Vasileios Vittis
University of
Massachusetts, Amherst

ABOUT ME

PhD student in DREAM Lab of College of Information and Computer Science, University of Massachusetts Amherst, working under the supervision of Alexandra Meliou and Peter Haas. Graduated from the School of Electrical and Computer Engineering of Technical University of Crete. I received my diploma (5 year curriculum) (top-5.8%) under the supervision of Antonios Deligiannakis.

I am excited about streaming distributed systems and theoretical machine learning algorithms. The last two years, I am actively working on Database Systems, Distributed Streaming Engines, Ensemble Learning, Concept Drift adaptation and Linear Optimization Techniques. For more information you can take a look in my CV.

I am first and foremost a problem solver, and search widely to find problems where mathematics (simple or complicated) can answer scientific questions.

Publications

Thesis: Online Ensemble Classification Algorithms of Big Data Streams at Apache Flink PDF

Award & News

  • [Feb 2023] Poster Accepted at NEDB
  • [September 2022] UMass CICS scholarship $4,000
  • [April 2021] Attended ICDE (virtual)
  • [April 2019] Attended ECESCON11 in Thessaloniki, Greece
  • [June 2018] Attended WoWMoM in Chania, Greece
  • [Feb 2019] 1st Place Entrepreneurship Initiative Start-up Pitch Greece Section Link

    Rε-Scan was a startup effort that wanted to reduce the world’s environmental footprint enabling future generations to live in a cleaner and more sustainable planet with minimum wasted resources. Our goal was to make recycling as easy as possible and we could do that by creating a live community around the RεScan brand with millions of users as passionate about recycling as we are. Our Participation / Presentation



Online Material that I find useful

(...that surely have helped me a lot)

Courses
  1. Machine Learning Specialization (Andrew Ng) DeepLearning.AI
  2. MIT 18.065: Matrix Methods in Data Analysis, Signal Processing and Machine Learning, Spring 2018
  3. MIT 6.041: Probabilistic Systems Analysis And Applied Probability 2010
  4. MIT 6.S191: Introduction to Deep Learning
  5. CMSC 828W: Foundations of Deep Learning
  6. MIT 6.438: Algorithms for Inference
  7. MIT 15.S12: Blockchain and Money
Textbooks
  1. Artifical Intelligence: A Modern Approach (S.Russell, P.Norvig)
  2. Pattern Recognition and Machine Learning (C.M. Bishop)
  3. Introduction to Linear Optimization (D. Bertsimas, J.N. Tsitsiklis)
  4. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (A. Géron)


My technical skills as Research Data Scientist

The key concepts that I am very familiar with!

Voluntary Actions


These two years, were the years that I will never forget. Year long, I was trying to give to the members of our branch, the best possible experience, by organising seminars, talks and workshops that could help them be a better version of themselves, not only educationally but also socially. All together, as a team, organised more than 20 different events such as educational trips (FORTH), different competitions (Google Hashcode, IEEEXtreme, Capture the Flag: Hacking Competition) to name, but a few.

I mostly contributed to the team's future by creating sub-teams with different scientific directions, following the structure of our university, such as telecom team, rocket team, energy/battery management team and web development team, where I strategically put students, who had attended advanced courses, to teach the younger ones, who wanted to evolve and learn more.

Personally, I was the "teacher" in the web development team, where I helped young students build their own personal website, using frameworks in order to be able updating them along their academical career with new info.
I was in the technical support of IEEE's Polytechnic website using Django tools, performing tasks such as updating, debugging, and expanding IEEE Website
I have been the Ambassador for my university of the 24h programming competition of IEEE (IEEEXtreme 2018). My tasks were the organization of time and space for the competition, finding support of technical equipment, approaching sponsors to support the event, surveillance of competitor to name but a few.