open Source Projects
§ Increased team productivity by 50% (PRs made) by facilitating greater ownership and teamwork
§ Empowered members to enable greater decentralization to support upto 50 members in the team
§ Achieved a 25% PR merge time reduction by designing an onboarding process for new members
§ Created simplified approaches to migrate complex coding patterns from AngularJS to Angular
§ Analysed and resolved critical errors, at an organization level, that blocked progress across projects
§ Implemented parts of file system module and introduced version-based installer on Windows
Research
Diabetic Retinopathy Detection
§ Created an economical prototype using DL & Edge Computing for remote diagnosis in tier 4 cities
§ Designed a system for prioritizing patients based on ailment severity and waiting time in queue
Anomaly detection in networks using reinforcement learning
§ Created a model to predict anomalies in communication networks to prevent SLA violations
§ Trained a Deep Q network on 122 features to supress anomalies & keep the signal strength strong
Achieving autonomy in cars using deep reinforcement learning
§ Devised “Perception Aided Deep Deterministic Policy Gradient” approach for training RL agents
§ Achieved ~100% increase in the mean reward obtained on custom benchmarks built using Carla
Real-time crowd analytics
§ Developed DL models to spot people, gender, emotion and attentiveness on a live video feed
§ Visualized real time gender distribution and attention heatmaps on a progressive web application