Hi, I'm Avishek Biswas

Data Scientist at Quiq Inc.
MS, Clemson University.


First and foremost, I'm a Machine Learning Guy


I have been for some time now. I have undertaken projects in a lot of different disciplines of ML - Computer Vision, NLP, Reinforcement Learning, Network Science, Robotics, Biomedical Data Science, Autonomous Driving, etc. Some of these projects have been at an industrial end-to-end scale, some were research projects that have led to publications and poster presentations, some were academic projects, and some were crazy adventures I took on a random Saturday afternoon. I tend to get better results at certain domains than others, but I have gone on tours with them with all of them. That said, I don't like to put myself in a single bracket - I don't aim to only be an NLP guy or only a Robotics guy. At least, not as of today. To me, Machine Learning is a larger organism and the more I learn about the state of ML at scale, the better I can apply myself in it's subdomains.


Awards and Achievements


  • Awarded the "Best Paper Award, 1st position" in ACM Siggraph Conference on MIG 2021 for the paper Motor Babble: Morphology-Driven Coordinated Control of Articulated Characters


  • Awarded the "Outstanding Master's Student in Computer Science" by Clemson University School of Computing on April 2020.



Background

I am working as a Data Scientist at Quiq, one of the fastest-rising startups in the world of customer-business chat services. At Quiq, we spend hours developing and deploying cutting-edge Machine Learning and AI techniques to enhance the quality and efficiency of conversations between end-users and live agents. My role requires a ton of NLP and Deep Learning research, and also train models with production deployment and scalability in mind, and striving for quiq releases and immediate product impact.


Prior to working at Quiq, I completed my Master of Science (MS) in Computer Science from Clemson University in May 2021. At Clemson, I worked for three out of my four semesters as a Graduate Research Assistant (GRA) and Graduate Teaching Assistant (GTA). My research experiences at Clemson cover a variety of fields: Artificial Intelligence, Machine Learning, Character Animation, and Network Science.


My Master's Thesis at Clemson involved using Deep Reinforcement Learning to train physics-based character controllers. The thesis covers two research projects - "Learning Coordinated Locomotion from Latent Coactivation Space" and "Training Physics-based Characters to Dance to Music". The former project, titled Motor Babble: Morphology-Driven Coordinated Control of Articulated Characters, recently won the best paper award at MIG (Motion In Games) 2021. The latter project won the Peer-Voted Best Poster Award at MIG 2020.


Here is a more detailed description of my projects

Industrial Experience

Data Scientist - Advanced Conversational Techniques, QUIQ INC (May 2021 - Present)

This is my first industrial stint as a Data Scientist! At Quiq, we enhance customer experiences and make businesses more efficient by augmenting conversations with AI & NLP. I am the first Data Scientist hired at Quiq, which not only put me in a position of responsibility but also accelerated my growth in the field. Being an active part of building end-to-end Machine Learning frameworks, from data cleaning to model training to deployment, has given me a wholesome view of Machine Learning and has been an incredible learning experience on top of my time as a research assistant in grad school.


Key Achievements:

  • Primary author of non-trivial deep learning model architectures customized to our domain and novel problem set

  • Develop Deep Learning models with production deployments and scalability in mind, resulting in fast releases and immediate product impact

  • Assist in ML engineering and deployment efforts, including deployment of a high-scale, low-latency prediction model in the browser using TensorFlowJS



Senior Software Developer - Capgemini (2016 - 2019)

I worked with Capgemini India as a Senior Software Developer from Sep-2016 to Mar-2019. I was part of a Oracle Applications DBA (Database Adminstrator) Team. My professional experience working as an Oracle DBA in Capgemini has given me invaluable technical insights into Database Systems, Automation, and Linux. Equally importantly, it has enriched my leadership qualities, team spirit, communication skills, and my ability to deliver my best in critical situations!


Key Achievements:

  • My team was awarded the Team Award of Excellence for the “Wave 2” Oracle EBS Migration project for Norway Posten

  • Automated several modules of the project through shell scripts and reduced manual workload of our team. Here is one such example script to automate the transfer of Oracle Concurrent Request Log/Out files from Production to Dev servers: Github Link.

  • Mentored and trained team of three in Oracle E-Business Suite (EBS) and Linux Environment

Graduate Research Experience


Dec 2019-May 2021: Working with Dr. Victor Zordan, Dr. Ioannis Karamouzas, and Dr. Avinash Ranganath in the intersection of Physics-based Character Control and Deep Reinforcement Learning.

Please visit the Projects page for further details!


Teaching Assistant Experience

Spring 2020: CPSC 4050/6050 - Computer Graphics, by Dr. Daljit Singh Dhillon.

Fall 2020: CPSC 4420/6420 - Artificial Intelligence, by Dr. Ioannis Karamouzas

Spring 2021: CPSC 8810 - Deep Reinforcement Learning, by Dr. Ioannis Karamouzas


Courses


    • Relevant Courses (Clemson University):

      • Fall 2019:
        CPSC 6420: Artifiicial Intelligence
        CPSC 6050: Computer Graphics
        CPSC 8040: Data Visualization

      • Spring 2020:
        CPSC 8400: Design and Analysis of Algorithms
        CPSC 8810: Motion Planning
        CPSC 8430: Deep Learning

      • Fall 2020
        CPSC 8420: Advanced Machine Learning
        CPSC 8480: Network Science

    • GPA: 4.0/4.0


Extra Curricular Activities

I used to compete in over the board Chess tournaments until couple of years back. In my free-time, I still like to play some Blitz on Chess.com.